Multi-target treatment planning and delivery and virtual positioning for radiation therapy

Abstract

Methods for patient setup and patient target region positioning for irradiating multiple patient target regions in a single treatment session are disclosed herein. Virtual positioning is a method that can be used to align patient target regions without physically moving the patient using a patient platform. Instead, the planned fluence is updated to reflect the current position of the patient target region by selecting a positioning reference in a positioning image, calculating a positioning function based on the positioning reference point, and calculating the delivered fluence by convolving the positioning function with a translation-invariant emission filter. Mosaic multi-target positioning divides the planned fluence map for multiple patient target regions into sub-regions that can be positioned individually. Decoupled multi-target positioning involves generating a separate planned fluence map for each target, but limiting the cumulative fluence map to ensure that dosimetry goals are met.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to U.S. Provisional Patent Application No. 62 / 873,742, filed on July 12, 2019, the entire contents of which are incorporated herein by reference. Background Art

[0003] Radiation therapy involves acquiring planning images of the patient and one or more tumor regions and designing a treatment plan that provides a prescribed dose of radiation to the tumor region. In addition to determining the tumor region to be irradiated, radiation therapy also attempts to limit the irradiation of healthy tissue. This may include identifying radiosensitive or radiation avoidance regions (e.g., organs at risk or OARs) and designing a treatment plan that will not irradiate these radiation avoidance regions beyond the prescribed range. In most cases, the treatment plan assumes that the absolute and / or relative positions of one or more tumor regions, OARs, and healthy tissue regions during treatment match (or almost match) their absolute and / or relative positions when the planning images were acquired. Once a treatment plan that meets the tumor region and OAR dosimetry goals is designed, the patient can be placed on a patient platform or bed of the radiotherapy system so that the patient feels quite comfortable on the bed and is in a position suitable for radiation delivery. One or more positioning images of the patient can be acquired on the bed (e.g., fan beam CT scan, cone beam CT scan, and / or PET scan). The position of each of the one or more tumor regions, OARs, and / or other anatomical structures can be determined using positioning images, and their absolute positions relative to the therapeutic radiation source and / or their relative positions to each other can be compared with their positions from the treatment planning images. If any tumor regions and / or OARs have moved, the radiotherapy system can calculate during treatment planning how the patient should be moved to match their position, and to the extent possible, the couch can be adjusted to implement that movement.

[0004] However, the patient setup and positioning of the tumor region and / or OAR relative to the coordinates of the radiotherapy system may be time-consuming, particularly because the size, shape and / or / or position of the tumor region and / or OAR may change between the acquisition time of the planning image and the treatment period, and in some cases, may continue to change during the treatment period. In addition, patient setup and positioning are usually optimized for the treatment of a single target area, and may not be easily adapted to the treatment of multiple target areas. For example, a patient setup arrangement and positioning may be suitable for one tumor region, but may not allow the delivery of a prescribed dose for another tumor region, and / or may cause undesired irradiation of OARs. Accurately registering a patient to a plan intended to treat multiple targets simultaneously involves mapping the new actual positions of multiple targets of the patient at the time of delivery to the original positions of multiple targets in the treatment plan in some way. Since one tumor may move relative to another, there may not be a single translation and orientation movement of the patient that can align all tumors with the plan. That is, the adjustment, movement and rotation of the patient to align one tumor with the expected position in the plan may cause other tumors to lose alignment.

[0005] A method of delivering radiation to multiple patient target areas involves performing a series of patent settings and positioning. For example, for a first patient target area, the bed can be adjusted to position the patient to a setup position suitable for delivering radiation to the first target area, a positioning image can be obtained to position the first target area, and then radiation is delivered to the first target area. These steps are then repeated for each target area, which may be time-consuming (especially if the patient setup involves opening the bunkhouse door so that a clinician or technician can enter to adjust the patient on the bed), and because each iteration is individually processed, it may result in overdosing of OARs and / or healthy tissues, and / or underdosing of target areas (e.g., when trying not to overdose the OARs). Therefore, improved radiation therapy planning, patient setup and registration, and positioning methods are needed, especially for irradiation of multiple target areas. Summary of the invention

[0006] Disclosed herein are methods of treatment planning, patient setup, positioning, and radiation delivery for irradiating multiple patient target areas in a single treatment session or fraction.

[0007] A treatment planning method for irradiating multiple target regions may include selecting a planning positioning reference point for each target region and calculating a translation-invariant transmit filter for each target region based on the selected planning positioning reference point. A treatment planning fluence map may be calculated based on the translation-invariant transmit filter and the planning positioning reference point for each target region, the map specifying the radiation fluence delivered to the multiple target regions and the radiation levels to OARs and healthy tissues.

[0008] Additionally or alternatively, the translation invariant transmit filter can be expressed as a function shift and orientation operator of the radiation fluence delivered to multiple target regions based on a planned positioning reference point for each target region. For example, a function shift operator can include a function that interpolates a two-dimensional or three-dimensional map using a shift. For example, a function orientation operator can include a function that interpolates a two-dimensional or three-dimensional map using a rotation along an axis in two-dimensional or three-dimensional space. For example, a function orientation operator can be used to interpolate (e.g., transform) a two-dimensional (or three-dimensional) fluence map for delivery based on the position of the positioning reference point on the day of treatment. This can include calculating a translation of the fluence map in (x,y) coordinates, and / or scaling the fluence map in (x,y,z) and / or along The fluence map is rotated about an axis in the treatment plan. In some variations, the treatment planning method may include defining a perimeter in the treatment plan fluence map around each patient target region including a region of low fluence values. The treatment planning method for multiple target regions may include calculating an individual treatment plan including an individual fluence map for each target region, combining the individual fluence maps into a cumulative treatment plan fluence map, and iteratively modifying the cumulative treatment plan fluence map based on one or more constraints (e.g., dose constraints, such as keeping high fluence regions separate from each other, satisfying OAR fluence limits, and satisfying dose objectives for each target region). After iteratively modifying the cumulative treatment plan fluence map according to the desired constraints, the treatment planning method may include defining a perimeter in the treatment plan fluence map around each patient target region including a region of low fluence values, and may optionally include separating the iteratively modified cumulative treatment plan fluence map into individual fluence maps for each patient target region along the defined perimeter. In some variations, one or more of a function shift operator and an orientation operator may be used during treatment plan optimization to calculate a fluence map based on a planned positioning reference point for each target region.

[0009] Optionally, in bio-guided radiation therapy (BgRT), where positron annihilation emission path data is acquired during a treatment session and used to calculate a delivered fluence, a treatment planning method may include defining a first region of interest (ROI) or radiation emission zone around a first patient target region and a second ROI or radiation emission zone around a second patient target region for a predetermined positional movement range for the first and second patient target regions. An output of the treatment planning method described herein may include a treatment planning fluence map defining a fluence to be delivered to each patient target region and radiation exposure levels for OARs and healthy tissues, and a set of translation-invariant emission filters for each planned positioning reference point associated with each patient target region. Alternatively or additionally, in treatment planning for BgRT, the treatment planning method may output a set of translation-invariant emission filters associated with a ROI (e.g., a biological emission zone (BFZ)) defined around each patient target region. Additionally or alternatively, the set of translation-invariant emission filters may include a function shift operator and / or a directional operator. Optionally, the output of the treatment planning method may include a set of radiation therapy machine instructions for execution by a radiation therapy system following patient setup and patient target region positioning.

[0010] In some variations, a method for virtual target region positioning and radiation delivery may include acquiring an image of a patient in a treatment position and identifying a patient target region in the acquired image, selecting a positioning reference point within the acquired image, wherein the positioning reference point corresponds to a planned positioning reference point, calculating a spatial offset based on movement between the positioning reference point and the planned positioning reference point, moving a boundary of a planned region of interest based on the spatial offset, wherein the boundary of the planned region of interest surrounds the patient target region, acquiring imaging data that has been spatially filtered by the moved region of interest, calculating a fluence delivered to the patient target region at each emission position of a therapeutic radiation source by convolving a set of emission filters with the acquired imaging data, and emitting the calculated fluence to the patient target region using the therapeutic radiation source.

[0011] In some variations, the bounds of the planned region of interest may include a spatial filter. In some variations, moving the bounds of the planned region of interest may include a roll correction factor representing a rotational translation of a positioning reference point relative to a planned positioning reference point. Apply rotation and translation to the planned region of interest. Calculating the delivered fluence may include combining a set of transmit filters with a roll correction factor Circular convolution.

[0012] In some variations, a treatment planning method for radiation delivery to multiple patient target regions may include identifying a first position of a first patient target region and a second position of a second patient target region in a patient planning image, defining a first region of interest having a boundary around the first patient target region, and defining a second region of interest having a boundary around the second patient target region. For a predetermined range of position movement of the first and second patient target regions, the boundaries of the second region of interest may be selected to surround the second patient target region. The first and second regions of interest may represent spatial filters configured to select imaging data acquired during a treatment session. The method may further include calculating a treatment planning fluence map for the first patient target region and the second patient target region, the treatment planning fluence map specifying a fluence to be delivered if the selected imaging data indicates that the first patient target region is within the boundaries of the first region of interest and the second patient target region is within the boundaries of the second region of interest.

[0013] In some variations, the first patient target area may be closer to the planned structure. In some variations, the first region of interest may be smaller than the second emission zone. In some variations, the planned structure may be an organ at risk (OAR). In some variations, the first patient target area may be closer to two or more planned structures than the second patient target area. In some variations, the method may further include designating a treatment plan reference point within the first region of interest as a positioning reference point to position the patient at the beginning of the treatment period. In some variations, the selected imaging data may be used to guide radiation delivery during the treatment period. In some variations, the treatment plan reference point may be a center point in the first patient target area.

[0014] In some variations, the imaging data may include positron annihilation emission path data. In some variations, the positron annihilation emission path is selected if it intersects at least one of the first and second emission regions. In some variations, the size of the second region of interest may include a range of locations of a second patient target region. In some variations, the imaging data may include one or more of positron emission tomography (PET) imaging data, computed tomography (CT) imaging data, and magnetic resonance imaging (MRI) imaging data.

[0015] Also disclosed herein is a method for patient setup and patient target region positioning for irradiating multiple target tissue regions. The method for patient setup and target registration / positioning may include positioning a patient on a patient platform or bed of a radiotherapy system, acquiring one or more positioning images of the patient, including one or more target regions and / or OARs, and selecting positioning reference points within one or more acquired positioning images. The selected positioning reference points may correspond to the planned positioning reference points of a specific patient target region and may represent the updated position of the patient target region. A fluence map for delivery to a specific patient target region may be calculated by calculating a positioning function based on the selected positioning reference points and applying the positioning function with a translation-invariant emission filter derived based on the planned positioning reference points. Alternatively or additionally, a translation-invariant emission filter may be derived from other planning parameters. For example, a fluence map for delivery to a patient target region may be calculated by calculating a delta function (e.g., a 3-D discrete delta function) based on the selected positioning reference points and convolving the delta function with a translation-invariant emission filter derived based on the planned positioning reference points and / or other planning parameters. In another example, a fluence map for delivery to a patient target region can be calculated by interpolating the fluence map with a movement or rotation based on a selected positioning reference point. In such a manner, the delivery fluence map can be updated with the current position of the patient target region and may not require the use of the bed to adjust the position of the patient. Positioning a patient target region by calculating a fluence map based on a positioning function according to a selected positioning reference point (e.g., a delta function or a Gaussian function centered at a selected positioning reference point) and a set of translation-invariant emission filters can be referred to as "virtual positioning". In some variations, the patient can be set on the bed once, and the acquisition of the positioning image, the selection of the positioning reference point, and the calculation of the delivery fluence map can be performed for each patient target region (e.g., one physical positioning / setting, multiple positioning image scans, corresponding to multiple virtual positioning of multiple patient target regions). Alternatively, the positioning image can be acquired once (e.g., when the patient is initially positioned in the radiotherapy system), and the selection of the positioning reference point and the calculation of the delivery fluence map can be performed for each patient target region (e.g., one physical setting, one positioning image scan, corresponding to multiple virtual positioning of multiple patient target regions) using the initially acquired positioning image.

[0016] In contrast, conventional treatment delivery methods include acquiring a positioning image (e.g., a positioning CT image) to physically position the patient and the patient target area on the patient platform to match the position of the patient target area determined at the time of treatment planning. In order to treat multiple patient target areas in a single treatment period, it may be necessary to physically reposition the patient before irradiating each patient target area, because the specific physical position of the patient that may be suitable for irradiating one patient target area may not be suitable for irradiating another patient target area. For each repositioning, an additional positioning image is acquired. In some variants, the positioning and repositioning of the patient may be provided by the patient platform. In addition, some treatment planning systems can be configured to output machine instructions (e.g., leaf types), which can then be moved according to the positioning image. However, the treatment planning system and method described herein are configured to output a fluence map and / or an emission filter of the delivery system for convolution with an image and / or a positioning function of a positioning reference point to generate a delivery fluence map. This can allow treatment of multiple patient target areas without repositioning the patient for each target area. The delivery fluence map can be segmented into machine instructions by the delivery system just before dose delivery. Thus, virtual positioning can eliminate or reduce the number of times to acquire scout images and physically position (and / or reposition) the patient for treatment of multiple patient target regions.

[0017] As an alternative or in addition to virtual positioning, a method for patient setup may include acquiring images of a first patient target area and a second patient target area. A first set of patient position movement vectors may be calculated based on the acquired images and a treatment planning image of the first patient target area. A second set of patient position movement vectors may be calculated based on the acquired images, the treatment planning image of the second patient target area, and the first set of patient position movement vectors. The patient may be positioned at a first location and / or position according to the first set of patient position movement vectors. The patient may be positioned at a second location and positioned according to the second set of patient position movement vectors. Positioning the patient according to the first set of patient position movement vectors may include moving a radiotherapy patient platform and / or a therapeutic radiation source according to the first set of patient position movement vectors. The patient may be positioned at a second location and adjusted according to the second set of patient position movement vectors. Positioning the patient according to the second set of patient position movement vectors may include moving a radiotherapy patient platform and / or a therapeutic radiation source according to the second set of patient position movement vectors. Moving the radiotherapy patient platform may include moving the platform along its X-axis, and / or Y-axis, and / or Z-axis. Moving the radiation therapy patient platform may include adjusting the yaw and / or pitch and / or roll of the platform, and moving the therapeutic radiation source may include adjusting the yaw / pitch / roll of a gantry coupled to the therapeutic radiation source. The first treatment planning image and the second treatment planning image may be the same treatment planning image. The acquired image may be a PET (positron emission tomography) image. The acquired image may be a CT (computed tomography) image. The acquired image may be an MRI (magnetic resonance imaging) image. In some embodiments, calculating the first and second sets of patient position movement vectors may occur before the therapeutic radiation source is activated. In some embodiments, a first position difference may be calculated by comparing the position of the first patient target area in the acquired image with the position of the first patient target area in the first treatment planning image. A second position difference may be calculated by comparing the position of the second patient target area in the acquired image with the position of the second patient target area in the second treatment planning image. If the first position difference or the second position difference exceeds a position difference threshold, a notification may be generated. The first patient target area and the second patient target area may include one or more tumor areas. The first patient target area may include a first portion of a tumor and the second patient target area may include a second portion of a tumor. The first and second sets of position movement vectors may include distance and direction translations. The directional translation may include a tilt angle.

[0018] A method for delivering radiation fluence to multiple patient regions may include transforming (also referred to as segmenting) a delivery fluence map into radiotherapy system machine instructions (e.g., therapeutic radiation source radiation emission parameters, multi-leaf collimator configurations for each emission position around a patient platform, etc.), and then executing the machine instructions by emitting radiation fluence from the therapeutic radiation source to the patient. The delivery fluence map for multiple patient target regions may be a combination of individual fluence maps calculated for each patient target region during virtual positioning and machine instructions for delivery to two or more patient target regions (e.g., all patient target regions), and may be segmented simultaneously. Alternatively or additionally, the individual fluence map for each patient target region may be segmented separately (e.g., sequentially). Optionally, in BgRT, positron annihilation emission path data is acquired during a treatment session and used to calculate the delivery fluence, and the delivery fluence map may be segmented into radiotherapy system machine instructions in real time, for example, within 500 ms or less between acquiring the emission path data and delivering the therapeutic radiation beam. The delivery fluence map may be a fluence map calculated from the emission path data, and virtual positioning may be achieved by moving or rotating the ROI.

[0019] A method for virtual target region positioning and radiation delivery may include acquiring an image of a patient in a treatment position and identifying a patient target region in the acquired image, selecting a positioning reference point within the acquired image, wherein the positioning reference point corresponds to a planned positioning reference point, calculating a fluence for delivery to the patient target region at each emission position of a therapeutic radiation source by calculating a positioning function based on the positioning reference point and applying the positioning function to a translation-invariant emission filter derived based on the planned positioning reference point, and emitting the delivery fluence to the patient target region using the therapeutic radiation source. The positioning function may be a delta function, and applying the positioning function to the translation-invariant emission filter may include convolving the delta function with the translation-invariant emission filter. Additionally or alternatively, the translation-invariant emission filter may include one or more function shift operators and orientation operators for delivering radiation fluence to multiple target regions based on the planned positioning reference point for each target region. For example, as described above, the function shift operator may include a function that interpolates a two-dimensional or three-dimensional map with a shift. The orientation operator may include a function that interpolates a two-dimensional or three-dimensional map using a rotation. For example, the interpolation may include one or more of linear interpolation, nearest neighbor interpolation, bicubic interpolation, spline interpolation, or Fourier shift interpolation. The positioning reference point may be a user-selected position within the acquired image and / or may correspond to a treatment plan isocenter defined relative to a patient target region during treatment planning. The first patient target region may be in a first treatment region of the patient defined during treatment planning and the second target region may be in a second treatment region of the patient defined during treatment planning. The first treatment region may include a first set of axial planes and may have an axial length of approximately 8 cm or less, and the second treatment region may not overlap with the first treatment region and may have an axial length of approximately 8 cm or less and may include a second set of axial planes. The center of the first treatment region and the center of the second treatment region may be colinear, for example along the IEC-Y axis and / or coplanar with the IEC-Y axis. In some variants, the first treatment region may overlap with the second treatment region.

[0020] The emission position of the therapeutic radiation source includes the position of the therapeutic radiation source relative to the position of the patient platform. The therapeutic radiation source can be mounted on a gantry that can rotate about a longitudinal axis, and the position of the therapeutic radiation source can be specified by the gantry angle about the longitudinal axis. The patient platform can be moved to different positions along the longitudinal axis.

[0021] In some variations, the therapeutic radiation source can be mounted on a gantry so that radiation can be delivered to the patient in discrete continuous arcs (e.g., non-coplanar VMAT, 4-pi VMAT). In some of these variations, these radiation delivery arcs may not be coplanar with each other (e.g., perpendicular to the longitudinal axis). The emission position can be specified as a discrete position along each arc and can be indexed by the arc. The patient platform can be configured to be repositioned to a predetermined position and orientation between each arc.

[0022] In some variations, the therapeutic radiation source can be mounted on a gantry so that radiation can be delivered at fixed points around a 4-pi or 2-pi hemispherical enclosure. In some of these variations, a set of emission locations can be specified as discrete locations based on a two-dimensional fluence map. The patient platform can be configured to move the patient to a set of predetermined positions and / or orientations between each fixed point.

[0023] The method may further include identifying a second patient target region in the acquired image, selecting a second positioning reference point for the second patient target region within the acquired image, wherein the second positioning reference point corresponds to a second planning positioning reference point, calculating a second delivered fluence at each firing position of the therapeutic radiation source by calculating a second positioning function based on the second positioning reference point and applying the second positioning function to a second translation-invariant transmit filter based on the second planning positioning reference point, and transmitting the second delivered fluence to the second patient target region using the therapeutic radiation source. The method may optionally include identifying a second patient target region in the acquired image, selecting a second positioning reference point for the second patient target region within the acquired image, wherein the second positioning reference point corresponds to a second planning positioning reference point, calculating a second delivered fluence at each firing position of the therapeutic radiation source by calculating a second delta function based on the second positioning reference point and convolving the second delta function with a second translation-invariant transmit filter based on the second planning positioning reference point, and transmitting the second delivered fluence to the second patient target region using the therapeutic radiation source. Radiating the first delivered fluence to the first patient target region and radiating the second delivered fluence to the second patient target region may occur simultaneously, and / or may occur sequentially.

[0024] In some variations, a method for virtual target region positioning and radiation delivery may include the steps of acquiring an image of a patient in a treatment position and identifying a patient target region in the acquired image, selecting a positioning reference point within the acquired image, wherein the positioning reference point corresponds to a planned positioning reference point, calculating a fluence for delivery to the patient target region at each emission position of a therapeutic radiation source by calculating a positioning function based on the positioning reference point and applying the positioning function to a translation-invariant emission filter derived based on the planned positioning reference point, and emitting the delivery fluence to the patient target region using the therapeutic radiation source.

[0025] In some variants, applying the positioning function to the shift-invariant transmit filter may include convolving the positioning function with the shift-invariant transmit filter. In some variants, the positioning function may be one of a delta function, a Gaussian function, a circular function, and an interpolation. In some variants, the Gaussian function may be a truncated Gaussian function. In some variants, the interpolation may be one of a linear, a bicubic, a spline, or a Fourier shift. In some variants, the acquired image may include one or more of a positron emission tomography (PET) image, an X-ray projection image, a computed tomography (CT) image, and a magnetic resonance imaging (MRI) image.

[0026] In some variations, the method may further include identifying a second patient target region in the acquired image and selecting a second positioning reference point for the second patient target region within the acquired image. The second positioning reference point may correspond to a second planned positioning reference point. The method may further include calculating a second delivered fluence at each emission position of the therapeutic radiation source by calculating a second positioning function based on the second positioning reference point and applying the second positioning function to a second translation-invariant emission filter based on the second planned positioning reference point, and emitting the second delivered fluence to the second patient target region using the therapeutic radiation source.

[0027] In some variations, the method may further include identifying a second patient target area in the acquired image and selecting a second positioning reference point for the second patient target area within the acquired image. The second positioning reference point may correspond to a second planned positioning reference point. The method may further include calculating a second delivery fluence at each emission position of the therapeutic radiation source by calculating a second delta function based on the second positioning reference point and convolving the second delta function with a second translation-invariant emission filter based on the second planned positioning reference point, and emitting the second delivery fluence to the second patient target area using the therapeutic radiation source. In some variations, emitting the first delivery fluence to the first patient target area and emitting the second delivery fluence to the second patient target area occur simultaneously. In some variations, emitting the first delivery fluence to the first patient target area and emitting the second delivery fluence to the second patient target area occur sequentially.

[0028] In some variations, the localization function is a first localization function (δ). The first translation-invariant transmit filter may include a first set of fluence map filters (P1, P2, ..., P i). The method may include calculating a positioning function (δ i ) to each emission position (i), δ i =proj i (δ). Each projection (δ i) may be a 2-D fluence distribution. Calculating the first delivered fluence may include calculating each projection (δ i ) and the corresponding fluence map filter (P i ) convolution, f i =P i ★δ i To calculate the first delivered fluence map (f i ), and delivering the first fluence may include moving the therapeutic radiation source to each emission position (i) and delivering the first fluence according to a first delivery fluence map (f i ) emits radiation to a first patient target area. In some variations, each projection (δ i ) may be an m×n matrix, where m is the number of multileaf collimator leaves, and n is a number selected during treatment planning. In some variations, n is the number of beam stations selected during treatment planning. In some variations, the first positioning function may be one of a delta function, a Gaussian function, a circular function, and an interpolation. In some variations, the Gaussian function may be a truncated Gaussian function. In some variations, the interpolation may be one of a linear, a bicubic, a spline, and a Fourier shift.

[0029] In some variations, the second translation-invariant transmit filter may include a second set of fluence map filters (p_21, p_22, ..., p_2 ) calculated for each transmit position (i) during treatment planning. i ). The method may include calculating a second positioning function (δ_2 i ) to each emission position (i), δ_2 i =proj i (δ_2), where each projection (δ_2 i ) is a 2-D fluence distribution. Calculating the second delivered fluence may include calculating each projection (δ_2 i ) and the corresponding fluence map filter (p_2 i )Convolution, f_2 i =p_2 i ★δ_2 i To calculate the second delivered fluence map (f_2 i ) delivering the second calculated fluence may include moving the therapeutic radiation source to each emission position (i) and delivering the second calculated fluence according to the second delivered fluence map (f_2 i ) emits radiation to a second patient target area. In some variations, each projection (δ_2 i) may be an m×n matrix. In some variations, m is the number of multileaf collimator leaves and n is the number selected during treatment planning. In some variations, n is the number of beam stations selected during treatment planning. In some variations, the second positioning function may be one of a delta function, a Gaussian function, a circular function, and an interpolation. In some variations, the Gaussian function may be a truncated Gaussian function. In some variations, the interpolation may be one of a linear, a bicubic, a spline, and a Fourier shift. In some variations, delivering the calculated fluence may include applying the delivered fluence map (f i ,f_2 i ) into multiple radiation therapy system machine instructions for each transmission position.

[0030] In some variations, delivering the calculated fluence may include splitting the calculated fluence into a plurality of radiation therapy system machine instructions for each shot position. In some variations, delivering the second calculated fluence may include splitting the second calculated fluence into a plurality of radiation therapy system machine instructions for each shot position.

[0031] In some variations, the plurality of radiotherapy system machine instructions may include one or more multi-leaf collimator configurations for each emission position. Emitting the radiation fluence may further include moving the leaves of the multi-leaf collimator to the multi-leaf collimator configuration corresponding to the emission position of the therapeutic radiation source and emitting the radiation pulses.

[0032] In some variations, the plurality of radiation therapy system machine instructions may further include therapeutic radiation source emission (e.g., pulse) parameters for each emission position. Emitting radiation pulses may include emitting radiation having therapeutic radiation source pulse parameters corresponding to the emission position of the therapeutic radiation source. In some variations, calculating the delivered fluence map (f i ,f_2 i ) may further include convolving each projection in the first or second set of projections with a corresponding translation-invariant fluence map filter and applying a virtually flat filter correction factor (FF):

[0033] (f i )=FF·(p i ★δ i );(f_2 i )=FF·(p_2 i *δ_2 i ).

[0034] In some variations, the virtually flat filter correction factor (FF) is an mxn matrix and is the inverse of the flat profile of the radiation beam emitted by the therapeutic radiation source.

[0035] In some variations, the delivered fluence map (f i ,f_2i ) may further include convolving each projection in the set of projections with a translation-invariant fluence map filter, applying a virtually flat filter correction factor (FF), and a distance compensation factor

[0036] In some variants, d i represents the distance from the emission position i to the center of the patient target area defined during treatment planning, and d′ i represents the distance from the emission position i to the center of the patient's target area determined at the time of radiation delivery.

[0037] In some variations, the positioning reference point may be a user-selected position within the acquired image. In some variations, the positioning reference point may correspond to a treatment plan isocenter defined relative to a patient target region during treatment planning. In some variations, the first patient target region may be in a first treatment region of the patient defined during treatment planning and the second target region may be in a second treatment region of the patient defined during treatment planning. In some variations, the first treatment region has an axial length of about 8 cm or less and includes a first set of axial planes, and the second treatment region has an axial length of about 8 cm or less and does not overlap with the first treatment region. The second treatment region may include a second set of axial planes. In some variations, the center of the first treatment region and the center of the second treatment region may be colinear along the IEC-Y axis and / or coplanar with the IEC-Y axis. In some variations, the first treatment region and the second treatment region may overlap. In some variations, the emission position of the therapeutic radiation source may include a position of the therapeutic radiation source relative to a patient platform position. In some variations, the therapeutic radiation source may be mounted on a gantry that can rotate about a longitudinal axis, and the position of the therapeutic radiation source may be specified by a gantry angle about the longitudinal axis. In some variations, the patient platform is moveable to different positions along the longitudinal axis.

[0038] In some variations, the delivered fluence map (f i ,f_2 i ) may further include comparing each projection in the set of projections with a delta function δ i ,δ_2 i The translation-invariant fluence map filter p′,P_2′ is convolved with the delta function with an angular shift The δ function of is circularly convolved, where the patient target area is located at position δ LOC and δ_2 LOC Outside the isocenter,

[0039] δ i =proj i (δ)*δ i,roll

[0040]

[0041] (f i )=(p i ′★δ i )

[0042] δ_2 i =proj i (δ_2)★δ_2 i,roll

[0043]

[0044] (f_2 i )=(p_2 i ′★δ_2 i )

[0045] A method for delivering radiation to multiple patient target regions may include acquiring a scout image at the beginning of a treatment session, identifying a first target region and a second target region in the scout image, moving a first fluence map subregion of a treatment planning fluence map so that a non-zero high fluence region of the first fluence map subregion is co-located with the first target region in the scout image, moving a second fluence map subregion of the treatment planning fluence map so that a non-zero high fluence region of the second fluence map subregion is co-located with the second target region in the scout image, delivering the moved first fluence map subregion to the first target region, and delivering the moved second fluence map subregion to the second target region.

[0046] The treatment plan fluence map can be divided into first and second fluence map sub-regions by defining the boundaries of each sub-region along a non-zero low dose region of the treatment plan fluence map. Delivering the first and second moving fluence map sub-regions may include dividing the moving first and second fluence map sub-regions into a plurality of radiotherapy system machine instructions for each emission position of a therapeutic radiation source. The radiotherapy system machine instructions may include one or more multi-leaf collimator configurations and therapeutic radiation source control parameters for each emission position. The method may optionally include acquiring imaging data during a treatment session and modifying the moving first fluence map sub-region based on the acquired imaging data before delivering a fluence to a first target region. Alternatively or additionally, the method may include acquiring imaging data during a treatment session and modifying the moving second fluence map sub-region based on the acquired imaging data before delivering a fluence to a second target region.

[0047] The first fluence map sub-region that delivers the movement and the second fluence map sub-region that delivers the movement can occur simultaneously and / or can occur sequentially. In some variants, the first fluence map sub-region that delivers the movement and the second fluence map sub-region that delivers the movement can occur sequentially. The positioning image may include a CT image and / or a PET image and / or an MRI image. The method may optionally include comparing a high fluence area of ​​the first fluence map sub-region with the position of the first target area to define a first positioning correction, comparing a high fluence area of ​​the second fluence map sub-region with the position of the second target area to define a second positioning correction, and adjusting the patient platform according to the first positioning correction before delivering the fluence to the first target area. After delivering the fluence to the first target area, the method may include adjusting the patient platform according to the second positioning correction before delivering the fluence to the second target area.

[0048] In some variations, delivering the moved first fluence map sub-region to the first target region may include selecting a positioning reference point representing a location within the positioning image, applying a positioning function calculated based on the positioning reference point to a first translation-invariant transmit filter calculated for the first target region during treatment planning to update the first fluence map sub-region, segmenting the updated first fluence map sub-region into a plurality of radiation therapy system instructions, and transmitting a radiation fluence to the first target region according to the first plurality of radiation therapy system instructions.

[0049] Applying the localization function may include convolving a first localization function (e.g., a first delta function or a first Gaussian function, such as a truncated Gaussian function) calculated based on the localization reference point with a first shift-invariant transmit filter. Delivering the moved second fluence map sub-region to the second target region may include acquiring imaging data of the second target region, convolving the imaging data with a second shift-invariant transmit filter calculated for the second target region during treatment planning to update the second fluence map sub-region, segmenting the updated second fluence map sub-region into a second plurality of radiation therapy system instructions, and transmitting a radiation fluence to the second target region according to the second plurality of radiation therapy system instructions.

[0050] In some variants, the acquired imaging data may be PET imaging data. Delivering the moved second fluence map sub-region to the second target region may include selecting a second positioning reference point within the second target region, calculating the second fluence map sub-region by applying a second positioning function calculated according to the second positioning reference point to a second translation-invariant transmit filter, segmenting the calculated second fluence map sub-region into a second plurality of radiotherapy system instructions, and emitting a radiation fluence to the first target region according to the second plurality of radiotherapy system instructions. Alternatively or additionally, delivering the moved second fluence map sub-region to the second target region may include selecting a second positioning reference point within the second target region, calculating the second fluence map sub-region by convolving a second positioning function (e.g., a first delta function or a first Gaussian function, such as a truncated Gaussian function) calculated according to the second positioning reference point with a second translation-invariant transmit filter, segmenting the calculated second fluence map sub-region into a second plurality of radiotherapy system instructions, and emitting a radiation fluence to the second target region according to the second plurality of radiotherapy system instructions. In some variants, the method may include adjusting the deliverable radiation dose to satisfy one or more dose constraints. In some variants, the one or more dose constraints may include one or more cost functions. In some variations, the one or more cost functions may include a cumulative cost function, with the weighting factor for each cost function being given by:

[0051] C=∑w i C i (x)+∑w k C k (Ax)+∑w m C m (Ax cumulative )+∑w n C n (x cumulative )

[0052] Where x is the fluence of the patient target area, A is the dose calculation matrix of the patient target area, and Ax cumulative is the cumulative planned dose and x cumulative is the cumulative planned injection.

[0053] A treatment planning method for radiation delivery to multiple patient target regions may include identifying a first position of a first patient target region and a second position of a second patient target region in a patient planning image, defining a first region of interest (ROI) having a boundary around the first patient target region (which may be a first emission zone), defining a second ROI having a boundary around the second patient target region (which may be a second emission zone), and calculating a treatment planning fluence map for the first patient target region and the second patient target region, the treatment planning fluence map specifying a fluence to be delivered if selected imaging data indicates that the first patient target region is within the boundaries of the first region of interest and the second patient target region is within the boundaries of the second region of interest. For a predetermined range of positional movement of the first and second patient target regions, the boundaries of the second region of interest may be selected to surround the second patient target region, and the first and second regions of interest may represent spatial filters configured to select imaging data acquired during a treatment session. The first patient target region may be closer to a planning structure. The first region of interest may be smaller than the second region of interest. In some variations, the planning structure may be an organ at risk (OAR). The first patient target region may be closer to two or more planning structures than the second patient target region. Some methods may further include designating a treatment planning reference point within the first region of interest as a positioning reference point to position the patient at the beginning of the treatment session. The selected imaging data may be used to guide radiation delivery during the treatment session. The treatment planning reference point may be a center point in the first region of interest, and in some instances may be a center point in the first patient target region. The imaging data may include positron annihilation emission path data (e.g., PET data), CT imaging data, and / or MRI imaging data. If the positron annihilation emission path intersects at least one of the first and second regions of interest, the positron annihilation emission path may be selected. The size of the second region of interest may include a series of locations of the second patient target region.

[0054] In some variations, a method for patient positioning and radiation delivery may include acquiring an image including a first patient target region and a second patient target region, and aligning the first patient target region within a first region of interest defined during treatment planning. If the second patient target region is located within a second region of interest defined during treatment planning, the method may include acquiring positron annihilation emission data including a plurality of response lines (LORs) using a positron emission detector array. If the LORs intersect the first region of interest and the second region of interest, the method may include calculating a delivery fluence by convolving the LORs with a translationally invariant emission filter defined for the corresponding region of interest during treatment planning. The method may further include emitting a delivery fluence using a therapeutic radiation source, wherein emitting the delivery fluence includes splitting the delivery fluence into a plurality of radiation therapy system machine instructions for each emission position of the therapeutic radiation source. The radiation therapy system machine instructions may include one or more multi-leaf collimator configurations and therapeutic radiation source emission (e.g., pulse) parameters for each emission position. In some variations, the image may include one or more of a positron emission tomography (PET) image, a computed tomography (CT) image, and a magnetic resonance imaging (MRI) image.

[0055] A method for positioning and registering a patient for a radiation therapy treatment session may include positioning the patient on a radiation therapy system platform so that a first patient target region is aligned with a location of a therapeutic radiation source and is within a first predetermined region of interest, and determining whether the location of a second patient target region is within a second predetermined region of interest. If the location of the second patient target region is within the second predetermined region of interest, the method may include continuing to deliver radiation to the first patient target region. If the location of the second patient target region is not within the second predetermined region of interest, the method may include generating a visual and / or audible notification. The first and second predetermined regions of interest may be calculated during treatment planning, and the location of the second predetermined radiation region of interest may be defined relative to the location of the first predetermined region of interest.

[0056] Optionally, some methods may include acquiring imaging data prior to delivering radiation to a second patient target region, wherein the first and second regions of interest are spatial masks configured to suppress imaging data having spatial characteristics that are not co-located with the first or second regions of interest for radiation. In some variations, the method may include determining whether the second target region is located within the second region of interest based on the acquired imaging data, and continuing to deliver radiation to the second target region if the second target region is located within the second region of interest. The acquired imaging data may be positron annihilation emission path data (e.g., PET imaging data), CT imaging data, and / or MRI imaging data. Delivering radiation may include splitting the delivered fluence into a plurality of radiotherapy system machine instructions for each emission position of a therapeutic radiation source. The radiotherapy system machine instructions may include one or more multi-leaf collimator configurations and therapeutic radiation source emission (e.g., pulse) parameters for each emission position.

[0057] In some variations, the method may further include adjusting the position of the patient when the position of the second patient target area is not within the second predetermined region of interest. In some variations, the method may further include adjusting the radiotherapy system platform to move the position of the second patient target area into the second predetermined region of interest. In some variations, the method may further include moving the planned fluence of the second patient target area according to the position of the second patient target area. In some variations, the method may further include delivering radiation, the delivering radiation including splitting the delivered fluence into a plurality of radiotherapy system machine instructions for each emission position of the therapeutic radiation source. In some variations, the method may further include radiotherapy system machine instructions including one or more multi-leaf collimator configurations and therapeutic radiation source pulse parameters for each emission position.

[0058] A method for radiation therapy may include acquiring an image including a first patient target region and a second patient target region, dividing a planned fluence map into a first fluence submap that delivers a first prescribed dose to the first patient target region, and a second fluence submap that delivers a second prescribed dose to the second patient target region, moving the first fluence submap to align with the first patient target region of the acquired image, moving the second fluence submap to align with the second patient target region of the acquired image, calculating a delivered fluence map by combining the moved first fluence submap and the moved second fluence submap, and delivering radiation to the first patient target region if a high fluence region of the moved first fluence submap and a high fluence region of the moved second fluence submap are not co-located with each other in the delivered fluence map. In some variations, a planning fluence map may be generated by identifying first and second patient target regions in a treatment planning image, calculating a first fluence map to deliver a first prescribed dose to the first patient target region, calculating a second fluence map to deliver a second prescribed dose to the second patient target region, and calculating the planning fluence map by combining the first and second fluence maps and adjusting the combined fluence map so that high fluence regions of the first and second fluence maps are not co-located with each other and the first and second patient target regions each receive a corresponding first and second prescribed dose. In some variations, the first fluence submap may include the first fluence map and the second fluence submap may include the second fluence map. In some variations, calculating the planning fluence map may include adjusting the combined fluence map based on one or more adjustment constraints so that the first fluence map and the second fluence map do not exceed a predetermined dose limit. In some variations, the method may include identifying an organ at risk in the treatment planning image. Calculating the planning fluence map may further include adjusting the combined fluence map so that the fluence to the organ at risk does not exceed the predetermined dose limit. In some variations, delivering radiation may include splitting the delivered fluence into a plurality of radiotherapy system machine instructions for each firing position of a therapeutic radiation source. In some variations, the radiotherapy system machine instructions may include one or more multi-leaf collimator configurations and therapeutic radiation source emission parameters for each emission position. In some variations, the method may include determining whether the delivered fluence map includes a fluence level to an organ at risk that exceeds a predetermined dose limit, and if the fluence to the organ at risk does not exceed the predetermined dose limit, delivering radiation to the first patient target area. In some variations, the planned fluence map may be generated as follows: identifying first and second patient target areas in the treatment planning image, calculating a first fluence map to deliver a first prescribed dose to the first patient target area, calculating a second fluence map to deliver a second prescribed dose to the second patient target area, and calculating the planned fluence map by combining the first and second fluence maps and iteratively adjusting the combined fluence map to satisfy a set of joint constraints while maintaining the first and second fluence maps as separate fluence maps. In some variations, the acquired image may include one or more of a positron emission tomography (PET) image, a computed tomography (CT) image, and a magnetic resonance imaging (MRI) image.

[0059] A planning fluence map may be generated by identifying first and second patient target regions in a treatment planning image, calculating a first fluence map to deliver a first prescribed dose to the first patient target region, calculating a second fluence map to deliver a second prescribed dose to the second patient target region, and calculating the planning fluence map by combining the first and second fluence maps and adjusting the combined fluence map so that high fluence regions of the first and second fluence maps are not co-located with each other, and the first and second patient target regions each receive a corresponding first and second prescribed dose. The first fluence submap may include the first fluence map and the second fluence submap may include the second fluence map. The planning fluence map may be reoptimized using, for example, a set of joint constraints while maintaining the first subfluence map and the second fluence submap as separate fluence maps. The method may further include identifying an organ at risk in the treatment planning image, and calculating the planning fluence map may further include adjusting the combined fluence map so that the fluence of the organ at risk does not exceed a predetermined dose limit. Delivering radiation may include splitting the delivered fluence into a plurality of radiotherapy system machine instructions for each emission position of a therapeutic radiation source. The radiotherapy system machine instructions may include one or more multi-leaf collimator configurations and therapeutic radiation source emission parameters for each emission position. Optionally, the method may include determining whether the delivered fluence map includes a fluence level to an organ at risk that exceeds a predetermined dose limit, and delivering radiation to the first patient target region if the fluence to the organ at risk does not exceed the predetermined dose limit.

[0060] In some variations, a separate treatment plan can be generated for each patient target area. Each of these plans can be individually optimized, aggregated, and then re-optimized based on a set of joint constraints while maintaining the treatment plans as separate entities. A separate fluence map can be generated based on each treatment plan and aggregated into a combined fluence map. During the treatment session, each separate fluence map can be moved independently, and their total dose volume histogram (DVH) can be confirmed before dose delivery.

[0061] Additionally or alternatively, one or more adjustment constraints (e.g., artificial constraints in addition to tissue constraints, such as adjustment structures) may be applied in addition to a predetermined set of constraints to ensure that the dose in a given zone (e.g., region) does not exceed a predetermined threshold. For example, one or more predetermined dose-limited zones may be added during treatment planning to maintain the zone as a "low-dose valley," which may be used to reduce the likelihood of dose "hot spots" that may occur when the fluence map for each patient target region moves independently during a treatment session. In some variations, one or more adjustment constraints may help facilitate decoupling of radiation delivery between two or more targets. Some variations of the adjustment constraints may limit the dose delivery angles.

[0062] Also disclosed herein is a method for generating a visualization graphical representation of radiation dose. A variation of the method for generating a visualization graphical representation may include generating a treatment plan for irradiating one or more patient target regions, wherein the treatment plan includes at least one or more treatment plan fluence maps, one or more planning images of each patient target region, and a corresponding nominal dose image, calculating a plurality of uncertainty data inputs representing treatment period uncertainty for each patient target region, calculating an expected dose to be delivered to each patient target region for each uncertainty data input in the presence of the uncertainty data input to derive a plurality of dose images, combining the plurality of dose images into a visualization graphical representation including a composite volume, wherein each dose image represents a frame in the composite volume, and displaying the visualization graphical representation on a display device.

[0063] In some variations, the treatment plan may further include one or more translation invariant transmit filters. The plurality of data inputs may include one or more scalar values, vector values, and / or volume values. In some variations, the composite volume may be a 4-D volume. The plurality of dose images may include 2-D dose image slices for each of the one or more patient target regions. The composite volume may include a 3-D dose volume for each patient target region, and each 3-D dose volume may include a 2-D dose image slice for each patient target region. In some variations, the method may include iterating the dose value at each point in each dose image, comparing the dose value to a first matching point in the minimum dose volume and a second matching point in the maximum dose volume to update the first and second matching points, iterating each point in the minimum dose volume, calculating a difference between the values ​​of the minimum dose volume and the nominal dose volume, storing the difference and the frequency of the difference in two frames of the delta dose volume, iterating each point in the maximum dose volume, calculating a difference between the values ​​of the maximum dose volume and the nominal dose volume, storing the difference and the frequency of the difference in another two frames of the delta dose volume, and rendering a surface plot for each four-frame slice of the delta dose volume, wherein the frequencies of the maximum values ​​are extruded from the 3-D plane along +Z, the frequencies of the minimum values ​​are extruded from the 3-D plane along -Z, and the values ​​at the points in the surface plot are represented by colors.

[0064] A variation of a method for generating a visualization graphic may include generating a treatment plan for irradiating one or more patient target regions, wherein the treatment plan may include at least one or more treatment plan fluence maps, one or more planning images of each patient target region, and a corresponding nominal dose image, calculating a plurality of uncertainty data inputs representing treatment period uncertainty for each patient target region, calculating an expected dose to be delivered to each patient target region for each uncertainty data input in the presence of the uncertainty data input to derive a plurality of dose images, combining the plurality of dose images into a visualization graphic including a composite volume, wherein each dose image represents a frame in the composite volume, and displaying the visualization graphic to a display device. In some variations, the treatment plan may further include one or more translation-invariant emission filters. The plurality of data inputs may include one or more scalar values, vector values, and / or volume values. The composite volume may be a 4-D volume. The plurality of dose images may include 2-D dose image slices of each of the one or more patient target regions. The composite volume may include a 3-D dose volume for each patient target region, and each 3-D dose volume may include a 2-D dose image slice for each patient target region. Optionally, the method may include iterating the dose value at each point in each dose image, comparing the dose value to a first matching point in the minimum dose volume and a second matching point in the maximum dose volume to update the first and second matching points, iterating each point in the minimum dose volume, calculating a difference between the values ​​of the minimum dose volume and the nominal dose volume, storing the difference and the frequency of the difference in two frames of the delta dose volume, iterating each point in the maximum dose volume, calculating a difference between the values ​​of the maximum dose volume and the nominal dose volume, storing the difference and the frequency of the difference in another two frames of the delta dose volume, and rendering a surface plot for each four-frame slice of the delta dose volume, wherein the frequencies of the maximum values ​​are extruded from the 3-D plane along the +Z axis, the frequencies of the minimum values ​​are extruded from the 3-D plane along the -Z axis, and the values ​​at the points in the surface plot are represented by colors.

[0065] Described herein is a visual graphical representation of radiation dose. A variation of the visual graphical representation may include a 3-D volume representing a patient's anatomy, wherein the 3-D volume includes a stack of 2-D patient anatomy images, and a 3-D dose surface map corresponding to a dose distribution for each of the 2-D patient anatomy images. The height of the 3-D dose surface map may represent a dose level according to a treatment plan for the patient, and a color value across the surface map may represent a probability value for the dose level for a treatment period.

[0066] In some variations, a graphical user interface for multi-target treatment planning may include a first graphical representation of a plurality of treatment volumes, each treatment volume including one or more patient target regions. Each treatment volume may span a different region of a patient and represent a different patient positioning, and a second graphical representation of dosimetric characteristics of each treatment volume. The first and second graphical representations may be configured to be simultaneously output to a display device.

[0067] In some variations, the dosimetric characteristics of all multiple treatment zones can be visualized simultaneously on a display device. In some variations, the dosimetric characteristics of each treatment zone can be individually visualized. In some variations, the dosimetric characteristics of each treatment zone can include one or more of a dosimetric target, a dose volume histogram, dose statistics, and target performance. In some variations, the third graphical representation can include a view of all patient target areas across multiple treatment zones and a visual marker representing the relative spatial relationship between one or more patient target areas. In some variations, the graphical user interface can further include a third graphical representation, which includes a view of multiple organs at risk (OARs) across multiple treatment zones and a visual marker representing the relative spatial relationship of each OAR to one or more treatment zones. In some variations, the graphical user interface can further include a third graphical representation, which includes a view of all patient target areas across multiple treatment zones and a first visual marker representing the relative spatial relationship between one or more patient target areas, and a fourth graphical representation, which includes a view of multiple organs at risk (OARs) across multiple treatment zones and a second visual marker representing the relative spatial relationship of each OAR to one or more treatment zones. In some variations, the graphical user interface can include a 3-D visualization representing the patient's anatomical structure. In some variations, the first graphical representation may be layered onto the anatomical 3-D visualization. In some variations, the first graphical representation may include a band for each of a plurality of treatment zones. Each band may have a range representing a dimension of its corresponding treatment zone. In some variations, the graphical user interface may include a first viewing mode depicting a subset of the plurality of treatment zones and a second viewing mode depicting all of the plurality of treatment zones. In some variations, the subset of the plurality of treatment zones may include a user-selected treatment zone. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] The present application can be understood by referring to the following description in conjunction with the accompanying drawings.

[0069] Figure 1A is a flow chart representation of a variation of a treatment planning method for SBRT virtual positioning.

[0070] Figure 1B is a flow chart representation of a variation of a treatment planning method for virtual positioning of BgRT.

[0071] Figure 2is a flow chart representation of a variation of the treatment planning method for mosaic multi-target localization.

[0072] Figure 3A-3B A flowchart representation of a variation of a treatment planning method for decoupled multi-target localization is depicted.

[0073] Figure 4 is a flow chart representation of a variation of a treatment planning method for BgRT-based localization.

[0074] Figure 5A is a flow chart representation of a variation of a method for treatment planning.

[0075] Figure 5B is a flow chart representation of a variation of a method for treatment planning.

[0076] Figure 5C is a flow chart representation of a variation of a method for treatment planning.

[0077] Figure 6 is a flow chart representation of a variation of a method for treatment planning.

[0078] Fig. 7A is a flow chart representation of a variation of a method for virtual positioning.

[0079] Figure 7B is a flow chart representation of a variation of a method for virtual positioning.

[0080] Fig. 8A is a flow chart representation of a variation of the method for mosaic multi-target localization.

[0081] Figure 8B is a flow chart representation of a variation of the method for mosaic multi-target localization.

[0082] Fig. 9 is a flow chart representation of a variation of a method for decoupling multi-target localization.

[0083] Fig.10 is a flowchart representation of a variation of a method for BgRT-based localization.

[0084] Fig.11A is a flow chart representation of a variation of a method of positioning a patient for radiation therapy.

[0085] Fig. 11B is a flowchart representation of a variation of the method.

[0086] Figures 12A-12F One variation of a process by which the patient position may be adjusted is shown.

[0087] Figures 13A-13F One variation of a process by which the patient position may be adjusted is shown.

[0088] Figures 14A-14F A variation of a process in which the position of a patient may be adjusted to irradiate two discrete patient target regions is shown.

[0089] Fig.15A A variation of a visualization graphic representing dose distribution and / or probability is depicted.

[0090] Fig. 15B A variation of a visualization representing a 3-D dose distribution (nominal, minimum, maximum dose levels) is depicted.

[0091] Fig. 15C A flowchart representation of a variation of the method for generating visualization graphics.

[0092] Fig.15D is a block diagram of a variation of the method for generating visualization graphs.

[0093] Fig.15E A flowchart representation of a variation of the method for generating visualization graphics.

[0094] Fig.16A A flowchart representation of a variation of the method for generating visualization graphics.

[0095] Fig. 16B is a block diagram of a variation of the method for generating visualization graphs.

[0096] Fig.17A A variation of a visualization diagram representing the delta dose distribution is depicted.

[0097] Fig. 17B A variation of a visualization diagram representing the delta dose distribution is depicted.

[0098] Fig. 17C Depicted is a variation of a visualization of the delta dose distribution representing the maximum dose level.

[0099] Fig.17D Depicted is a variation of a visualization of the delta dose distribution representing the nominal dose level.

[0100] Fig.17E Depicted is a variation of a visualization of the delta dose distribution representing the minimum dose level.

[0101] Fig.17F A variation of the visualization graph (nominal, minimum, maximum dose levels) is depicted.

[0102] Fig.18Ais a flow chart representation of one variation of a method for multi-target radiation delivery.

[0103] Fig.18B is a flow chart representation of one variation of a method for multi-target radiation delivery.

[0104] Fig.18C is a flow chart representation of one variation of a method for multi-target radiation delivery.

[0105] Fig.18D is a flow chart representation of one variation of a method for multi-target radiation delivery.

[0106] Fig.19 is a flow chart representation of one variation of a method for multi-target BgRT-based radiation delivery.

[0107] Fig. 20 is a flow chart representation of one variation of a method for multi-target radiation delivery.

[0108] Fig.21A One variation of a radiation therapy system is depicted that may be used with any of the methods described herein.

[0109] Fig. 21B Depicted is a cross-sectional view of another variation of a radiation therapy system that may be used with any of the methods described herein.

[0110] Fig. 21C Depicted is a schematic diagram of another variation of a radiation therapy system that may be used with any of the methods described herein.

[0111] Fig.22A It is a schematic diagram of the delta function based on spatial voxels.

[0112] Fig. 22B is an example of a virtually flat filter correction factor (FF) for a radiotherapy system with 64 MLC leaves and 20 patient platform beam stations.

[0113] Fig.23A is a schematic diagram depicting a moving positioning image of a patient.

[0114] Fig. 23B A sinusoidal diagram with rows and columns corresponding to the number of MLC leaves and the number of emission locations is depicted.

[0115] Fig.23C Dose distributions before and after a fluence shift are depicted (along the X-, Y-, and Z-axes, from left to right).

[0116] Fig.23DDepicted are the dose distributions observed at 90 degree emission angles / positions (along the X-, Y-, and Z-axes, from left to right) before and after a fluence shift.

[0117] Fig.24 The fluence shift as a function of delta over the MLC leaf index for a set of emission angles is plotted.

[0118] Fig.25 The fluence shift of the Gaussian function over the MLC leaf index for a set of emission angles is depicted.

[0119] Fig.26 The fluence shift of the truncated Gaussian function over the MLC leaf index for a set of emission angles is depicted.

[0120] Figure 27-29 Depicted are simulated color intensity plots of the localization function, which is a truncated Gaussian function with a σ-value of 2 mm.

[0121] Figure 30-32 Depicted is a simulation of the localization function which is a truncated Gaussian function with a σ-value of 4 mm.

[0122] Fig.33 is a schematic diagram depicting virtual positioning with roll correction.

[0123] Fig.34 is a schematic diagram depicting virtual positioning with roll correction for BgRT.

[0124] Figures 35A-35C is a diagram depicting three different patient treatment plan variations.

[0125] Figures 36A-36B is a diagram depicting an example of a treatment plan.

[0126] Figures 37A-37N Depicted is a graphical user interface for multi-target hybrid localization.

[0127] Figures 38A-38E A graphical user interface for multi-target treatment volume definition is depicted. DETAILED DESCRIPTION

[0128] Disclosed herein are methods for treatment planning, patient setup, positioning, and radiation delivery for irradiating multiple patient target regions in a single treatment session or portion. The treatment planning method may include selecting a planning positioning reference point for each target region, and calculating a translation-invariant emission filter for each target region based on the selected planning positioning reference point. For irradiation of multiple target regions, a treatment planning system that performs the methods described herein may generate a set of translation-invariant emission filters associated with the planning positioning reference point for each patient target region. Optionally, the treatment planning system may generate a planning fluence map representing the radiation fluence across one or more patient target regions, one or more OARs, and / or healthy tissue. In some variants, the treatment planning system does not generate a set of radiotherapy machine instructions for execution by the radiotherapy system after patient setup and patient target region positioning, but the segmentation of the delivery fluence map may occur in "real time", for example, during a treatment session, within about 2 hours, within about 1 hour, within about 30 minutes, within about 10 minutes, within about 5 minutes, within about 1 minute, within about 30 seconds, within about 1 second, within about 0.5 seconds or less, etc. of calculating the delivery fluence map. By postponing the segmentation of machine instructions until the treatment session, the planned fluence map can be updated with the latest position data of the patient target area before the machine instructions are calculated (e.g., calculating the delivered fluence map). Moving fluence maps (e.g., linear movement, rigid movement) can be easily calculated, while "moving" machine instructions may result in nonlinear effects that affect the delivered dose. In addition, postponing the segmentation of machine instructions until at least after the patient target area is positioned allows "virtual positioning", in which the fluence map generated by the treatment planning system is adjusted according to the latest position data. In some variants, virtual positioning can include updating the planned fluence map by convolving a translation-invariant emission filter with a positioning function derived from the latest position data (e.g., the current position of the planned positioning reference point). By updating the positioning reference point during the treatment session and calculating the delivered fluence map based on (e.g.) a delta function centered at the positioning reference point and a set of translation-invariant emission filters for the target area, the planned fluence map can "follow" the patient target area instead of physically adjusting the patient position (e.g., using a patient platform) to match the planned fluence map. A segmented fluence map that best reflects the actual location of a patient target region can facilitate radiation delivery with better accuracy than delivering radiation based on a fluence map that has not been updated to reflect the actual location of the patient target region. A virtual positioning approach combined with a BgRT approach (using imaging data acquired during, such as positron annihilation emission path data, to further update the delivered fluence) may help improve the accuracy of dose delivery to multiple patient target regions. Using the virtual positioning approach described herein, a patient can be physically set up and positioned once (e.g., for one patient target region), but radiation can be applied to multiple virtually positioned patient target regions.

[0129] Radiation delivery to multiple patient target areas and / or irregularly shaped target areas presents challenges for positioning / registration and radiation delivery. For example, between the time the treatment planning images are acquired and the time the patient arrives for treatment, multiple tumors may have changed in different ways (e.g., position, shape, and / or size). Some tumors may grow while others may shrink; some tumors may move to the right while others move to the left, etc. The position of the tumors relative to healthy tissue or bone landmarks may change if the patient loses or gains weight (e.g., due to swelling). In addition, when multiple target areas are treated in a single treatment session or portion, the target areas treated in the later part of the treatment session may have moved from their positions in the earlier part of the treatment session (e.g., at the beginning of patient setup and positioning, during patient setup and positioning). The motion may be cyclical (e.g., due to breathing) or static (e.g., during continuous treatment of multiple target areas, the positioning of the last target to be treated is unlikely to be valid because the patient may have moved position at some point during delivery). Due to the highly coupled nature of dose delivery to the patient, there are additional levels of complexity in accounting for changes in the patient and / or target areas between planning and treatment, as well as changes that may occur during a treatment session. Radiation applied to one target area may produce scattered dose to other target areas, and in some cases, a radiation beam may intersect two target areas (or a target area and an OAR) and deliver dose directly to both areas. If these target areas move relative to each other, the treatment plan fluence map may no longer deliver the prescribed dose. Therefore, aligning an entire target area or a collection of target areas associated with one or more tumors with a radiotherapy system for an anticipated (i.e., future) radiation therapy session, such as when a care provider is attempting to locate one or more targets at the beginning of a treatment session, can be challenging and may result in inaccurate dose delivery.

[0130] The treatment planning, positioning, and radiation delivery methods described herein can help mitigate some of the dose delivery uncertainties associated with treating multiple patient target areas in a single treatment session. A variation of the method for delivering radiation to multiple patient target areas can include positioning (e.g., virtually positioning and / or physically positioning) each patient target area individually (e.g., independently of other patient target areas) to derive a delivery fluence map for each patient target area, and then delivering radiation to each patient target area according to the delivery fluence map corresponding to each patient target area. Positioning each patient target area can include (by a treatment planning system during treatment planning or a radiotherapy system at the beginning of a treatment session) dividing the planning fluence map into fluence map sub-areas for each target area along a low fluence zone, and deriving the delivery fluence map by moving the fluence map sub-areas, for example, by using a virtual positioning method that moves the planning fluence map. Alternatively or additionally, a method for delivering radiation to multiple patient target regions may include generating a planned fluence map for each individual patient target region, individually (e.g., independently of other patient target regions) positioning each patient target region to derive a delivered fluence map for each patient target region, combining the individual delivered fluence maps and confirming that the cumulative fluence map meets a specified dose target, and if the dose target (i.e., a specified target region minimum dose, not exceeding a maximum dose to an OAR, etc.) is met, then delivering radiation to each patient target region according to the delivery fluence map corresponding to each patient target region. A BgRT method for delivering radiation to multiple patient target regions may include designating one of the multiple patient target regions as a registration target region, defining a region of interest (ROI) (e.g., a biological emission zone (BFZ)) around the other patient target regions that is large enough to contain a series of positional shifts of those patient target regions, positioning the registration target region, and delivering radiation to each patient target region according to imaging data that is spatially co-located with the ROI of each patient target region. The ROI around the registration target region may be smaller than the ROIs around the other patient target regions.

[0131] Optionally, at one or more stages during treatment planning and / or radiation delivery, the system controller of the treatment planning system and / or radiotherapy system can generate and display one or more visualizations indicating the deposition of dose on the patient's anatomical structure. Additional changes to the radiation delivery can be included in response to the visualizations as desired by the clinician or technician. Providing visualizations depicting the dose distribution on the patient's anatomical structure, particularly as part of or after a positioning / registration procedure, can help the clinician or technician evaluate the interaction of the fluences calculated for each patient target area and determine whether these cumulative fluence levels are acceptable. For example, if the scattered dose from one target area to another is relatively low, or is spatially uniform, the effect of spatial variations between the planned fluence map and the delivered fluence map can be ignored. The visualizations can help the clinician or technician identify hot spots and / or cold spots and / or dose coupling effects (e.g., when the radiation beam intersects two or more target areas and / or OARs) that may be caused by radiation delivery to multiple target areas. Identifying these unwanted dose interactions prior to radiation delivery and providing spatial information about the dose distribution as feedback to the treatment planning and optimization process may help to further improve the planning fluence maps and / or emission filters.

[0132] Alternatively or additionally, the patient setup and target region positioning / registration method may include acquiring an image of one or more tumors during an image-guided positioning procedure that reflects current information about the location, size, and shape of the tumor before applying radiation. The user may compare the acquired image with the treatment planning image acquired and / or prepared before the procedure. The user and / or the radiotherapy system may then adjust the radiotherapy session based on the acquired image (i.e., perform setup corrections on the patient's positioning and orientation) so that the applied radiation can more effectively target the current shape, size, and location of the one or more tumors. For example, the user may define one or more treatment zones (also referred to herein as "zones" and / or "treatment domains") in an image of one or more tumors for image-guided positioning. Image matching or position corrections may then be defined for each treatment zone or region of interest. As the radiotherapy system makes progress in irradiating a target region (e.g., a tumor or a portion of a tumor) or multiple target regions, the radiotherapy system may automate the application of each position correction. The radiotherapy system may provide instructions to the user indicating position corrections or adjustment instructions corresponding to the position correction action to be performed by the user (e.g., moving the patient's arm or leg, or tilting and / or rotating the surface on which the patient is located). After making position corrections, the radiotherapy system can apply radiation to the real-time or updated position of the tumor or a portion of the tumor in each region of interest. In addition, by using the most effective positioning of the patient relative to the therapeutic radiation source for each region of interest, rather than keeping the patient in a position that allows higher quality conformal dose delivery to certain tumor regions at the expense of lower quality conformal dose delivery to other tumor regions, the tumor or tumor portion in each region of interest can be more accurately targeted. This may have the benefit of providing better treatment outcomes and overall consistency of treatment plans. In addition, since multiple targets can be treated during a single radiotherapy session, the duration of the radiotherapy session can be reduced. The shortened time can allow nursing institutions to treat more patients in one day. In addition, the reduced duration required to treat multiple tumors or multiple tumor portions also improves the patient experience.

[0133] A method for setting up a patient for radiation therapy may include acquiring images of a first patient target area and a second patient target area. A first set of patient position movement vectors may be calculated based on the acquired images and a treatment planning image of the first patient target area. A second set of patient position movement vectors may be calculated based on the acquired images, the treatment planning image of the second patient target area, and the first set of patient position movement vectors. The patient may be positioned to a first position based on the first set of patient position movement vectors. The patient may be moved to a second position and positioned based on the second set of patient position movement vectors.

[0134] It should be noted that the methods of patient setup, patient target area positioning / registration, and radiation delivery described herein for irradiating multiple patient target areas in a single treatment session can be used alone or in combination for intensity modulated radiation therapy (IMRT) and / or stereotactic body radiation therapy (SBRT) and / or BgRT. For example, a clinician may determine that all patient target areas are treated using IMRT / SBRT, or all patient target areas are treated using BgRT, or some patient target areas are treated using SBRT / IMRT and others are treated using BgRT. Some treatment planning systems and / or radiotherapy systems may have two operating modes, wherein the first mode is SBRT / IMRT planning and radiation delivery, and the second mode is BgRT planning and radiation delivery. As desired, a single treatment session may include radiation delivery using the SBRT / IMRT approach to some patient target areas and radiation delivery using the BgRT approach to other patient target areas.

[0135] Method Overview

[0136] Virtual Positioning

[0137] Virtual positioning of a patient target region includes modifying (e.g., moving) a planning fluence map of a particular patient target region to reflect the current / real-time position of the patient target region. The planning fluence map includes a set of radiation beamlets and beamlet intensities to be applied to the patient, and is calculated by the treatment planning system based on one or more planning images. Conceptually, this can be thought of as adjusting the fluence map as if the positioning image were the planning image. Compared to physical patient setup, where the position of the patient is physically adjusted by a patient platform so that the position of the patient target region at the time of treatment matches the position of the patient target region during treatment planning, virtual positioning may require very few (if any) patient platform adjustments. Physical patient setup typically includes acquiring a positioning image (e.g., a positioning CT image, an MRI image), comparing the positioning image to the planning image to calculate an offset representing a change in the position of the patient target region, and performing a patient platform adjustment and / or otherwise moving the patient based on the calculated offset so that the current position of the patient target region is aligned with its position in the planning image. In virtual positioning, instead of adjusting the patient platform, the planning fluence map is adjusted (e.g., moved or scrolled) by the calculated offset, i.e., conceptually similar to moving the planning image to align with the positioning image. Other fluence modifications may also be included to help ensure that the resulting dose distribution received by the patient is shifted to the appropriate location in the scout image without significant distortion, such as that caused by the fan-beam nature of the radiation beam and increasing the radiation fluence closer to the radiation source.

[0138] Virtual positioning methods aim to change the dose received by the patient by modifying the fluence map delivered by the therapeutic radiation source of the radiotherapy system after positioning and before or during treatment of the patient. This is accomplished by computing a translation-invariant representation of the treatment plan (e.g., a translation-invariant transmit filter) and selecting appropriate positioning reference points during treatment planning. The translation-invariant treatment plan (e.g., a translation-invariant transmit filter) can be applied to the actual reference point positions derived from the positioning image to change the dose received by the patient (and derive a delivered fluence map that can direct radiation to the current position of the patient's target region). An example of a translation-invariant treatment plan representation may include a set of transmit filters p for each transmit position i of each patient target region. i , where each emission filter is a 2D fluence map image in the source beam-eye-view coordinate system (i.e., for a case with three patient target regions and one hundred emission locations, the treatment plan would compute three sets of emission filters, each specifying 100 emission filters, one for each emission location). Emission filter p i The transmit filter p may be calculated based on a planned positioning reference point associated with the patient target region and in some variations may be selected by the user. i can be calculated by solving a set of filters when convolved with the 2-D projection of a discrete 3-D delta function δ centered at the planned positioning reference point in the 2-D beam-eye-view patient coordinate system for each shot position, resulting in a fluence f for each shot position i i

[0139] f i =p i ★δ i

[0140] in

[0141] δ i =proj i (δ)

[0142] Projection δ i may be a 2-D discrete delta function (i.e. an all-zero image except for a single pixel of value 1), so the operation p i ★δ i It may be the transmit filter p i The 2-D movement of can be considered as a position-independent fluence map. i It can be determined based on the dose constraints and goals specified by the clinician for each patient target region using standard radiotherapy dose optimization techniques, for example, techniques that minimize a cost function of the patient dose using a gradient descent method. Any such f i A desired planning reference point (e.g., a point in the center of the target region, including a point in the treatment volume of the target region) may be selected and a delta representing the movement to that reference point may be created.i , and apply the reverse shift to f i To obtain To decompose into convolution p i ★δ i The planning positioning reference point may be located within the tumor of the patient's target region (eg, the centroid or central portion of the tumor) or may be in an anatomical structure located external to the tumor (eg, a nearby bone structure).

[0143] The delta function δ centered at the positioning reference point may represent the location of the patient target region and may therefore be used to calculate a moving fluence map that directs radiation to the current location of the patient target region. Conceptually, the delta function δ may be thought of as encoding the location of the patient target region specified in 3-D coordinates. The delta function δ may include an all-zero 3-D image in which a single uniform voxel of infinitely narrow size is centered at the planning positioning reference point, but its projection δ on the emission location (e.g., the "beam-eye-view" of a treatment radiation source, or a multi-leaf collimator space) is i It may be defined by the width of each multi-leaf collimator (MLC) leaf and / or the beam station spacing (i.e., the spacing between discrete patient table positions where the table stops during therapeutic radiation delivery), and may contain one or more non-zero voxels. Projection δ i It can be a matrix (or image) whose dimensions match the number of MLC leaves and the number of patient platform beam stations in the MLC of the radiotherapy system. Fig.22A A schematic diagram of a delta function based on spatial voxels and their projections to emission positions is depicted in. Alternatively, the delta function δ may have a finite size that is set during treatment planning.

[0144] In some variations, virtual positioning may include convolving a set of filters with a positioning function, and the positioning function may include a delta function, a Gaussian function, and a truncated Gaussian function centered at a positioning reference point. Figure 24-26 Depicted are examples of localization functions that may be used in any of the virtually localized treatment planning and delivery methods described herein and their corresponding values ​​for a set of MLC leaf indices across multiple emission angles or positions. Fig.24 The values ​​of the delta function and dose distribution are depicted. Fig.25 The values ​​of the Gaussian function and dose distribution are plotted, and Fig.26 The truncated Gaussian function and the values ​​of the dose distribution are depicted. Figure 24-26In Figure 1, the X-axis corresponds to the MLC leaf index and the Y-axis is the value or amplitude of the localization function projection of the one-dimensional interpolation shift (e.g., interp1 shift, the left set of graphs) and the Fourier shift (the right set of graphs). Each line represents the localization function value for a different emission angle and / or position. For each dose map, the X-axis corresponds to the distance in millimeters, and the Y-axis corresponds to the fluence (e.g., dose). The peak-to-peak dose variation is measured from the highest peak in the family of curves to the lowest peak in the family of curves.

[0145] Fig.24 The values ​​or amplitudes of the localization delta function projections at four emission angles and / or positions and their corresponding dose (or fluence) distributions are depicted. The peak-to-peak dose variation for the one-dimensional interpolation shift is about 40%, and the peak-to-peak dose variation for the Fourier shift is about 7.5%. Fig.25 The values ​​or amplitudes of the localized Gaussian function projections at four emission angles and / or positions and their corresponding dose (or fluence) distributions are depicted, and Fig.26 The values ​​or amplitudes of the localized truncated Gaussian function projections at four emission angles and / or positions and their corresponding dose (or fluence) distributions are depicted. Fig.25 and 26 As shown, the Gaussian function and the truncated Gaussian function are relative to Fig.24 The delta function shown in can have better peak-to-peak characteristics. The peak-to-peak dose variation of the Gaussian function is 11% and 1.5%, and the peak-to-peak dose variation of the truncated Gaussian function is 14% and 2.1% (correspondingly for linear interpolation and Fourier shift). However, the Gaussian function and the truncated Gaussian function have wider curves than the delta function curve. The wider curve corresponds to more MLC leaves that must be opened to deliver the fluence. That is, for a specific emission angle or position, the values ​​of the positioning function span more MLC leaves for the Gaussian function or the truncated Gaussian function compared to the delta function. Fig.26 The truncated Gaussian function provides improved peak-to-peak characteristics over the delta function, with a narrower curve than the Gaussian function. Low peak-to-peak variation is desired so that moving the fluence does not result in significant dose differences. Treatment planning methods incorporating virtual positioning can include selecting a specific positioning function that provides a dose distribution that meets specified goals for each patient target area and / or OAR.

[0146] In addition to selecting a particular localization function during treatment planning, some variations of the treatment planning method may also include selecting parameters (e.g., characteristics, constants, etc.) of the localization function. For example, the treatment planning method may include selecting a truncated Gaussian function as the localization function and selecting a δ-value (e.g., width) of the truncated Gaussian function. The μ-value (e.g., mean or center) of the truncated Gaussian function may be a planned localization reference point. Localization functions with different σ-values ​​may result in delivered fluences with different conformal and / or distortion characteristics. For example, selecting a localization truncated Gaussian function with a lower σ-value may result in an offset dose or fluence with better conformality than a similar function with a higher σ-value. Figure 27-29 Depicted are simulated color intensity plots of the localization function, which is a truncated Gaussian function with a σ-value of 2 mm. Figure 30-32 Depicted is a simulation of the localization function, which is a truncated Gaussian function with a σ-value of 4 mm. Figure 27-32 The X-axis of the graph is the emission position / angle, and the Y-axis is the MLC leaf index. Fig. 27 and 30 The projection of the localization function onto each emission position of the 2 mm and 4 mm truncated Gaussian functions, respectively, is depicted. Fig.28 and 31 The emission filter values ​​for each emission position are depicted for 2 mm and 4 mm truncated Gaussian functions, respectively. Fig.29 and 32 The fluence values ​​for each firing position are depicted for 2 mm and 4 mm truncated Gaussian functions, respectively. Fig.30 Projection ratio of the central positioning function (σ-value is 4 mm) Fig. 27 The projection of the localization function in (σ-value of 2 mm) is wider. This may result in a fluence distribution of the localization function with a 4 mm σ-value ( Fig.32 ) than the 2mmσ-value localization function of the fluence distribution ( Fig.29 ). However, the fluence peak across multiple shot locations may be more uniform (less distorted) for the 4 mm σ-value localizer than for the 2 mm σ-value localizer (more distorted). These different fluence characteristics can be adjusted during treatment planning based on clinical and / or prescribed goals for each patient target region and / or OAR. For example, Figure 27-32 As depicted, a treatment planning system can balance the trade-off between fluence conformality and uniformity or distortion by iterating and evaluating different σ-values ​​of the localization function.

[0147] In some variants, the convolution of a three-dimensional image or a two-dimensional image with a positioning function (e.g., a delta function, a Gaussian function, a truncated Gaussian function) can be equivalently represented as an operation on the three-dimensional image or the two-dimensional image, and then moved by an interpolation operator. The movement with the delta function can be implemented as a linear, Fourier, or bicubic interpolation of a 2-D or 3-D image. The operation on the three-dimensional image or the two-dimensional image can be filtered by a Gaussian filter or a truncated Gaussian filter.

[0148] It should be understood that although the examples and variations of the methods described herein may refer to the use of a delta function, any of the above functions, such as a Gaussian function, a truncated Gaussian function, may alternatively be used.

[0149] Although the above-mentioned delta function can encode the position of the patient target area by the positioning reference point (that is, the delta function is a function of the 3-D coordinates of the positioning reference point), optionally, the virtual positioning method can include a second rotation transformation function that encodes the orientation of the patient target area. For example, the rotation function R can be a positioning function of the pitch, yaw and roll of the patient platform, which can represent the orientation of the patient target area in the patient. That is, the virtual positioning method can include two positioning functions: a first delta function representing the reference position of the patient target area and a second rotation transformation function representing the orientation of the patient target area. That is,

[0150]

[0151] Just as the translation can be projected to each emission angle, the fluence map rotation operation can also be projected to each emission angle. The 3-D rotation operation may become a 2-D affine transformation of the fluence map (i.e., the fluence map is rotated in 3-D and then projected to the same 2-D beam-eye-view space). The 3-D rotation operation to achieve pitch and yaw correction can be expressed as Below. A real-time delivered fluence map used by a radiotherapy system may be:

[0152] f i =R i (δ i ★p i )

[0153] For a ring gantry radiotherapy system, one example of roll correction can be implemented by adding a single offset to the gantry encoder position to roll the plan to the patient. For multiple targets, there may not be a single roll offset that can be implemented to individually roll each individual transmit filter. i An example of virtual roll correction implemented by a ring gantry system of N, where i is an index representing the transmit position around the gantry, is implemented by interpolating the filter across the transmit angles. fp Launch position and rotation angle An example of a radiotherapy system where the z-axis is negative and Then the new transmit filter p′ for each patient target area is i may be:

[0154]

[0155] The modulo function mod returns the launch position around the ring rack. If the rotation angle is positive relative to the z-axis, and but

[0156]

[0157] It is known that if Other interpolation algorithms may be used to rotate the filters to their new positions. In some variants, the interpolation algorithms may include one or more Fourier, bicubic, and spline based interpolation algorithms. The above method is an example of a method for implementing transmit filter rotation in projected space, where the p′ group at the transmit position angle θ can be rotated using an angle rolling function with a delta function. It can be described by a circular convolution where:

[0158]

[0159] By Angle After rotation, the new transmit filter p′ can be used to replace the previous filter p. This can be given an order of operations that matches the application of an offset to the gantry position encoder to achieve roll correction. The advantage of calculating a new set of filters in this way is that any fluences calculated can be added together. Fluences for all patient target regions can be summed since they are on the same rotated grid.

[0160] In some annular gantry radiotherapy systems, a patient target region that is not at the isocenter may experience a virtual rotation of the patient target region, a rotation of the reference frame, and a virtual shift in the fluence. Fig.33 Depicted is a virtual roll correction for the IMRT / SBRT treatment delivery system. Let δ be located at the virtual center of rotation of the patient's target region.

[0161]

[0162] The virtual roll correction may include: The entire reference system is rotated so that the patient target region can be rotated and moved based on the position of the patient target region, such as Fig.33 Depicted. Δx and Δy may correspond to the original position xy of the target and the rotation angle The difference between the new positions after the reference frame is rotated.

[0163]

[0164] Δr θ corresponds to the leaf offset at each therapeutic radiation source (e.g., linear accelerator) location to move the fluence to the center of the new location. For a fan-beam therapeutic radiation source, Δw may correspond to the spacing between leaves at the target and is based on the distance to the target, D t Divided by the distance D between the linear accelerator source and the system isocenter iso where θ corresponds to the angle between the launch positions around the ring gantry.

[0165] Δr θ ≈(Δx cosθ+Δy sinθ) / Δw

[0166]

[0167] In some variations, the leaf shift can be approximately related to the amount of Δx and Δy movement of the patient target region in the rotation plane of the radiotherapy system. Patient target regions farther from the source may have greater leaf movement. In some variations, Δr θ A more accurate solution can be obtained by computing the leaf offsets using a convolution operation.

[0168]

[0169] In this formula, the position of the patient target area can be projected into the fan beam projection space. The position of the patient target area δ LOC At its rotation angle After that, it can be projected into the fan beam projection space at a given transmit position i. This operation can shift the fluence by inverting the projection of the delta function and convolving it with the position of the patient target region. The inversion of the projected delta function can be implemented as a discrete representation of the transposed delta function. Alternatively, the inversion of the delta function can represent the negation of the shift of the delta function. This movement with rotation realizes a virtual rotation of the planned fluence around an arbitrary patient target region position.

[0170] where the positioning reference point is selected at the treatment session with 3-D coordinates (x, y, z), and the pitch, yaw, roll, and x-, y-, z-positions reflect the orientation of the patient platform / couch on which the patient is set (which may correspond to the predetermined orientation of the patient platform during treatment planning). Positioning the patient target region in position and orientation may shift the delivered fluence at the emission position i accordingly:

[0171] f delivery,i =δ delivery,i *p′ i

[0172] where δ delivery,i is δ delivery The projection on the emission position i, and p′ i is the projection of the transmit filter p' on the transmit position i.

[0173] Fig.34 A schematic diagram of a virtual roll correction for a BgRT treatment delivery system is depicted. For a virtual roll of a patient target area, the fluence at each shot position i can be a combination of the roll and the delivered fluence shift.

[0174]

[0175] δ′ delivery,i =δ delivery,i *δ i (Δr)

[0176] f dlivery,i =δ′ delivery,i *p′ i

[0177] Translation invariant transmit filter p i The treatment planning system calculates, based on the planned positioning reference points, a virtual positioning of the patient target area during treatment, and may include acquiring a positioning image of the patient in a treatment position (e.g., positioned or set on a patient platform), identifying the patient target area in the image, selecting a positioning reference point corresponding to the planned positioning reference point, and calculating the delta function δ based on the positioning reference point. local To calculate the delivered fluence f_delivery at each shot position i , and the delta function is combined with the translation-invariant emission filter p i convolution:

[0178] f_delivery i =p i ★δ_local i

[0179] in

[0180] δ_local i =proj i (δ local )

[0181] Convolving the transmit filter with a delta function centered at a positioning reference point has the effect of moving (e.g., shifting) the planned fluence map to reflect the current position of the patient target region. After calculating the delivered fluence, the radiotherapy system controller can then segment the delivered fluence into machine instructions (e.g., MLC configuration, therapeutic radiation source parameters, etc.), which can then be executed to deliver the prescribed fluence. Virtual positioning and machine instruction segmentation can occur during a treatment session, and preferably in real time. This is in contrast to other treatment planning and radiotherapy systems in which machine instructions are calculated during the treatment planning phase rather than during a treatment session, resulting in a set of machine instructions that deliver radiation to the location of the patient target region in the planning image rather than the current location of the patient target region. In the case of SBRT / IMRT radiation delivery, after virtual positioning and segmentation, the radiotherapy system can then continue to deliver the prescribed fluence to the patient target region by following the newly segmented machine instructions. In the case of BgRT radiation delivery, a region of interest or ROI (e.g., a biological emission zone or BFZ) may be adjusted (e.g., moved) using virtual positioning, and the delivery fluence map may not be segmented into machine instructions until after the delivery fluence map has been further updated using imaging data (e.g., positron annihilation emission path data) acquired during the treatment session. For example, approximately 500 ms prior to delivery of a therapeutic radiation beam, the radiotherapy system may update the delivery fluence using imaging data acquired in a 500 ms window and then segment the delivery fluence just prior to delivery. In the case where multiple patient target regions are to be irradiated in a single session, virtual positioning of each patient target region may be performed in a single batch at the beginning of the treatment session and / or sequentially throughout the treatment session (e.g., positioning a first patient target region, segmenting the delivery fluence into machine instructions, and irradiating the first patient target region, positioning a second patient target region, segmenting the delivery fluence into machine instructions, and irradiating the second patient target region, and so on).

[0182] Some localization methods may account for and compensate for one or more physical effects of moving the fluence map as it moves to reflect the current position of the patient target region. Examples include MLC leaf tongue and groove (T&G) effects, non-flat treatment beam effects, and treatment beam intensity falloff effects that are inversely proportional to the square of the distance from the treatment radiation source. Optionally, to calculate a delivered fluence map that accounts for one or more of these effects, the convolution of the localization function (e.g., a delta function, a Gaussian-type function) with the emission filter can be convolved with additional factors. To compensate for a non-flat treatment beam (i.e., beam intensity varies across the irradiation field in the IEC-X and IEC-Y directions, where the center portion of the field has greater beam intensity than the edges of the field), a virtual flat filter correction factor (FF) can be applied to each projection, where the virtual flat filter correction factor is a matrix that is the inverse of the beam intensity flatness distribution of the treatment radiation source beam along the MLC leaf dimensions:

[0183] (f i )=FF·(p i ★δ i )

[0184] The virtual flat filter correction factor (FF) matrix can be a two-dimensional matrix with the number of rows matching the number of MLC leaves and the number of columns matching the number of patient platform beam stations. Fig. 22B An example of a virtually flat filter correction factor (FF) for a radiotherapy system with 64 MLC leaves and 20 patient platform beam stations is depicted.

[0185] Calculating a delivered fluence map to compensate for the inverse square beam intensity drop with distance from the therapeutic radiation source may include applying a distance compensation scaling factor in the delivered fluence calculation

[0186]

[0187] where d i represents the distance from the emission position i to the center of the patient's target region (eg, the target region centroid) determined during treatment planning, and d′ i represents the distance from the emission position i to the center of the patient's target region (eg, the target region centroid) determined at the time of radiation delivery based on the scout image.

[0188] The delivered fluence map accounting for the non-flat treatment beam and the inverse square beam intensity reduction can be calculated as follows:

[0189]

[0190] The virtual positioning method described herein can be used to irradiate multiple patient target areas in a single treatment session or portion. The method for irradiating multiple patient target areas in a single treatment session may include defining a patient area or treatment zone for each patient target area (e.g., defined by a treatment planning system, with or without user input), selecting a positioning reference point for virtual positioning for each patient treatment zone according to the steps described herein, and then emitting a therapeutic radiation beam according to a delivery fluence map calculated for each patient treatment zone by virtual positioning. The patient treatment zone may include a patient area irradiated for a single physical setup and positioning. For example, the treatment zone may be a patient area irradiated for a specific patient position on a platform (e.g., a position along the platform, a patient position such as an arm position, etc.) and a set of platform positions in IEC-Y. The physical setup and positioning may include a unique laser alignment of the patient and / or acquisition of a positioning image (e.g., CT or MRI or PET image), a patient position (e.g., arm raised, arm lowered, abdominal compression, breath holding, etc.), and / or one or more patient platform adjustments so that the patient position matches the position during the treatment plan. The patient treatment zone may span the patient area irradiated for a specific physical setup and positioning. Each treatment zone may have its own physical setup and positioning. In some variants, the patient treatment area can be represented by a set of patient platform positions across the irradiated area of ​​the patient in IEC-Y. For example, the acquired image and / or treatment planning image can be divided into a first treatment area and a second treatment area. Each treatment area may include one or more patient target areas, so that one or more patient target areas in the acquired image can be compared with one or more corresponding patient target areas in the treatment planning image. Each treatment area can correspond to a portion of the patient, one or more patient target areas are located within the portion, and the portion will be irradiated when the patient is positioned according to a specific setting during a specific portion of the radiation treatment period. The treatment area can be mapped to a series of patient platform positions or stages (e.g., beam stations) and / or a series of patient platforms along its longitudinal axis. Movement, where one or more target areas in the treatment area intersect with the radiation beam of the therapeutic radiation source. The treatment area can correspond to a specific patient position and / or platform orientation. For example, a first treatment area can be associated with a first patient position and orientation for irradiating a first patient target area within the first treatment area, and a second treatment area can be associated with a second patient position and orientation for irradiating a second patient target area within the second treatment area. Thus, in some embodiments, a first treatment zone can be associated with a first portion of a radiation treatment session (e.g., moving the patient platform via a first set of beam stations), a first patient target area, and a first position of the patient, and a second treatment zone can be associated with a second portion of a radiation treatment session (e.g., moving the patient platform via a second set of beam stations), a second patient target area, and a second position of the patient.

[0191] Optionally, the central regions of the defined patient treatment volumes can be aligned with each other (e.g., along "isolines") so that no adjustment of the patient position is required between emitting therapeutic radiation for each patient treatment volume (other than longitudinal IEC-Y movement toward each patient platform beam station so that IEC-X and IEC-Z are fixed). This can help reduce the incidence of users entering treatment bunkers during treatment sessions, which can significantly increase the total treatment time. For example, the center of a first treatment volume and the center of a second treatment volume can be colinear along the IEC-Y axis and / or coplanar with the IEC-Y axis. In some variations, the first treatment volume and the second treatment volume can overlap, while in other variations, the treatment volumes may not overlap. The center of mass can be along IEC-X in the same plane (e.g., along "isolines"). The center of the treatment volume is not necessarily the center of the target.

[0192] The positioning reference point of each patient target area (or patient target area group) can be different from the central area or point of the treatment area. In some variations, the treatment area (e.g., the planned patient treatment area) defined during treatment planning can be selected based on certain clinical criteria. For example, target areas in different axial planes can be divided into different planned patient treatment areas, and / or target areas separated from another target area by more than about 5-10 cm can be divided into different planned patient treatment areas. During treatment planning, a set of translation-invariant emission filters for each patient target area and / or patient target area group that share a positioning reference point can be calculated using the methods described herein, so that if necessary, the virtual positioning of the patient target area can be performed separately during the treatment period. The emission of the therapeutic radiation beam according to the delivery fluence map of each planned patient target area can be performed sequentially, and in some variations, a separate, physical patient setup (e.g., by adjusting the orientation of the patient platform) can be included before the radiation is delivered to the patient target area in the next patient treatment area. Alternatively or additionally, the delivered fluence maps for each patient target region can be delivered in parallel, e.g., segmented together and delivered without any physical patient setup between target regions (other than stepping the patient platform through discrete beam station positions along the longitudinal axis, i.e., IEC-Y). For treatment sessions in which one or more patient target regions will receive BgRT radiation delivery and these BgRT patient target regions have been positioned using virtual positioning, virtual movement is applied to the ROI. A treatment planning method incorporating virtual positioning of one or more BgRT targets can include selecting planning positioning reference points for the BgRT patient target regions, defining a region of interest (ROI) (e.g., a biological emission zone (BFZ)) around the patient target regions, and computing a translationally invariant emission filter (e.g., a radiation excitation matrix (RFM) or a radiation emission filter) based on the ROI and a planning guidance image (e.g., a planning PET image, an MRI image, etc.) that includes the patient target regions. i. The ROI can be a spatial mask or filter that defines a patient area or region, which can include a patient target region and an edge around the patient target region. For example, the ROI can include a tumor region (or any patient target region), and the edge around the tumor region can take into account the position estimation error of the tumor region, and / or the movement of the tumor region, and / or the possible position of the tumor region during emission delivery, and / or the geometric change of the tumor region. During the treatment period, the radiotherapy system can acquire imaging data (e.g., positron annihilation emission path data or LOR data (in the case where the patient has been injected with a PET tracer), SPECT data (in the case where the patient has been injected with a SPECT tracer), gamma radiation data, MRI data, CT data, and / or X-ray data) that intersects and / or is co-located with the ROI of the BgRT target region. Imaging data that does not intersect the ROI or contains data related to structures located outside the ROI is not included in the calculation of the delivery fluence map. In this way, the ROI is used as a spatial mask or filter that can be applied to imaging data acquired during the treatment period.

[0193] A radiation delivery method combining virtual positioning and BgRT delivery may include acquiring an image of a patient at a treatment position including a BgRT patient target region and an ROI, selecting a positioning reference point within the acquired image, adjusting the ROI by calculating a delta function based on the positioning reference point and convolving the delta function with the ROI, calculating a fluence for delivery to the patient target region at each emission position of a therapeutic radiation source by convolving imaging data with an emission filter, and continuing to emit the delivery fluence:

[0194] (f i )=(p i ★project i (x·(ROI★δ i,delivery )))

[0195] where x is the acquired additional imaging data (e.g., partial imaging data, time-limited acquired imaging data, positron annihilation emission path data, MRI data, SPECT data, gamma data, CT data, and / or X-ray data), and p i is the emission filter (also called the BgRT emission filter or the radiation excitation matrix) that is the opposite of the filter used by virtual localization. In this case, virtual localization shifts the ROI by δ delivery The additionally acquired imaging data may be spatially filtered (or masked) by the ROI so that only imaging data co-localized with the adjusted ROI may be used to calculate the delivered fluence.

[0196] For BGRT, when roll correction is optionally applied at any time, the filter p iRotation, the ROI can be rotated by the same number of degrees. An example is to implement a 2-D rotation function that rotates the ROI mask in place along Z for each plane. The order of operations can be important when implementing roll correction, and in this example, roll correction is applied first, followed by translation by a virtual offset:

[0197]

[0198] Now rotate the emission filter to match the new reference frame:

[0199]

[0200] The fluence f at a given launch position i Now is the projection of the imaging data, masked by the rotated and shifted ROI, and virtually offset by δ delivery Move, project to a given emission angle i and compare with a set of rotation filters p′ i convolution:

[0201] (f i )=(p′ i *proj i (x·(ROI′*δ delivery )))

[0202] ROI′=δ(Δx,Δy)*rot(ROI,θ roll )

[0203] (f i )=(p i ★project i (x·(ROI′★δ delivery )))

[0204] Optionally, a delivered fluence map that takes into account the non-flat treatment beam and the inverse square beam intensity reduction in the BgRT target area can be calculated as follows:

[0205]

[0206] As needed, therapeutic radiation may be delivered to BgRT targets and / or SBRT / IMRT targets sequentially and / or concurrently in a single session.

[0207] Optionally, during treatment planning after the translation-invariant transmit filter has been calculated, a bounded dose volume histogram curve (bDVH) showing minimum and maximum dose values ​​over the patient target region volume can be calculated, taking into account possible dose variations due to patient target region movement. Outputting a visualization graphic such as a bDVH or any visualization graphic described herein during treatment planning and / or during patient setup and / or target region positioning can help a user evaluate whether the treatment plan is appropriate for the patient (e.g., on the day of treatment).

[0208] After multi-target virtual localization, each patient target region may have dose components coupled between different patient treatment volumes. This dose coupling may be a result of the possibility of additional fluence beams interacting with multiple patient target regions. Once a set of virtual localizations is known, doses to patient target regions, OARs, and / or treatment volumes may be calculated. A set of normalization coefficients may be applied to each patient target region and / or treatment volume to ensure that certain dosimetry goals are met, or alternatively, certain OAR doses are constrained. An example of implementing these coefficients for each IMRT / SBRT virtual multi-localization j from a set of N localizations may be to solve for the coefficient β for each localization j to normalize the joint effect of all virtual localizations (e.g., all virtual localizations in the entire treatment plan, all virtual localizations in each treatment volume). One such example of a joint solution is to minimize the mean square sum of dosimetry scalars associated with each patient target region and / or treatment volume. j . is the dosimetry scalar calculated when planning target region j.

[0209] For IMRT / SBRT:

[0210]

[0211] For BgRT:

[0212]

[0213] Dosimetry Scalar D j It can be any of the following: mean dose to PTV, percentile dose to PTV, maximum dose to PTV. Alternatively, this dosimetric scalar D j It may be based on a function of the OAR dose relative to the target region.Other convex minimization algorithms may be used instead of the mean square error, such as weighted least squares.

[0214] While some of the virtual positioning methods described above and herein use a delta function derived from a positioning reference point and convolve the delta function with a translation-invariant transmit filter, it should be understood that the virtual positioning methods include other positioning functions that encode the orientation of the patient target region based on the pitch, yaw, and roll of the patient platform or bed. For example, the virtual positioning methods described herein may include convolving a set of filters with a positioning function on a positioning reference point that may be selected during a treatment session, the positioning function including a delta function, a Gaussian function, and a truncated Gaussian function.

[0215] Mosaic multi-target positioning

[0216] As briefly described above, one of the challenges of treating multiple patient target regions in a single treatment session is that the positioning / registration that is suitable for one patient target region may not be suitable for other patient target regions. Methods for positioning / registration of multiple patient target regions may include positioning / registering each one separately (e.g., using a virtual positioning method in which the planning fluence map moves and / or using a physical positioning method that uses a platform to move the patient). For example, a treatment session may include one physical positioning / registration for a patient target region and one or more virtual positioning for other patient target regions. Through virtual positioning, multiple patient target regions can be irradiated without physically moving and / or changing the patient's position to position each target region. In a variant in which a treatment plan can be calculated and optimized for all patient target regions, i.e., a single treatment plan that specifies a 3-D fluence for each patient target region, a "global" treatment plan (e.g., a "global" fluence map) can be divided into discrete sub-regions. Based on a single positioning image, the targets in each sub-region can be independently positioned or registered in a multi-target treatment plan. Typically, a treatment plan fluence map can include a high fluence region located on (e.g., co-located with) a target region and a low fluence region almost anywhere else. These low fluence areas may be referred to as low fluence bands or boundary areas. A method for treatment planning may include generating a global treatment plan or global fluence map having a high fluence area co-located with a target area surrounded or bounded by the low fluence area or low fluence band, and may further include dividing the global treatment plan or fluence map into sub-areas surrounded or bounded by the low fluence area. Conceptually, the global treatment plan can be "cut" along the center of these low fluence bands and divided into discrete areas around each target area. These treatment plan fluence map sub-areas or "mosaics" can be independently moved and oriented around each target using a positioning image at the beginning of a treatment session. While the movement of the plan fluence map sub-areas may result in fluence overlap of the low fluence boundary areas of adjacent sub-areas (i.e., the boundary area may receive a fluence during irradiation of the target area of ​​two or more adjacent sub-areas), the low fluence levels in these boundary areas may be specified during treatment planning as being low enough so that the fluence overlap is not a clinical concern. During treatment planning, the low fluence boundary areas may be defined as being wide enough so that the amount of overlap that can be accommodated is large enough so that all positioning / registration error sources can be addressed. In some variations, adjustment structures and / or constraints may be added during treatment planning to obtain desired low fluence bounded regions. After locating individual patient target regions in independent fluence map subregions, the delivery fluence map for each subregion may be segmented into machine instructions for execution by the radiotherapy system. Radiation may be delivered to multiple local patient target regions or fluence map subregions sequentially and / or simultaneously. For example, some patient target regions or fluence map subregions may be irradiated sequentially, while other patient target regions or fluence map subregions may be irradiated simultaneously with other patient target regions or fluence map subregions.A single scout image including all patient target regions may be used to locate / register each patient target region or multiple scout images (e.g., one scout image per patient target region or fluence map sub-region). For example, during a treatment session, there may be one physical scout per treatment volume (as defined during planning), and there may be one or more virtual scouts for one or more patient target regions within the treatment volume. The mosaic scout method may be used for SBRT / IMRT delivery and / or BgRT delivery, and optionally in combination with other scout methods and patient setup methods (e.g., in combination with a moving patient platform, a virtual scout method, a rigid body multiple scout method where a "best fit" move is applied to the patient via the platform based on the scout image).

[0217] Hybrid mosaic multi-target localization

[0218] Optionally, when the global planning fluence map is divided into planning fluence map sub-regions, during treatment planning for mosaic localization, the method can include specifying whether to treat a patient target region in each fluence map sub-region using an SBRT / IMRT approach (e.g., designated as an SBRT / IMRT target region) or a BgRT approach (e.g., designated as a BgRT target region). A translationally invariant transmit filter can be calculated based on a planning localization reference point selected for all target regions, as described herein for virtual localization. Optionally, a bDVH curve can be calculated for each patient target region, which can include generating a series of simulations of all potential movements of a BgRT target region and / or a SBRT / IMRT target region. The bDVH curve can be reviewed and approved by a clinician at the time of planning. A method for hybrid mosaic multi-target localization can include acquiring a large volume CT (e.g., a single large volume CT) of multiple SBRT and BgRT target regions, delineating a set of patient platform adjustments (e.g., 6DOF corrections) for each patient target region based on a CT localization image, and selecting localization reference points for each patient target region. To locate / register a specific patient target region, the patient platform can first be moved according to the depicted patient platform adjustment group, and a delivery fluence map can be calculated using a virtual positioning technique applied to the selected positioning reference points of the patient target region. For BgRT delivery, a PET pre-scan can be acquired in conjunction with acquiring a positioning image. Based on the PET pre-scan, a predicted dose to the BgRT target can be calculated just before activating the therapeutic radiation source to irradiate the BgRT target region, which may help ensure that the actual positioning and PET pre-scan images are within the pre-approved dose limits. Real-time delivery fluence maps for BgRT and SBRT / IMRT target regions can be smoothly combined and segmented into machine instructions on the fly (i.e., minutes or seconds before delivery). In beam station delivery, where the patient platform remains stationary in a longitudinal position and the therapeutic radiation source moves around the patient to deliver the calculated fluence, the delivery fluence maps for the BgRT and SBRT / IMRT target regions at a specific beam station can be added together and segmented into machine instructions together when the platform is parked at the beam station. In this way, delivery fluences for multiple BgRT and SBRT / IMRT target regions can be delivered simultaneously.

[0219] Decoupled multi-target localization

[0220] A method for treating multiple patient target regions in a single treatment session may include calculating an individual treatment plan for each patient target region (i.e., an individual plan fluence map specifying a 3-D fluence for the individual patient target region), rather than calculating a global treatment plan (i.e., a global fluence map specifying a 3-D fluence for each patient target region). In some variations, a method for decoupled localization of treatment planning may include calculating an individual treatment plan for each target region without regard to the presence of other target regions, but taking into account the presence and location of OARs and / or other critical structures, combining the individual treatment plans together to form a combined treatment plan, while still maintaining the individual plans as separate entities, constraining the combined plan to not allow high fluence regions in the individual plans to overlap with other high fluence regions, and also meeting the original goals of dose coverage, dose constraints for OARs, etc. Constraining the combined treatment plan may create a planned global fluence map having a low fluence region or band around each patient target region so that the treatment plan can accommodate some independent target region motion. In some variations, adjustment structures and / or constraints may be added during treatment planning to obtain a desired low fluence bounding region. The combined treatment plan (ie, the planned global fluence map) may be reviewed and approved by a clinician prior to treatment.

[0221] An example of a treatment planning method for decoupled multi-target positioning may include generating a treatment plan for irradiating a first patient target in a first treatment volume and a second patient target region in a second treatment volume, dividing the treatment plan into a first treatment plan for irradiating the first patient target region in the first treatment volume at a first prescribed dose while limiting irradiation of OARs to less than a first dose amount and a second treatment plan for irradiating the second patient target region in the second treatment volume at a second prescribed dose while limiting irradiation of OARs to less than a second dose amount, combining the first and second treatment plans to generate a combined treatment plan, and iteratively modifying the combined treatment plan to meet desired dose objectives and constraints. Examples of dose objectives and constraints may include preventing hot spots or cold spots in the combined treatment plan. The first treatment plan may include an optimized radiation beam delivering a first prescribed dose to the first patient target region, and the second treatment plan may include an optimized radiation beam delivering a second prescribed dose to the second patient target region. The dose amount or level to the OAR as a result of the individual (e.g., first and second) treatment plans may be set to a certain proportion of the maximum dose amount. For example, a first dose amount to an OAR (e.g., an OAR located between or spanning the first and second treatment zones) from a first treatment plan may be 35% of a maximum dose level, and a second dose amount to an OAR from a second treatment plan may be 65% of the maximum dose level. The specific contribution values ​​of the first and second treatment plans to the OAR dose may be dynamically set based on an iterative calculation within a joint optimization or through a series of separate optimizations at different contribution levels based on a goal evaluation in the combined treatment plan until an acceptable plan is reached. After the combined treatment plan is modified to meet the desired dose goals and constraints, it may be divided into a first and a second treatment plan, but with an optimized beam and / or fluence for delivery. In some instances, the combined treatment plan may include a planned fluence map, and the first treatment plan may include a first fluence map and the second treatment plan may include a second fluence map, wherein the first fluence map and the second fluence map are combined to form the planned fluence map.

[0222] Optionally, in some variations, a user may select one patient target region as a higher priority than another. For example, if a user defines irradiation of a first patient target region as a higher priority than irradiation of a second patient target region, the treatment planning method may include dividing the treatment plan into a first treatment plan for irradiating the first patient target region in a first treatment volume at a first prescribed dose and a second treatment plan for irradiating the second patient target region in a second treatment volume at a second prescribed dose, while limiting irradiation of OARs to less than a selected dose amount, combining the first and second treatment plans to generate a combined treatment plan, and iteratively modifying the combined treatment plan to meet the desired dose goals and constraints. In the method, the first treatment plan may have fewer dose constraints (e.g., no OAR dose constraints) than the second treatment plan, such that the first treatment plan includes a beam optimized for delivering a prescribed dose to the first patient target region, with little or no consideration of the dose of the OARs. The second treatment plan may then consider the dose delivered by the first treatment plan as a "previous dose" that constrains its beam optimization to deliver a dose to the second patient target region.

[0223] During the treatment period, individual patient target areas can be individually positioned using one or more positioning images (e.g., by adjusting the patient platform or changing the radiotherapy machine instructions using typical positioning methods, and / or using the virtual positioning methods described herein). After all patient target areas are positioned, the delivery fluence maps for each patient can be combined together to confirm whether any "overlapping" dose areas exceed any constraints. If the required dose constraints are met, the radiotherapy system can segment the delivery fluence map into machine instructions and continue to deliver therapeutic radiation to the patient target area. Delaying the segmentation or translation of the delivery energy map into radiotherapy system instructions so that the segmentation occurs as close to delivery as possible allows the radiotherapy system to update the delivery fluence to reflect the actual location (and / or any changes in location) of the patient target area, resulting in more accurate delivery of the total prescribed dose.

[0224] Biologically guided radiotherapy (BgRT) positioning

[0225] As briefly described, BgRT is a radiation delivery method that uses imaging data acquired during a treatment session to update the delivered fluence and emits therapeutic radiation within minutes or seconds of acquiring the imaging data. Due to the low latency nature of BgRT, the imaging data used to update the delivered fluence may be relatively sparse (e.g., "partial image data" collected within a short or limited time window is insufficient for complete image reconstruction) and / or noisy (e.g., having a signal-to-noise ratio that does not allow for reliable determination of the centroid of the patient's target region). For example, in BgRT, the imaging data used to update or calculate the delivered fluence map may include a partial PET image containing one or more lines of response (LORs), a partial MRI image containing subsampling in k-space, and / or one or more X-ray projection images. Although the examples herein are described in the context of a PET imaging modality, it should be understood that any other imaging modality may be used alone or in combination with a PET imaging modality. Imaging data may be acquired within a limited time window, which may be, for example, about 3 seconds or less, about 2 seconds or less, about 1 second or less, about 500 ms or less, about 300 ms or less, about 200 ms or less, and the like. Due to the low latency between image acquisition and radiation delivery (e.g., about 10 seconds or less, about 5 seconds or less, about 3 seconds or less, about 1 second or less, about 500 ms or less), radiation may be delivered to the target region before the target region moves. A ROI (e.g., a bio-emission region or bio-target region) may be defined around each BgRT target region, which represents a volume used to determine what LOR to use to direct the fluence at the target. That is, the ROI may be a spatial filter or mask that may be applied to the LOR; if a detected LOR intersects the ROI, it is used in the BgRT delivery algorithm to update the delivered fluence, otherwise it will be ignored. A smaller ROI may be preferred because it may reduce the chance of including PET-hungry tissue that is not a target in the ROI (any PET-hungry tissue in the ROI will be treated as if it were a target).

[0226] Methods for BgRT-based multi-target positioning may include designating one of the BgRT target regions as a registration target region and defining a sufficiently large ROI around the other to encompass the range of positional movement of those patient target regions. In some variations, the ROI of the registration target region may be smaller than the ROIs of the other BgRT target regions. In some variations, the registration target region may be the BgRT target region that is closest to a critical structure or OAR (e.g., a PET-hungry OAR such as the heart). During a treatment session, as long as the ROI of the registration target region is positioned / registered and the other BgRT target regions are within their ROIs (which may be larger or enlarged to account for expected changes in spatial positioning relative to the registration target region), the radiotherapy system may deliver radiation using the BgRT method (i.e., calculating the delivered fluence by convolving the acquired spatially filtered imaging data with a translationally invariant radiation excitation matrix or emission filter, which is then segmented into machine instructions for immediate execution). The effect of a larger ROI on dose conformality may be calculated and reviewed at the time of treatment planning, and may be shaped or designed to help reduce the likelihood of including additional PET-hungry tissues while helping to increase the likelihood that spatial differences between planning and delivery can be accommodated. BgRT-based positioning can optionally be used in combination with other positioning methods and patient setup methods (e.g., in combination with a mobile patient platform, virtual positioning methods, rigid body multi-positioning methods, where "best fit" movements are applied to the patient by the platform based on the positioning images).

[0227] Any of the multi-target positioning and radiation delivery methods described herein can be used alone or in combination with positioning and delivery methods commonly used for single patient target irradiation and / or irradiation of multiple target areas in multiple treatment sessions. For example, any of the planning, positioning and delivery methods described herein can be used in combination with physical patient settings (e.g., one physical patient setting per patient target area or treatment zone in a continuous manner), rigid multi-positioning, treatment plan deformation, robust treatment plans (treatment plans that consider position uncertainty during the optimization process and create plans that do not change strongly with position changes), and / or online treatment plan adaptation (generating new treatment plans based on positioning images). In continuous registration and treatment, each patient target area is independently positioned and treated, one after another. Immediate treatment after positioning may help reduce the possibility of static patient movement during treatment, however, it may be necessary to obtain multiple positioning images (e.g., multiple kVCT images) for each positioning instance. Treatment plans for continuous registration and treatment may include jointly optimizing fluence maps across multiple patient target areas and / or may be optimized to be robust to individual movement of each tumor when positioned separately. Rigid body multi-localization can include acquiring a localization image and then calculating a single movement of the localization image relative to the planning image that minimizes a function of the total registration error across all target regions and / or OARs (i.e., performing a "rigid body" registration). The margins around each target region in the original treatment plan may be enlarged to account for these expected registration errors. The targets and OARs in the treatment plan can be moved and oriented as a rigid body to find the "best" mapping to the actual locations of the targets and OARs in the localization image. The user can choose to consider all registration errors equally weighted and minimize the total registration "error amount", or alternatively, they can choose to weight certain target regions or OARs as more important than others and seek to better align those targets at the expense of larger registration errors or increased tumor margins elsewhere.

[0228] For example, mosaic multi-target localization and BgRT-based localization can be combined with one or more of the above methods. It is expected that some targets in a multi-target treatment plan may move more like a rigid body (e.g., target regions associated with the same bone) and therefore can be grouped together and registered using a rigid body method, while other patient target regions can be registered using mosaic multi-target or BgRT-based localization. Robustness algorithms can be used during treatment planning to help ensure that spatial adjustments made to each treatment plan or fluence map sub-region introduce a minimal amount of dose variation. Robust planning can also be used in conjunction with BgRT-based virtual localization to optimize the shape and position of the ROI for each patient target region. It may also be desirable to register patient target regions using mosaic multi-target or BgRT-based localization techniques and then apply soft tissue deformation methods to each sub-region or target region. This may help reduce the amount of tissue deformation that must be considered, thereby helping to reduce the dose variation introduced by the soft tissue method. Alternatively or additionally, a mosaic multi-target localization method can be used to reduce the computational burden of online treatment plan adaptation. For example, the mosaic multi-target localization method can be used to register patient target regions based on the planning fluence map, and then the fluence map of each patient target region can be adjusted individually. In another example, the BgRT treatment plan can combine treatment planning steps from the mosaic multi-target localization method, which can help reduce the size of the ROI of each target region.

[0229] In another variation, a treatment plan for multiple patient target areas may include multiple treatment zones, wherein the patient may be physically set / positioned for each treatment zone. Each treatment zone may have one or more tumors or patient target areas (e.g., ROIs). During a treatment session, the patient may be physically set / positioned for a first treatment zone, and the radiotherapy system may virtually position each patient target area within the first treatment zone. For example, physical positioning may provide appropriate positioning for a first patient target area in a first treatment zone, and then the radiotherapy system may adjust the fluence of other patient target areas in the treatment zone using the virtual positioning method described herein. The delivered fluence may be calculated or adjusted based on a positioning reference point selected from a positioning image during the treatment session. Irradiation of the patient target area in the first treatment zone may be performed continuously and / or in parallel. After the first treatment zone has been irradiated, the patient may then be physically set / positioned for a second treatment zone (e.g., moving a patient platform along an IEC-Y), and the radiotherapy system may virtually position each patient target area within the second treatment zone. The patient target area in the second treatment zone may be irradiated as described above for the first treatment zone. The first and second treatment zones may overlap in some variations and may not overlap in other variations.

[0230] The method for multi-target treatment planning, positioning and radiation delivery may optionally include generating one or more visualization graphics that can be output to a display device (e.g., a monitor). The visualization graphics may include a dose volume histogram (DVH) or a bounded dose volume histogram (bDVH) for each of a plurality of patient target regions, so that a user can be informed that a dose can be delivered to the patient target region. However, the DVH and bDVH curves do not provide information about the spatial interaction between the fluence maps of different target regions. For example, when the fluence map is moved and / or updated during positioning, fluence regions that were previously not overlapped during treatment planning may overlap during the treatment period. In mosaic positioning, the fluence map sub-regions can be positioned and moved separately, and in decoupled positioning, the individual fluence maps of different patient target regions can also be positioned and moved separately. Some overlapping regions may include low fluence regions of two or more individual fluence maps or fluence map sub-regions, so the cumulative fluence in the overlapping region may not exceed the dose safety threshold of non-target tissues, but, in some cases, such fluence overlap may exceed the dose safety threshold and / or may be co-located on OARs. Visual graphics can be generated based on the positioning data (e.g., a moving fluence map or fluence map sub-region, positioning reference points, positioning images, etc.) and output to a display device to help the user evaluate the dose impact of individual positioning of multiple patient target regions, and / or help identify any unwanted dosimetric effects caused by movement of these positioning fluence maps. The visual graphics can help the user better understand the interactions between targets and encode spatial information to evaluate the uncertainty of dose delivery.

[0231] Some visualization graphs can be calculated based on the bDVH curve and calculations, and can refer to the limits of the bDVH curve: nominal dose (D n ), the minimum possible dose (D pmin ) and the possible maximum dose (D pmax ). Visual graphics can depict representations of the probability of certain dose distributions and levels on certain anatomical structures in 2-D slices and / or 3-D renderings. Movies or short animations can also depict minimum, nominal, and maximum dose levels so that visual comparisons can be made between these levels. Differences or fluctuations from the nominal dose (e.g., delta dose) can provide the user with a visual tool to identify hot and cold spots.

[0232] Multi-target treatment planning method

[0233] If desired, a treatment planning method for treating multiple patient target regions in a single treatment session may include calculating various fluence maps (e.g., a global fluence map for all patient target regions and / or OARs, a fluence map sub-region including a subset of target regions and / or OARs), emission filters (e.g., a translation-invariant emission filter), spatial filters (e.g., spatial filtering for imaging data, regions of interest or ROIs, biological emission zones or BFZs, biological target zones). A treatment planning method for treating multiple patient target regions in a single treatment session may include calculating one or more translation-invariant emission filters for each patient target region for virtual positioning, and / or calculating a fluence map sub-region divided by low fluence bands for mosaic multi-target positioning, and / or generating a separate treatment plan or fluence map for each patient target region, and constraining the cumulative fluence map for decoupled multi-target positioning. A BgRT treatment planning method for treating one or more BgRT patient target regions (alone or in combination with one or more SBRT / IMRT patient target regions) may include designating one BgRT patient target region as a registration target region and defining an ROI for another BgRT patient target region to accommodate motion of the registration target region and motion of other target regions. A treatment planning method for treating SBRT / IMRT and BgRT patient target regions (e.g., hybrid mosaic multi-target positioning) may further include designating whether a patient target region is a BgRT target region or a SBRT / IMRT target region.

[0234] The treatment planning methods described herein can be used alone or in combination to develop a multi-target treatment plan suitable for a particular patient. Some clinicians or clinics can configure their treatment planning systems to calculate treatment planning parameters that can accommodate virtual positioning and mosaic multi-target positioning of multiple patient target areas with continuous or parallel radiation delivery to the patient target areas. Alternatively or additionally, the treatment planning system can be configured to calculate treatment planning parameters that can accommodate virtual positioning and decoupled multi-target positioning of multiple patient target areas with continuous or parallel radiation delivery to the patient target areas. For example, some treatment planning systems can be configured to calculate translation-invariant emission filters for all patient target areas, calculate emission filters for any BgRT patient target areas, and / or divide the treatment plan or planning fluence map based on the relative position of the patient target area and / or OAR and / or low fluence area of ​​the planning fluence map. . The BgRT patient target area can be irradiated during a first treatment period, and the SBRT / IMRT patient target area can be irradiated during a second treatment period (i.e., on a different day from the first treatment period, where the first and second treatment periods do not overlap in time, occur at different time intervals on the same day, etc.). Alternatively, the BgRT patient target area and the SBRT / IMRT patient target area can be irradiated sequentially during the same treatment session. For example, the BgRT patient target area can be irradiated during a first shuttle pass, and the SBRT / IMRT patient target area can be irradiated during a second shuttle pass.

[0235] Figure 1A and 1B Flowchart representations of respective SBRT and BgRT variants of a treatment planning method using virtual positioning to locate a single patient target region or multiple patient target regions during a treatment session. Figure 1AA variation of a treatment planning method incorporating virtual localization of SBRT / IMRT patient target regions is depicted. The method (120) may include acquiring (122) one or more treatment planning images of one or more patient target regions, defining (124) contours of one or more patient target regions and / or organs at risk (OARs) and corresponding dose constraints, selecting (126) a planning localization reference point for each of the one or more patient target regions and / or treatment volumes, calculating (128) a corresponding localization function for each localization reference point, determining (129) a set of treatment radiation source emission positions and calculating a projection of the localization function to each emission position, and calculating (130) a set of translation-invariant emission filters for each emission position based on the planning localization reference point and the localization function projection for each patient target region. Defining (124) contours of the one or more patient target regions may include defining a set of patient target regions that may be connected or associated (e.g., attached to the same bone structure) such that their positions and / or motions may be related. The method (120) may include selecting (128) a planned positioning reference point for the entire patient target region group, and calculating (130) a set of translation-invariant transmit filters based on the planned positioning reference points for the patient target region group. The calculated set of translation-invariant transmit filters and the planned positioning reference points for each patient target region, patient target region group, and / or treatment volume (along with other treatment planning parameters) may be transmitted to a radiotherapy system for positioning during treatment. In some variants, the calculated translation-invariant transmit filter may represent a planned delivered fluence based on (e.g., centered on) the planned positioning reference point. For example, for a particular patient target region (or patient target region group), the positioning function may be a delta function centered on the planned positioning reference point for the patient target region (e.g., tumor centroid). The translation-invariant transmit filter for a particular patient target region may represent a fluence map (e.g., a planned fluence map) centered on the planned positioning reference point.

[0236] Figure 1B A variation of a treatment planning method is depicted that incorporates virtual localization of BgRT patient target regions (ie, patient target regions where the fluence delivered to those target regions is calculated based on acquired imaging and / or biological data, such as PET emission data). Figure 1BThe method (140) described in the claims may include acquiring (142) one or more treatment planning images of one or more patient target regions, defining (144) contours of one or more patient target regions and / or organs at risk (OARs) and corresponding dose constraints, defining (146) a region of interest including a margin surrounding the contours of the patient target regions for each patient target region, selecting (148) a planning positioning reference point for each patient target region, acquiring (150) imaging data spatially masked by the region of interest, determining (152) a set of treatment radiation source emission positions and calculating projections of the acquired imaging data to each emission position, and calculating (154) a set of translation-invariant emission filters for each patient target region based on the planning positioning reference point and the imaging data projections. In some variations, the boundaries of the planned region of interest may include spatial filters. Defining (146) the contours of the one or more patient target regions may include defining a set of patient target regions that may be connected or associated (e.g., attached to the same skeletal structure) such that their positions and / or motions may be related. The method (140) may include selecting (148) a set of planned positioning reference points for the entire set of patient target regions and calculating (154) a set of translation-invariant transmit filters based on the planned positioning reference points for the set of patient target regions.

[0237] Optionally, some treatment planning methods may include designating some patient target areas as SBRT / IMRT target areas and designating other patient target areas as BgRT target areas. Generating treatment plans for both SBRT / IMRT target areas and BgRT target areas may also include acquiring PET images. For each BgRT patient target area, a method may include calculating a translationally invariant emission filter (e.g., a radiation excitation matrix (RFM)) based on the ROI, one or more planning images of the BgRT patient target area, and a dose of a specified BgRT patient target area. Optionally, some treatment planning methods may include determining a set of therapeutic radiation source emission positions, calculating a projection of a positioning function such as a delta function, a Gaussian function, a truncated Gaussian function, etc. to each emission position. Optionally, some treatment planning methods may include calculating a cost function based on a positioning reference point for each patient target area.

[0238] A radiation excitation matrix (RFM) or emission filter may be a matrix that specifies a transformation from a partial image to a fluence map, which may include beamlet patterns and / or beamlet intensities applied to a patient during a treatment session. An emission filter or RFM may represent a relationship between a fluence map F for delivering radiation to a patient region and an image X of the patient region. That is, a radiation excitation matrix or emission filter P may be any matrix such that F=P·X. An emission filter or RFM may be calculated during a treatment planning session for each patient target region in conjunction with calculating a fluence map that minimizes one or more cost functions based on radiation dose constraints and objective formation, such as a cost function C(D,F) of the resulting dose distribution D and fluence F, and optional restrictions on F. Examples of cost functions may include, but are not limited to, a minimum dose to a target region, an average or maximum dose on an OAR, and / or fluence smoothness, total radiation output, total tissue dose, treatment time, and the like. In some variations, generating a radiation excitation matrix P may include setting an optimization problem to minimize a cost function C(D,F), and iterating different sets of P such that the cost function C(D,F) is minimized when the following conditions are met:

[0239] F=P·X and

[0240] D = A·F = A·P·X;

[0241] Where D is the predicted dose distribution, A is a pre-computed dose calculation matrix, F is the predicted total delivered radiation fluence, and X is a known complete image (e.g., an image acquired during a diagnostic imaging session and / or a previous treatment session). The predicted dose distribution D and the predicted radiation fluence F can be calculated using dose constraints, patient target volume and / or OAR data, and patient planning CT images. An example of a dose calculation matrix A can be a (kxn) matrix, where n can be the candidate beamlets {b i} and k can be the number of preselected voxels for the ROI. The i-th column of the dose calculation matrix A (which has k elements) represents the dose from the unit-weighted beamlet b i The dose contribution to each of the k voxels.

[0242] The dose calculation matrix A can be calculated column by column, for example, by ray tracing the aperture of each beamlet along a path through the ROI or patient volume and calculating the contribution of the unit weighted beamlet to each of the k voxels. The beamlet aperture can be an MLC aperture defined by a single MLC leaf opening (i.e., a binary MLC or 2-DMLC). Examples of dose calculation algorithms that can be used in any of the methods described herein can include Monte Carlo simulations, barrel string convolution superposition, pencil beam convolution, and the like.

[0243] The radiation excitation matrix P (also called RFM or emission filter) can be the following matrix: When multiplied by the full image X, it results in a predicted or desired delivered radiation fluence F that minimizes a cost function. The cost function can be convex, allowing the use of well-known convex optimization algorithms such as gradient descent, accelerated proximal gradient method, or interior point method. The calculated radiation excitation matrix P can represent a multiplicative factor that ties the fluence F to the full image X. This relationship can be used during a treatment session to calculate the delivered radiation fluence F at a specific time point based on a partial image x acquired at the same time point. i By multiplying the partial image with the radiation excitation matrix P (e.g., f i =P·x i ) to update the injection volume f i Additional details regarding BgRT treatment planning and delivery methods can be found in U.S. Patent Application No. 15 / 993,325, filed on May 30, 2018, the entire contents of which are incorporated herein by reference.

[0244] Optionally, some methods (120) may include determining (132) a set of therapeutic radiation source emission positions and calculating a projection of an emission filter to each emission position. For example, a radiotherapy system with a rotatable gantry may have 100 circumferentially distributed emission positions or angles around a bore of an advanceable patient platform. The method (120) may include calculating a projection of each emission filter to each of the 100 emission positions. For emission filters convolved with a Gaussian function or a truncated Gaussian function, the width (σ) of the Gaussian function may be selected during treatment planning, where the mean (μ) is centered at a planning location reference point. For example, the width (σ) of the Gaussian function or the truncated Gaussian function may be based on the width of the MLC leaf.

[0245] Figure 2A flowchart representation depicting a variation of a treatment planning method that uses mosaic multi-target localization to register multiple patient target regions during a treatment session. The method (220) may include acquiring (222) one or more treatment planning images of one or more patient target regions, defining (224) contours of one or more patient target regions and / or OARs and corresponding dose constraints, selecting (228) planning localization reference points for each of the one or more patient target regions and / or OARs, and calculating (230) a set of translation-invariant transmit filters based on the planning localization reference points for each patient target region and / or OAR. The method (220) may include generating (234) a treatment planning fluence map based on the transmit filters and the one or more planning images, and defining (236) a perimeter around each patient target region, the patient target region including a region of low fluence values ​​in the treatment planning fluence map. The calculated set of translation-invariant transmit filters, the planning localization reference points for each patient target region and / or OAR, and the treatment planning fluence map with the defined perimeter may be transmitted (along with other treatment planning parameters) to a radiotherapy system for localization during treatment.

[0246] Optionally, some treatment planning methods (220) may include designating (226) each patient target region as a SBRT / IMRT target region or a BgRT target region. If the patient target region has been designated as a BgRT target region, the method (220) may include calculating an ROI for the patient target region. For each BgRT patient target region, the method (220) may also include calculating a translationally invariant transmit filter (e.g., RFM), as described above.

[0247] Optionally, some methods (220) may include determining (232) a set of therapeutic radiation source emission locations and calculating a projection of the emission filter to each of the emission locations. For example, a radiation therapy system with a rotatable gantry may have 100 circumferentially distributed emission locations or angles around a bore of an advanceable patient platform. The method (220) may include calculating a projection of each emission filter to each of the 100 emission locations.

[0248] Optionally, some treatment planning methods (220) may include calculating (238) a bounded dose volume histogram (bDVH) curve for each patient target region and / or OAR, and displaying (240) the bDVH curve and / or dose calculation data for each patient target region and / or OAR to a display device. The bDVH curve for the patient target region may be calculated by calculating the dose per unit volume for each possible position of the patient target region in the motion envelope (or in the case of a BgRT target, in the ROI), and / or based on bioactivity and / or physiological and / or anatomical data acquired before or during the planning period to generate a family of dose volume curves. For example, a family of bounded DVH curves based on emission filters may be calculated for each OAR, ROI, and / or patient target region for a particular moved target region position by performing a rigid shift of a PET image of the patient target region within the ROI and calculating the corresponding dose for the OAR, ROI, and / or patient target region. For example, for a patient having a patient target region and one OAR within the ROI, a family of DVH curves for the patient target region may be calculated for each shifted position of the patient target region within the ROI. The upper threshold limit of the bDVH curve may include the rightmost point of the family of dose volume curves and the lower threshold limit of the bDVH curve may include the leftmost point of the family of dose volume curves. Additional details and variations of methods for calculating bounded DVH curves are provided in U.S. Patent Application No. 16 / 016,272 filed on June 22, 2018, the entire contents of which are incorporated herein by reference.

[0249] Figure 3A and 3BA flowchart representation depicting a variation of a treatment planning method that uses decoupled multi-target localization to register multiple patient target regions during a treatment session. The method (350) may include acquiring (352) one or more treatment planning images of one or more patient target regions, defining (354) contours of one or more patient target regions and / or OARs and corresponding dose constraints, selecting (358) planning localization reference points for each of the one or more patient target regions, and calculating (360) a set of translation-invariant transmit filters based on the planning localization reference points for each patient target region. The method (350) may include generating (362) a fluence map for each patient target region based on the transmit filter and the one or more planning images, and combining (364) all patient target region fluence maps into a cumulative treatment planning fluence map. When the patient target regions are physically separated from each other (e.g., non-overlapping), each patient target region may have a separate planning localization reference point. This allows each patient target region to be moved independently. The corresponding patient target region fluence maps for each patient target region may be added together (because dose delivery is linear) to calculate a total dose. For example, if the positions of the first and second planning positioning reference points are changed from the planning period to the treatment period, the new positioning reference point positions may be used to recalculate the cumulative treatment planning fluence map. Individual treatment planning fluence maps for multiple patient target regions may allow multiple planning positioning reference points to be moved independently of each other, thereby allowing multiple (e.g., two or more) fluence maps to be moved relative to one another to obtain more optimized dose coverage. Additionally or alternatively, the corresponding patient target region fluence map for each patient target region may be individually constrained.

[0250] The method (350) may then include iteratively modifying (366) the cumulative treatment plan fluence map based on one or more dose constraints, such as one or more of: (a) keeping high fluence regions separated from each other, (b) satisfying OAR constraints, and (c) satisfying the original dose constraints / goals.

[0251] In some variations, each constraint on the cumulative treatment plan fluence map can be weighted by a linear factor that defines or approximates its relative importance. In some variations, the fluence map for the target region can be described as a variable x. The sum of the combined fluences can be described as x cumulative The dose calculation matrix for a patient can be defined as A. The dose to a specific target area can be defined as Ax. In addition, the dose to the entire patient can be defined as Ax cumulative For example, the dose constraint may include one or more cost functions, and optionally, each cost function may be weighted by an individual scaling factor. The prescribed dose requirement or constraint (C) may include one or more cost functions, and may include, for example, a cost function C(x) for the radiation fluence (x), and / or a cost function C(Ax) for the treatment volume dose and / or a cost function C(Ax) for the total dose. cumulative), and / or the total injection cost function C(x cumulative ). These can each optionally be adjusted by individual scaling factors (w i ,w k ,w m ,w n ) weighted. For example, the cost function of the cumulative fluence map can be used to optimize treatment time in the case of joint delivery. For example, the cost function of the dose to each treatment volume can be optimized to ensure that the minimum dose is delivered. This ensures that the fluence from different treatment volumes does not deliver most of the dose to a given target. This significantly reduces the coupling between treatment volumes, thereby increasing the robustness of the treatment plan to relative movement between treatment volumes. For example, D cumulative A cost function can be used to limit the average combined dose to the heart from all treatment volumes combined.

[0252] c=∑w i C i (x)+∑w k C k (Ax)+∑w m C m (Ax cumulative )+∑w n C n (x cumulative )

[0253] Additional details regarding the cost function and other constraints can be found in U.S. Provisional Patent Application No. 62 / 966,997, filed on January 28, 2020, the entire contents of which are incorporated herein by reference.

[0254] Additionally or alternatively, in addition to a predetermined set of dose constraints, one or more adjustment constraints (e.g., artificial constraints in addition to tissue constraints, adjustment structures) may be applied to ensure that the dose does not exceed a predetermined threshold in a given zone (e.g., region). In some variations, one or more adjustment constraints may achieve decoupling of radiation delivery between two or more target regions.

[0255] After the cumulative treatment plan fluence map has been modified, the method (350) can include defining (368) a perimeter around each patient target region that includes a region of low fluence values ​​in the cumulative treatment plan fluence map (e.g., adjustment constraints, cost functions), separating (370) the cumulative treatment plan fluence map along the perimeter into individual fluence maps for each patient target region, and for each patient target region, calculating (372) a second set of translation-invariant transmit filters based on the planning positioning reference points and the fluence map for the patient target region. The second set of translation-invariant transmit filters, the planning positioning reference points for each patient target region and / or OAR, and the individual treatment plan fluence map for each patient target region (along with other treatment plan parameters) can be transmitted to a radiation therapy system for positioning during treatment.

[0256] In some variations, such as for SBRT / IMRT delivery, a treatment planning method can include calculating a delivery fluence for a patient target region and / or treatment zone (e.g., based on a prescribed dose, a dose constraint, and / or a dose calculation matrix), wherein the delivery fluence is connected to (e.g., anchored to) a planned positioning reference point. The calculated delivery fluence can then be segmented into machine instructions (by a treatment planning system and / or a radiotherapy system) for delivery. During a treatment session, the calculated delivery fluence can be updated based on an updated position of a positioning reference point (e.g., selected by a user from a positioning image acquired during the treatment session). In this variation, the treatment planning system may not need to calculate a transmit filter.

[0257] Optionally, some treatment planning methods (350) may include designating (356) each patient target region as a SBRT / IMRT target region or a BgRT target region. If the patient target region has been designated as a BgRT target region, the method (350) may include calculating an ROI for the patient target region. When the patient target regions are physically separated from each other to allow each patient target region to move independently, each patient target region may have a separate planning positioning reference point, thereby allowing the fluence map to move relative to one another to optimize dose coverage. For each BgRT patient target region, the method (350) may also include calculating a translation-invariant transmit filter, as described above.

[0258] Optionally, the method (350) may include displaying (374) a visualization of the cumulative treatment plan fluence map on a display device. Optionally, some treatment planning methods (350) may include calculating (376) a bDVH curve for each patient target region and / or OAR, and displaying (378) the bDVH curve and / or dose calculation data for each patient target region and / or OAR on a display device. The bDVH curve for the patient target region may be calculated as previously described.

[0259] Figure 4A flowchart representation of a variation of a treatment planning method for registering multiple patient target regions in a treatment session using BgRT-based multi-target localization is depicted. The method (450) may include acquiring (452) one or more treatment planning images of one or more patient target regions, defining (454) contours of one or more patient target regions and / or OARs and corresponding dose constraints, designating (456) one of the multiple patient target regions as a registration target region, and defining (458) contours of a spatial mask or filter (e.g., ROI, emission region) for each of the other patient target regions (i.e., not the registration target region) to adapt its size and shape to motion of the registration target region and motion of the other patient target regions. The method (450) may include calculating (462) a set of translation-invariant emission filters based on planning localization reference points selected for each patient target region and / or ROI of the registration target region, generating (466) a treatment planning fluence map based on the emission filters and the one or more planning images, and calculating (468) doses for the registration target region and other patient target regions for all patient target regions. The method (450) may also include calculating a translation invariant transmit filter, such as a transmit filter for each ROI of each patient target region, which may be calculated as previously described, and generating (466) a treatment planning fluence map based on the calculated transmit filter and one or more planning images. The translation invariant transmit filter used for ROI virtual positioning and / or the translation invariant transmit filter (e.g., RFM) for BgRT delivery, the planned positioning reference points for each patient target region and / or OAR, and / or any treatment planning fluence map and / or dose calculation may be transmitted (along with other treatment planning parameters) to the radiotherapy system for positioning and radiation delivery.

[0260] Optionally, some treatment planning methods (450) may include defining (460) the contour of a spatial mask or filter (e.g., emission region, ROI) of a registration target region to be smaller than the spatial masks or filters of other patient target regions. For example, the ROI of the registration target region may be smaller than the ROIs of other patient target regions. In some variations, the patient target region selected as the registration target region may be a patient target region that is closest to a critical structure, such as a highly radiosensitive organ and / or a PET-hungry critical structure and / or a bone structure. In some variations, the patient target region selected as the registration target region may be a target region that is closest to a planned structure (e.g., calculated or user-selected), such as a potential dose interface between two patient target regions. In some variations, the patient target region selected as the registration target region may be the most sensitive to uncertainty, such as a region with high dose gradients, critical dosimetry targets or constraints, inconsistent PET activity (e.g., hypoxic or perfused regions), or variable motion trajectories near the edge of the ROI.

[0261] Optionally, some methods (450) may include determining (464) a set of therapeutic radiation source emission positions and calculating a projection of an emission filter to each emission position. For example, a radiotherapy system with a rotatable gantry may have 100 circumferentially distributed emission positions or angles around a bore of an advanceable patient platform. The method (450) may include calculating a projection of each emission filter to each of the 100 emission positions. Optionally, the method (450) may include calculating (470) a bDVH curve for each patient target region and / or OAR and displaying (472) the bDVH curve and / or dose calculation data for each patient target region and / or OAR to a display device. The bDVH curve for the patient target region may be calculated as previously described.

[0262] As previously described, any treatment planning method for multi-target irradiation can optionally include calculating bDVH curves for each patient target region and / or OAR and displaying DVH and other dose data to the clinician for review and / or approval. In some variations, such dose data can be used as feedback (i.e., as additional constraints) to further improve treatment plan fluence maps and / or emission filters that can help improve compliance with dosimetry goals and prescriptions. Figures 5A-5C Depicted is a flowchart representation of a variation of a treatment planning method for modifying a planning fluence map and / or transmit filter based on user selected modifications to a confidence interval for a bDVH of a patient target region and / or shifting the dose distribution.

[0263] bDVH confidence intervalsEdit

[0264] bDVH confidence interval editing can provide a mechanism by which spatial uncertainty can be reduced or eliminated. bDVH calculations can often be calculated with 95% confidence intervals, with the goal that on the day of treatment, the patient will be represented within those limits. Reducing the width of the limits in the bDVH is intended to make the potential minimum dose D pmin and the potential maximum dose D pmax Closer to the nominal dose D n Methods to reduce the difference from the nominal dose may include reducing the confidence interval. For example, an 80% confidence interval may result in a narrower bDVH curve, where D pmax and D pmin Probably closer to D n The trade-off is that, for example, rather than expecting one in twenty patients to fail the bDVH safety check on treatment, one in five patients may fail the bDVH safety check and be denied treatment with a non-definitive treatment approach (i.e., BgRT). Similarly, if the bDVH of a target region comes back fairly tight on the initial 95% CI calculation, the bDVH can be recalculated with a higher confidence interval (e.g., 99% CI), which will expand the bDVH, resulting in a D pminand D pmax Move further away from D n (i.e., widening / expanding the bDVH curve). Using this capability, the clinician may be able to reduce or eliminate hot and cold spots within existing boundaries.

[0265] Figure 5A A treatment planning method including bDVH confidence interval editing is depicted. The method (550) may include developing (551) a treatment plan with one or more specified uncertainty vectors (e.g., biological activity, set position error, etc.) and selecting (552) a confidence interval (CI) for the uncertainty vector, which may be determined based on the type of uncertainty. The method (550) may include optimizing (553) a treatment plan fluence map with uncertainty, calculating the bDVH using a CI that describes the likelihood that the treatment daily dose fits within the bDVH bounds, and evaluating (554) the bDVH and determining whether the bounds are acceptable. For example, the bDVH may be output to a display device and viewed by a user. If the bounds are deemed acceptable, the method (550) may include calculating (556) a final dose for the treatment plan and approving (557) the bounds for the treatment plan. If the bounds are unacceptable, the method (550) may include determining (558) how to adjust the bounds. In some variations, the method (550) may include widening the bounds and increasing (559) acceptable uncertainty and setting a new CI that is larger than the original CI. In some variations, the method (550) can include tightening the bounds and reducing (560) the acceptable uncertainty and setting a new CI that is smaller than the original CI. After the CI is adjusted, the method (550) can include optimizing (561) the treatment plan with uncertainty, calculating a new bDVH using the new CI that describes the likelihood that the treatment daily dose fits within the bDVH bounds, and then evaluating (554) the new bDVH and determining whether the bounds are acceptable. The evaluation and calculation of the bDVH (554-561) can be iterated until a bDVH with acceptable bounds is calculated.

[0266] In some variations, confidence interval editing may include determining whether the treatment plan fluence map needs to be re-optimized after the CI has been adjusted. Figure 5BA treatment planning method including a determination as to whether to re-optimize after a bDVH confidence interval edit is depicted. The method (570) may include developing (571) a treatment plan with one or more specified uncertainty vectors (e.g., biological activity, set position error, etc.) and selecting (572) a confidence interval (CI) for the uncertainty vector, which may be determined based on the type of uncertainty. The method (570) may include optimizing (573) a treatment plan fluence map with uncertainty, calculating a bDVH using a CI that describes the likelihood that the treatment daily dose fits within the bDVH limits, and evaluating (574) the bDVH and determining whether the limits are acceptable. For example, the bDVH may be output to a display device and viewed by a user. If the limits are deemed acceptable, the method (570) may include calculating (576) a final dose for the treatment plan and approving (577) the limits for the treatment plan. If the limits are unacceptable, the method (570) may include determining (578) how to adjust the limits. In some variations, the method (570) may include widening the limits and increasing (579) the acceptable uncertainty and setting a new CI that is greater than the original CI. In some variations, the method (570) may include tightening the limits and reducing (580) the acceptable uncertainty and setting a new CI that is less than the original CI. After the CI has been adjusted, the method (570) may include determining whether a new optimization is needed. If so, the method (570) may include optimizing (581) the treatment plan with uncertainty, calculating a new bDVH using a new CI that describes the likelihood that the treatment daily dose fits within the bDVH limits, and then evaluating (574) the new bDVH and determining whether the limits are acceptable. If it is determined that optimization is not required, the method (570) may proceed directly from the CI adjustment to evaluating (574) the new bDVH. The evaluation and calculation of the bDVH (574-581) may be iterated until a bDVH with acceptable limits is calculated. In some variations, a visualization graphic may optionally be included to represent the impact on the bDVH due to changes in the CI.

[0267] Some treatment planning methods may include displaying a treatment planning dose distribution (e.g., calculated from a treatment planning fluence map) superimposed on a patient anatomical image that also includes each patient target region to be treated during a treatment session, receiving clinician input related to dose movement, and recalculating the treatment planning fluence map and / or emission filter based on the dose movement input by the clinician. In some variations, the dose movement may be a rigid movement of the dose by about 0.1 mm to about 1 mm in any direction. These minor dose movements may help avoid unnecessary fluence delivery to the spine and / or reduce hot spots caused by two interacting fluence maps between target regions in two planes. For example, when fluence map sub-regions are individually positioned in mosaic multi-target localization, and / or when individual fluence maps of different patient target regions are individually positioned in decoupled multi-target localization, the cumulative delivered fluence map (i.e., the sum of all delivered fluence map sub-regions and / or the sum of all individual fluence maps for each patient target region) may have regions with unwanted fluence, such as regions with elevated fluence levels at OARs or healthy tissue regions. These unwanted fluence regions may not exist in the planning fluence map, however, as fluence map changes (e.g., moves) are implemented during positioning, adverse fluence map artifacts may appear in the delivered fluence map. The radiotherapy system can generate a visualization graphic reflecting these fluence map changes (and / or dose changes) overlaid with the patient's anatomical image, so that the user can decide whether any delivered fluence map can be moved to mitigate any unwanted dose or fluence. Alternatively or additionally, in some variations, dose movement can be performed after fluence map optimization during treatment planning, which can help facilitate the generation of treatment plans and / or planning fluence maps that meet dosimetry goals. After the dose move, an additional fluence map optimization step may be optional (i.e., re-optimization may not be necessary). The updated fluence map and / or transmit filter can be transmitted to the radiotherapy system for positioning and treatment.

[0268] Figure 5C A flowchart depicting a variation of a treatment planning method (590) comprising calculating (591) a treatment planning fluence map (and / or emission filters, such as any emission filters described herein) for all patient target regions, calculating (592) a dose distribution map based on the treatment planning fluence map, generating (593) a composite image comprising the dose distribution map superimposed on an image of a patient anatomy comprising one or more patient target regions, receiving (594) user (e.g., clinician, radiation dosimeter) input related to shifting dose on the dose distribution map, and calculating (595) an updated treatment planning fluence map based on the dose shift input by the user. Fluence map optimization after dose shifting may be optional.

[0269] In some treatment planning methods, dose variance (also called delta dose) can be used as a constraint for optimizing the treatment planning fluence map. A minimum or maximum allowed dose variance can be selected as a constraint. For example, setting the maximum dose variance as a treatment planning fluence map optimization constraint may help reduce the width of the bDVH while keeping the default confidence interval (e.g., CI = 95%). Figure 6 A treatment planning method including setting dose variance as a constraint for generating a treatment plan fluence map is depicted. The method (670) may include developing (671) a treatment plan having one or more specified uncertainty vectors (e.g., biological activity, set position error, etc.) and selecting (672) a maximum allowable dose variance D of the uncertainty vectors. plan , which may be determined according to the type of uncertainty. The method (670) may include optimizing (673) a dose having a maximum allowable dose variance D plan treatment plan fluence maps, calculation of bDVH using CIs describing the likelihood that the treatment day dose fit is within the bDVH bounds, and evaluation of the (674) user synthesized dose variance D actual And determine D actual Is it acceptable? If you think D actual is acceptable, the method (670) may include calculating (676) a final dose for the treatment plan and approving (677) the dose variance for the treatment plan. actual is unacceptable, then the method (670) may include determining (678) how to adjust the dose variance. In some variations, the method (670) may include increasing (559) the acceptable dose variance and setting a dose greater than the original D plan The new dose variance D plan In some variations, the method (670) may include reducing (580) the acceptable dose variance and setting a dose smaller than the original D plan The new dose variance D plan '. After adjusting D plan Thereafter, the method (670) may include using the updated dose variance D plan 'Constrained optimization (681) treatment plan, based on D plan 'The constraint selects a geometry that is more or less susceptible to dose variance, and then evaluates (674) the new D actual And determine whether the dose variance is acceptable. The evaluation and calculation of the dose variance (674-681) can be iterated until an acceptable dose variance is calculated.

[0270] Multi-target localization method

[0271] The virtual positioning method moves the planned fluence map of the patient target area to reflect the current / real-time position of the patient target area during treatment. During treatment planning, a set of translation-invariant emission filters calculated based on the planned positioning reference point and the desired dosimetry target can be calculated, and during the treatment period, the translation-invariant emission filters can be used to calculate the delivery fluence generated when the dose is delivered to the patient treatment area. A method for virtual positioning may include selecting a positioning reference point corresponding to the planned positioning reference point. For example, if the planned positioning reference point is the center of the patient target area, then during positioning, the positioning reference point should also be selected as the center of the patient target area reflected in the positioning image. Then, a positioning function (e.g., a delta function, a Gaussian function, a truncated Gaussian function, etc.) based on the selected positioning reference point can be calculated. For example, the positioning function can be a delta function, it can be an impulse function centered on the positioning reference point, or the positioning function can be a Gaussian function with a width (σ) selected during treatment planning, where the average value (μ) is centered on the positioning reference point. The delivered fluence for each shot position of the therapeutic radiation source can be calculated by convolving the projection of the delta function at that shot position with the projection of the translation-invariant transmit filter at that shot position (which can be predetermined by the treatment plan). The delivered fluence for each shot position of the patient target region can then be segmented into radiotherapy system machine instructions for radiation delivery.

[0272] Fig. 7AA flow chart representation of one variation of a method for virtual positioning of SBRT / IMRT delivery is depicted. The method can be used for virtual positioning of a single patient target region or multiple patient target regions and can be used multiple times at the beginning of a treatment session or throughout a treatment session. In some variations, a treatment plan can include multiple treatment volumes, each with one or more patient target regions. The patient can be physically set up / positioned once for a treatment volume, and each patient target region within the treatment volume can be virtually positioned. In some variations where groups of patient target regions have been defined during treatment planning, each group can share a single positioning reference point and be virtually positioned together. The method (700) may include acquiring (702) one or more localizer images of one or more patient target regions, selecting (704) localizer reference points within the acquired images for each patient target region, wherein the localizer reference points correspond to planned localizer reference points selected during treatment planning, calculating (706) a localizer function (e.g., delta, Gaussian, truncated Gaussian, etc.) from the localizer reference points of each patient target region and calculating projections of the localizer function to each therapeutic radiation source emission position, and calculating (708) a fluence for delivery to each patient target region for each emission position by convolving the corresponding localizer function projection with a translation-invariant emission filter derived based on the planned localizer reference points. As described above, in some variations, the delivered fluence for each emission position of the therapeutic radiation source may be calculated by convolving the projections of the localizer function and the emission filter at each emission position. Optionally, the method (700) may include performing (710) radiation delivery (i.e., emitting the delivered fluence to each patient target region using the therapeutic radiation source). The translation-invariant emission filter may be calculated based on (e.g., centered on) the planned localizer reference points during treatment planning. In some variations, the localization function may be a delta function, and the translation-invariant transmit filter calculated during treatment planning may represent a fluence map centered at a planned localization reference point (e.g., a planned fluence map). In this example, calculating (708) the delivered fluence may include convolving the calculated delta function (which is centered at a selected localization reference point) with the translation-invariant transmit filter, which may result in the generation of a delivered fluence map that is shifted as a planned fluence map. In some variations, the radiotherapy system may segment the delivered fluence map into machine instructions in real time, i.e., minutes or seconds prior to radiation delivery. The patient target region to be localized may be included in a single localization image, or may be included in multiple localization images acquired at the beginning of a treatment session and / or throughout a treatment session. For example, a first patient target region may be identified in a first image and a second patient target region may be identified in a second image. The images may be separate images acquired at separate times or simultaneously, or may be sub-regions of a single image. The planned localization reference point may be the treatment isocenter, however, in some variations, the planned localization reference point may not be the treatment isocenter and may be any point selected by a user. The localization reference point may be specified by coordinates.The localization function used to localize the target area of ​​the patient may be an impulse function or a peak value or pixel centered at a selected localization reference point, as previously described. The method (700) may be used in conjunction with any of the treatment planning methods of FIGS. 1-4. Figure 1A , 1B method together with the

[0273] Figure 7B A flowchart representation of a variation of a method for virtual positioning of BgRT delivery to one or more patient target regions is depicted. Virtual positioning of the BgRT patient target regions includes adjusting a position ROI based on an offset between a planned positioning reference point and a positioning reference point selected during a treatment session. The method (720) may include acquiring (722) one or more positioning images of the one or more patient target regions, selecting (724) a positioning reference point within the acquired image for each patient target region, wherein the positioning reference point corresponds to a planned positioning reference point selected during treatment planning, calculating (726) a spatial offset based on movement between the selected positioning reference and the planned positioning reference point, and moving (728) the boundaries of a planned region of interest (ROI) based on the calculated spatial offset. In some variations, moving (728) the boundaries of the planned region of interest includes adjusting the boundaries of the planned region of interest by a rolling correction factor. The rotation and translation are applied to the planned region of interest, the roll correction factor representing the rotational translation of the positioning reference point relative to the planned positioning reference point. The method (720) may further include the steps of acquiring (730) imaging data and spatially masking (e.g., filtering) the imaging data using the moved region of interest, calculating (732) a fluence for delivery to each patient target region at each emission position of the therapeutic radiation source by convolving a projection of the acquired imaging data with a corresponding translation-invariant emission filter, and performing (734) radiation delivery (i.e., emitting the delivery fluence to each patient target region using the therapeutic radiation source). The acquired imaging data (730) may include PET imaging data (e.g., positron annihilation emission path, LOR), X-ray imaging data, MRI imaging data, ultrasound imaging data, optical imaging data (e.g., from a camera), etc. Calculating (732) the delivery fluence for a particular emission position may include projecting the acquired, spatially masked imaging data to the emission position, and convolving the imaging data projection with the emission filter for the emission position and the target region. The transmit filter may be one of the transmit filters calculated during treatment planning (e.g., using Figure 1B In a variation where a rolling correction factor has been applied to the planned region of interest, calculating (732) the delivered fluence may include applying a set of transmit filters to the rolling correction factor Circular convolution, and in some variants, may include moving the ROI as described above (e.g., as Fig.34The method (720) may be used in conjunction with any of the treatment planning methods of FIGS. 1-4 . Figure 1A , 1B method together with the

[0274] Fig. 8A A flowchart representation of a variation of a method for mosaic multi-target localization is depicted. The method can be used at the beginning of a treatment session (e.g., to register / localize all patient target regions) or multiple times throughout a treatment session (e.g., to sequentially register / localize patient target regions). The method (800) can include acquiring (802) one or more localization images of one or more patient target regions, dividing (804) a treatment plan fluence map into one or more fluence map sub-regions according to a perimeter around each patient target region defined during treatment planning, and moving (806) each fluence map sub-region such that a high fluence region is co-localized with its corresponding patient target region. Moving (806) the fluence map sub-regions can be performed using the virtual localization methods described herein (e.g., selecting a localization reference point for each patient target region, calculating a delta function based on the localization reference point, and convolving the delta function with a translation-invariant transmit filter). Alternatively or additionally, moving (806) the fluence map sub-regions can be performed by moving a radiotherapy system machine instruction (e.g., MLC, gantry, linear accelerator, jaws, etc.).

[0275] Optionally, some variations of method (800) may include calculating (808) a dose for each patient target region based on the moved fluence map sub-regions, comparing the calculated dose to a bounded dose volume histogram curve calculated during treatment planning, and / or displaying the bounded dose volume histogram curve and / or dose calculation data for each patient target region and / or OAR to a display device. Optionally, method (800) may include performing (810) radiation delivery (i.e., emitting a delivery fluence to each patient target region using a therapeutic radiation source). In some variations, the radiotherapy system may segment the delivery fluence map into machine instructions in real time, i.e., minutes or seconds prior to radiation delivery. The patient target region to be located may be included in a single localization image, or may be included in multiple localization images acquired at the beginning of a treatment session and / or throughout a treatment session, as described above. Method (800) may be used in conjunction with any of the treatment planning methods of FIGS. 1-4 , e.g., Figure 2 method together with the

[0276] Figure 8BA flowchart representation of a variation of a method for mosaic multi-target positioning that includes patient platform movement or adjustment is depicted. In some methods, patient setup can include adjusting the orientation of the patient platform (e.g., roll, pitch, yaw, xyz translation, etc.) based on a scout image and a treatment planning image. The method can be used at the beginning of a treatment session (e.g., to register / position all patient target regions) or multiple times throughout a treatment session (e.g., to sequentially register / position patient target regions). The method (820) can include acquiring (822) one or more scout images of one or more patient target regions, dividing (824) a treatment planning fluence map into one or more fluence map sub-regions based on a perimeter around each patient target region defined during treatment planning, calculating (826) a patient platform position movement vector for each fluence map sub-region based on the scout image and the treatment planning image, moving (828) the fluence map sub-region for each patient platform position so that a high fluence region is co-located with its corresponding patient target region, and calculating (830) a fluence for each patient target region at each patient platform position movement vector. Moving (828) the fluence map sub-region may be performed using the virtual positioning methods described herein (e.g., selecting a positioning reference point for each patient target region, calculating a delta function based on the positioning reference point, and convolving the delta function with a translation-invariant transmit filter). Alternatively or additionally, the fluence map sub-region may be moved (828) by moving radiotherapy system machine instructions (e.g., MLC, gantry, linear accelerator, jaws, etc.).

[0277] Optionally, some variations of method (820) may include calculating (832) a dose for each patient target region based on the moved fluence map sub-regions, comparing the calculated dose to a bounded dose volume histogram curve calculated during treatment planning, and / or displaying the bounded dose volume histogram curve and / or dose calculation data for each patient target region and / or OAR to a display device. Optionally, method (820) may include performing (834) radiation delivery (i.e., emitting a delivery fluence to each patient target region using a therapeutic radiation source). In some variations, the radiotherapy system may segment the delivery fluence map into machine instructions in real time, i.e., minutes or seconds prior to radiation delivery. The patient target region to be located may be included in a single localization image, or may be included in multiple localization images acquired at the beginning of a treatment session and / or throughout a treatment session, as described above. Method (820) may be used in conjunction with any of the treatment planning methods of FIGS. 1-4 , e.g., Figure 2 method together with the

[0278] Fig. 9A flowchart representation of a variation of a method for decoupled multi-target localization is depicted. The method (900) may include acquiring (902) one or more localization images of one or more patient target regions, wherein each patient target region has a separate individual treatment plan including a set of treatment plan parameters (including a set of shift-invariant transmit filters), selecting (904) a localization reference point for each patient target region and calculating a delivered fluence map for each target region using a virtual localization method (e.g., calculating a delta function based on the localization reference point and convolving the delta function with the shift-invariant transmit filter to obtain a delivered fluence map for each patient target region), and calculating (906) a cumulative fluence map by combining the delivered fluence maps for all patient target regions, and calculating a dose for each patient target region. The method (900) may include evaluating (908) whether dose objectives for all patient target regions are met and / or whether high fluence regions of the individual delivered fluence maps are sufficiently separated from each other (i.e., not co-localized with other high fluence regions). If dose objectives for all patient target regions are met and / or high fluence regions of individual delivered fluence maps are sufficiently separated from one another, method (900) may include performing (912) radiation delivery, which may include segmenting (914) one or more of the following into radiotherapy system instructions: (a) an individual fluence map for each patient target region; and / or (b) a cumulative fluence map. If dose objectives for all patient target regions are not met, and / or high fluence regions of individual delivered fluence maps are not sufficiently separated from one another, method (900) may include generating (916) a visual and / or audible notification. Dose calculation data and / or DVH curves may optionally be presented to a user so that they may evaluate a next course of action. In some variations, the radiotherapy system may segment the delivered fluence map into machine instructions in real time, i.e., minutes or seconds prior to radiation delivery. The patient target region to be positioned may be included in a single positioning image, or may be included in multiple positioning images acquired at the beginning of a treatment session and / or throughout a treatment session, as described above. Method (900) may be used in conjunction with any of the treatment planning methods of FIGS. 1-4 , such as Figure 3A-3B method together with the

[0279] Fig.10A flowchart representation of a variation of a method for decoupling multiple target localization is depicted. The method (1000) may include acquiring (1002) one or more localization images of one or more patient target regions, localizing (1004) a patient target region designated as a registration target region during treatment planning along with a treatment isocenter (e.g., a central location of a treatment radiation beam), and determining (1006) whether the other patient target regions are within the boundaries of a spatial emission filter (e.g., an excitation region, ROI) designated during treatment planning. If the other patient target regions are within the boundaries of the spatial mask or filter (e.g., within the ROI), the method (1000) may include performing (1002) radiation delivery. If the other patient target regions are not within the boundaries of the spatial mask or filter (e.g., not within the ROI), the method (1000) may include generating (1010) a visual and / or audible notification. The position data of the patient target regions relative to their associated ROIs may optionally be presented to a user so that they can evaluate a next course of action. Optionally, the ROI of one or more of these non-registered target regions may be positioned using the virtual positioning methods described herein. Positioning (1004) the registered target region may use one or more settings and / or positioning methods. For example, positioning (1004) the registered target region may include one or more of the following: (a) moving the radiotherapy system machine instructions (e.g., MLC, gantry, linear accelerator), (b) selecting a positioning reference point for the ROI of the registered target region, calculating a delta function based on the positioning reference point, and convolving the function (e.g., delta, Gaussian, truncated Gaussian) with the ROI, and / or (c) calculating a patient platform position movement vector and adjusting the patient platform accordingly. In some variations, radiation delivery may include segmenting one or more of the following into radiotherapy system instructions: (a) an individual fluence map for each patient target region; and / or (b) a cumulative fluence map. In some variations, the radiotherapy system may segment the delivery fluence map into machine instructions in real time, i.e., a few minutes or seconds before radiation delivery. The patient target area to be located may be included in a single locator image, or may be included in multiple locator images acquired at the beginning of a treatment session and / or throughout a treatment session, as described above. The method (1000) may be used in conjunction with any of the treatment planning methods of FIGS. 1-4 . Figure 4The method of using a virtual positioning system for a plurality of patient target regions may be used together. For example, each of a plurality of patient target regions may have a separate planned positioning reference point and a set of transmit filters. During a treatment session, the position of the positioning reference point of each of the plurality of patient target regions may be updated based on the acquired positioning image (e.g., the positioning reference point may be selected by a user). The separate and / or independent virtual positioning of each patient target region based on the updated positioning reference point effectively moves the delivery fluence map to the real-time position of the plurality of patient target regions. In such a manner, the fluence map of each of the plurality of patient target regions may be moved relative to each other. For example, in a treatment session with two or more patient target regions, the radiation delivery method may include performing one or more (e.g., two or more) virtual positioning to move the planned fluence map of each of the two or more patient target regions.

[0280] Fig.11A is a flow chart illustrating a method (100). The method (100) may be used to position a patient for radiation therapy. Fig.11A As shown, the method (100) includes acquiring (102) images of a first patient treatment volume and a second patient treatment volume. In some embodiments, the first patient treatment volume and the second patient treatment volume may include one or more tumor regions (e.g., patient target regions). For example, in some embodiments, the first patient treatment volume may include a first portion of a tumor and the second patient treatment volume may include a second portion of a tumor. In some embodiments, the first patient treatment volume and the second patient treatment volume may each include one or more discrete tumors located in different regions of the patient's body. The acquired images may be, for example, images acquired via one or more of PET, CT, MRI, ultrasound, optical imaging modalities, combinations thereof (e.g., surface tracking / mapping, optical and CT to predict internal locations based on external surface data), and / or any other suitable method. In some embodiments, for example, the CT system may be used to acquire one or more images prior to or at the beginning of a treatment session. In some embodiments, the CT system may be attached to the same gantry as a radiation source intended to deliver radiation therapy during the treatment session. In some embodiments, the CT system may be attached to a gantry different from the gantry supporting the radiation source. In some embodiments, where radiation is delivered at discrete patient platform locations or sites (i.e., beam stations), the location of a first patient treatment volume may correspond to the location of the first beam station of a source of therapeutic radiation and the location of a second patient treatment volume may correspond to the location of a second beam station. In some variations, the first and second treatment volumes may overlap, while in other variations, the first and second treatment volumes do not overlap.

[0281] A first set of patient position movement vectors may be calculated (104) based on an acquired image of a first patient target area and a treatment planning image (also referred to herein as a "first treatment planning image"). The position of the first treatment zone and / or patient target area in the acquired image may be compared in 2D and / or 3D with the position of the first treatment zone and / or patient target area in the treatment planning image. For example, in some embodiments, the patient target area may be divided into sub-areas (e.g., sub-volumes) that may be represented by voxels, and the coordinates of each voxel of the acquired image may be compared with the coordinates of a corresponding voxel of the patient target area in the treatment planning image. Each vector in the first set of patient position movement vectors may represent a distance and a direction difference between the coordinates of a voxel of the acquired image and the coordinates of a corresponding voxel of the treatment planning image. In some embodiments, the direction difference may include a tilt angle. In some embodiments, the first set of patient position movement vectors may be calculated by moving the acquired image relative to the treatment planning image to align or register the first patient target area of ​​the treatment planning image with the first patient target area of ​​the acquired image. For example, each voxel of the acquired image may be translated along or about the X, Y, and / or Z axis, maintaining the relative position of each voxel of the acquired image to each other during the movement of the acquired image, until the acquired image and the treatment planning image are approximately aligned with respect to the first patient target region (e.g., aligned within a predetermined acceptable tolerance or difference such that there is an acceptable area or overlap ratio between the first patient target region in the image). A first set of patient position movement vectors may then be calculated based on the position and / or location differences between the acquired image before and after being moved to increase alignment with the treatment planning image. The first set of patient position movement vectors may reflect the distance and / or direction that each voxel of the acquired image will be translated for acceptable alignment between the first patient target region of the acquired image and the first patient target region of the treatment planning image. In addition, the first set of patient position movement vectors may include or correspond to instructions associated with a first position and / or first orientation of the patient (e.g., a first position and / or first orientation of a surface on which the patient is disposed) such that the first patient target region of the patient is located approximately where the first patient target region was when the treatment planning image was acquired. This may facilitate delivery of therapeutic radiation to the patient target region that is closer to the treatment plan. Additionally, the first set of patient position movement vectors may include information regarding any tilt, pitch, yaw, and / or roll corrections that may need to be achieved by positioning the patient platform and / or by adjusting the roll of a gantry coupled to a radiation source (e.g., a therapeutic radiation source) (e.g., for correcting a gantry firing position) such that the position of the first patient target area approximates the position of the first patient target area in the first treatment planning image.

[0282] In some embodiments, the acquired image of the first treatment zone and / or the patient target area and the treatment planning image of the first patient target area can each be a two-dimensional image. The two-dimensional acquired image can be compared with the two-dimensional treatment planning image to calculate a first set of patient position movement vectors. In some embodiments, multiple two-dimensional images of the first treatment zone and / or the patient target area can be acquired along different orientations or planes (e.g., three or more orientations or planes), and the image can be compared with the corresponding treatment planning image of the first patient target area acquired along the same orientation or plane. The first set of patient position movement vectors can be calculated using the change in the position of the first patient target area along each image plane at each orientation. For example, the acquired images can include an acquired axial image, an acquired sagittal image, and an acquired coronal image of the first patient target area of ​​the patient. When the patient lies in a supine position on a surface such as a patient platform or a treatment couch and the patient is oriented so that the patient will first encounter the head of the treatment radiation source, the acquired axial image may be taken along the patient's axial plane (e.g., a plane dividing the body into upper and lower parts), the acquired sagittal image may be taken along the patient's sagittal plane (e.g., a plane dividing the patient into left and right parts), and the acquired coronal image may be taken along the patient's coronal plane (e.g., a plane dividing the patient into abdomen and back). The axial plane is disposed perpendicular to the sagittal plane, and the coronal plane is disposed perpendicular to both the axial plane and the sagittal plane. The treatment planning images may include a treatment planning axial image, a treatment planning sagittal image, and a treatment planning coronal image of a first patient target area of ​​the patient. Therefore, the acquired axial image corresponds to the treatment planning axial image, the acquired sagittal image corresponds to the treatment planning sagittal image, and the acquired coronal image corresponds to the treatment planning coronal image.

[0283] The amount by which the patient position and / or orientation should be adjusted along or about each of the X-axis, Y-axis, and Z-axis (e.g., by moving the patient surface and / or rotating the radiation source) for treatment of the first patient target region can be reflected by a first set of patient position movement vectors based on the difference between the treatment planning image and the corresponding acquired image taken in each of the axial, sagittal, and coronal planes of the patient. In some embodiments, the X-axis of the patient surface can be parallel to the intersection of the sagittal and coronal planes of the patient and can be disposed in the sagittal plane. The Y-axis of the patient surface can be parallel to the intersection of the axial and coronal planes of the patient and can be disposed in the axial plane. The Z-axis of the patient surface can be parallel to the intersection of the sagittal and axial planes of the patient and can be disposed in the sagittal or axial planes of the patient. To determine the first set of patient position movement vectors, each acquired image of the first patient target region can be compared with a corresponding treatment planning image of the first patient target region taken in the same plane to determine a distance correction and / or a rotation correction of the patient in the same plane (e.g., by movement of the patient surface and / or rotation of the radiation source). One or more vectors in the first set of patient position movement vectors may indicate an amount and direction by which the patient surface will be moved (e.g., displaced and / or rotated) so that the first patient target region approximates the position of the first patient target region in the treatment planning image. One or more vectors in the first set of patient position movement vectors may also indicate an amount and direction by which the radiation source may be moved (e.g., rotated on a gantry) so that the position of the first patient target region approximates the position of the first patient target region in the treatment planning image. In some embodiments, the first set of patient position movement vectors may reflect up to six corrections (i.e., an amount of adjustment along or around each of the X-axis, Y-axis, and Z-axis of the patient platform). In some embodiments, a DICOM spatial registration object (SRO) may be used to determine each of the six corrections associated with the first set of patient position movement vectors (i.e., an amount of adjustment along or around each of the X-axis, Y-axis, and Z-axis of the patient platform).

[0284] In some embodiments, the first set of patient position movement vectors can be calculated by moving (e.g., by shifting and / or rotating) each acquired image relative to its respective treatment planning image to align or register the first treatment volume and / or patient target region of the treatment planning image with the first patient target region of the acquired image. Each acquired image can be moved a specific distance and / or rotated a specific amount to improve the registration of the first patient target region of the treatment planning image with the first patient target region of the acquired image. For example, an image acquired along an axial plane during treatment can be compared with a treatment planning image acquired along the patient's axial plane to determine the amount of correction required along the transverse axis (i.e., Y axis) and the vertical axis (i.e., Z axis) of the patient surface (e.g., table or bed) in the axial plane and the amount of correction required about the gantry roll axis (e.g., about the X axis). An image acquired along a sagittal plane during treatment can be compared with a treatment planning image acquired along the patient's sagittal plane to determine the amount of correction required along the longitudinal axis (i.e., X axis) and the vertical axis, and the amount of pitch correction (e.g., rotation about the Y axis) of the patient surface (e.g., table or bed) in the sagittal plane. Images acquired along the coronal plane during treatment can be compared to treatment planning images acquired along the patient's coronal plane to determine the amount of correction required along the transverse and longitudinal axes and the amount of yaw correction (i.e., about the Z axis) of the patient surface (e.g., table or couch) in the coronal plane.

[0285] The first set of patient position movement vectors may reflect an amount of correction of the patient surface required along or about each of the X-axis, the Y-axis, and the Z-axis to improve the alignment between the first patient target region and the position of the first patient target region when the treatment planning image was acquired. Thus, in some embodiments, the first set of patient position movement vectors may include at least one patient position movement vector reflecting an adjustment along the X-axis of the patient surface based on a longitudinal difference determined from a comparison of an acquired sagittal image with a treatment planning sagittal image and / or a comparison of an acquired coronal image with a treatment planning coronal image. The first set of patient position movement vectors may include at least one patient position movement vector reflecting an adjustment along the Y-axis of the patient surface based on a transverse difference determined from a comparison of an acquired axial image with a treatment planning axial image and / or a comparison of an acquired coronal image with a treatment planning coronal image. The first set of patient position movement vectors may include at least one patient position movement vector reflecting an adjustment along the Z-axis of the patient surface based on a vertical difference determined from a comparison of an acquired axial image with a treatment planning axial image and / or a comparison of an acquired sagittal image with a treatment planning sagittal image. In some embodiments, the adjustment along the Z-axis of the patient surface included in the first set of patient position movement vectors can be an average of a lateral difference determined from a comparison of an acquired axial image with a treatment planning axial image and a lateral difference determined from a comparison of an acquired sagittal image with a treatment planning sagittal image.

[0286] With respect to rotation of the patient surface about the patient surface axis and / or rotation of the radiation source about the radiation source axis, the first set of patient position movement vectors may include a rotation correction of the patient surface about the patient surface Y axis based on a comparison of the acquired sagittal image with the treatment planning sagittal image, and / or a rotation correction of the patient surface about the patient surface Z axis based on a comparison of the acquired coronal image with the treatment planning coronal image, and / or a rotation correction of the radiation source about the radiation source X axis (e.g., the X axis of the gantry coextensive with the X axis of the patient surface) based on a comparison of the acquired axial image with the treatment planning axial image. For example, moving or panning an acquired sagittal or coronal image to match a treatment planning sagittal or coronal image can be translated into a set of patient position movement vectors representing movement in the X, Y, and Z axes. Tilting an acquired sagittal or coronal image to match a treatment planning sagittal or coronal image can be translated into a set of patient position movement vectors representing pitch and / or roll position corrections. Thus, the amount by which the patient position or orientation should be adjusted along or about each of the X, Y, and Z axes can be reflected by a first set of patient position movement vectors based on the differences between the treatment planning image and the corresponding acquired images taken in each of the axial, sagittal, and coronal planes of the patient.

[0287] A second set of patient position movement vectors may be calculated (106) based on the acquired image, a treatment planning image of the second treatment volume and / or the patient target region (also referred to herein as a "second treatment planning image"), and the first set of patient position movement vectors. In some embodiments, the second set of position movement vectors may include distance and / or directional translations. In some embodiments, the directional translation may include a tilt angle. In some embodiments, similar to what is described above with respect to the first set of patient position movement vectors, the second set of patient position movement vectors may be calculated by moving the acquired image relative to the treatment planning image to align or register the second patient target region of the treatment planning image with the second patient target region of the acquired image. For example, each voxel of the acquired image may be translated along or about an X, Y, and / or Z axis, maintaining the relative position of each voxel of the acquired image to each other during the movement of the acquired image until the acquired image and the treatment planning image have improved alignment relative to the second patient target region (e.g., the overlap between the second patient target region in the image is increased or optimized). The second set of patient position movement vectors may then be calculated based on the difference in position and / or location between the acquired image before and after being moved to increase alignment with the treatment planning image. The second set of patient position movement vectors may reflect the distance and / or direction that each voxel of the acquired image must be translated to improve the alignment between the second patient target region of the acquired image and the second patient target region of the treatment planning image. In some embodiments, the second set of position movement vectors may be calculated based on the first set of patient position movement vectors such that the distance and / or direction information included in the second set of position movement vectors is relative to the first set of position movement vectors, rather than the initial coordinates of the voxels of the acquired image. Thus, the position and / or orientation instructions based on the second set of patient position movement vectors may include or correspond to instructions recording the modification to be made to the patient's position and / or orientation relative to the patient's first position and / or first orientation based on the first set of patient position movement vectors, such that the patient will be in a second position and / or orientation to irradiate the second treatment zone and / or patient target region.

[0288] The patient can be positioned according to a second set of patient position movement vectors such that the patient transitions from a first position to a second position. For example, the therapeutic radiation source can be deactivated such that a first patient target area is not irradiated by the therapeutic radiation source, and then the patient can be positioned according to the second set of patient position movement vectors. Positioning the patient according to the second set of patient position movement vectors can include moving a radiotherapy patient platform on which the patient is disposed relative to the therapeutic radiation source and / or adjusting a rotational position of the radiation source according to the second set of patient position movement vectors. The therapeutic radiation source can then be activated such that the second patient target area is irradiated. In some embodiments, for beam station-based delivery, during an irradiation cycle, the patient can be positioned according to a first set of patient position movement vectors at a first position associated with a first beam station, and the patient can be positioned according to a second set of patient position movement vectors during a transition of the patient platform between a first position associated with the first beam station and a second position associated with a second beam station (e.g., a second beam station adjacent to the first beam station).

[0289] In some embodiments, not only the first patient target area and the second patient target area are defined, the method may also include defining any suitable number of target areas, acquiring an image of each target area, and positioning the patient based on the patient movement vector based on the first patient target area and the second patient target area as described above. For example, for beam station-based delivery, the method may include defining multiple patient target areas, wherein each patient target area may span multiple beam stations. In some variations, there may be as many patient target areas as beam stations. An image of each patient target area may be acquired, and a set of position movement vectors associated with each defined patient target area may be generated as described above. Each patient target area and the associated set of position movement vectors may be associated with a particular beam station. During the transition of the patient and / or patient platform to a position associated with each respective beam station, the patient may be positioned based on a set of position movement vectors associated with the beam station. In some embodiments, the defined target areas (and the associated set of patient position movement vectors) may be associated with more than one beam station, so that the patient may be positioned based on a set of position movement vectors rather than being repositioned as the patient platform advances through a series of two or more beam stations. Thus, the number of defined target regions (and corresponding sets of associated patient position movement vectors) may be equal to or less than the number of beam stations.

[0290] Additionally, the second set of patient position movement vectors may include information regarding any tilt, pitch, yaw, and roll corrections that need to be implemented by moving the patient platform and / or by adjusting the roll of the gantry for radiation source coupling (e.g., correcting the gantry transmit position) such that the alignment of the second patient target region with the position of the second patient target region in the second treatment planning image is improved.

[0291] In some embodiments, similar to what is described above with respect to the first set of patient position movement vectors, multiple two-dimensional images of the second treatment volume and / or patient target region can be acquired along different orientations or planes (e.g., three or more orientations or planes), and the images can be compared with corresponding treatment planning images of the second patient target acquired along the same orientations or planes. In some embodiments, the multiple two-dimensional images of the second patient target region can be the same as the two-dimensional images acquired for the first patient target region used to calculate the first set of patient position movement vectors. The second set of patient position movement vectors can be calculated using changes relative to the position of the second patient target region along each image plane at each orientation. For example, the acquired images can include an acquired axial image, an acquired sagittal image, and an acquired coronal image of the second patient target region of the patient. When the patient lies in a supine position on a surface such as a patient platform or a treatment couch and the patient is oriented so that the patient will first encounter the head of the treatment radiation source, the acquired axial image may be taken along the patient's axial plane (e.g., a plane dividing the body into upper and lower parts), the acquired sagittal image may be taken along the patient's sagittal plane (e.g., a plane dividing the patient into left and right parts), and the acquired coronal image may be taken along the patient's coronal plane (e.g., a plane dividing the patient into abdomen and back). The axial plane is disposed perpendicularly to the sagittal plane, and the coronal plane is disposed perpendicularly to both the axial plane and the sagittal plane. The treatment planning images may include a treatment planning axial image, a treatment planning sagittal image, and a treatment planning coronal image of a second patient target area of ​​the patient. Therefore, the acquired axial image corresponds to the treatment planning axial image, the acquired sagittal image corresponds to the treatment planning sagittal image, and the acquired coronal image corresponds to the treatment planning coronal image.

[0292] The amount by which the patient position and / or orientation should be adjusted along or about each of the X-axis, Y-axis, and Z-axis (e.g., by moving the patient surface and / or rotating the radiation source) for treatment of the second patient target region can be reflected by a second set of patient position movement vectors based on the difference between the treatment planning image of the second patient target region and the corresponding acquired image of the second patient target region taken in each of the axial, sagittal, and coronal planes of the patient. In some embodiments, the X-axis of the patient surface can be parallel to the intersection of the sagittal and coronal planes of the patient and can be disposed in the sagittal plane. The Y-axis of the patient surface can be parallel to the intersection of the axial and coronal planes of the patient and can be disposed in the axial plane. The Z-axis of the patient surface can be parallel to the intersection of the sagittal and axial planes of the patient and can be disposed in the sagittal or axial planes of the patient. To determine the second set of patient position movement vectors, each acquired image of the second patient target region can be compared with the corresponding treatment planning image of the second patient target region taken in the same plane to determine a distance correction and / or a rotation correction of the patient in the same plane (e.g., by movement of the patient surface and / or rotation of the radiation source). One or more vectors in the second set of patient position movement vectors may indicate an amount and direction by which the patient surface will be moved (e.g., displaced and / or rotated) so that the second patient target region approximates the position of the second patient target region in the treatment planning image. One or more vectors in the second set of patient position movement vectors may also indicate an amount and direction by which the radiation source may be moved (e.g., rotated on a gantry) so that the position of the second patient target region approximates the position of the second patient target region in the treatment planning image. In some embodiments, the second set of patient position movement vectors may reflect up to six corrections (i.e., an amount of adjustment along or around each of the X-axis, Y-axis, and Z-axis of the patient platform). In some embodiments, a DICOM spatial registration object (SRO) may be used to determine each of the six corrections associated with the second set of patient position movement vectors (i.e., an amount of adjustment along or around each of the X-axis, Y-axis, and Z-axis of the patient platform).

[0293] In some embodiments, a second set of patient position movement vectors may be calculated by moving (e.g., by shifting and / or rotating) each acquired image relative to its respective treatment planning image to align or register the second patient target region of the treatment planning image with the second patient target region of the acquired image. Each acquired image may be moved a specific distance and / or rotated a specific amount to improve the registration of the second patient target region of the treatment planning image with the second patient target region of the acquired image. For example, an image acquired along an axial plane during treatment may be compared with a treatment planning image acquired along the patient's axial plane to determine the amount of correction required along the transverse axis (i.e., Y axis) and the vertical axis (i.e., Z axis) of a patient surface (e.g., a table or bed) in the axial plane, and the amount of correction required about the gantry roll axis (e.g., about the X axis). An image acquired along a sagittal plane during treatment may be compared with a treatment planning image acquired along the patient's sagittal plane to determine the amount of correction required along the longitudinal axis (i.e., X axis) and the vertical axis, and the amount of pitch correction (e.g., rotation about the Y axis) of the patient surface (e.g., a table or bed) in the sagittal plane. Images acquired along the coronal plane during treatment can be compared to treatment planning images acquired along the patient's coronal plane to determine the amount of correction required along the transverse and longitudinal axes and the amount of yaw correction (i.e., about the Z axis) of the patient surface (e.g., table or couch) in the coronal plane.

[0294] The second set of patient position movement vectors may reflect the amount of correction of the patient surface required along or about each of the X-axis, the Y-axis, and the Z-axis to improve the alignment between the second patient target region and the position of the second patient target region when the treatment planning image was acquired. Thus, in some embodiments, the second set of patient position movement vectors may include at least one patient position movement vector reflecting an adjustment along the X-axis of the patient surface based on a longitudinal difference determined from a comparison of the acquired sagittal image with the treatment planning sagittal image and / or a comparison of the acquired coronal image with the treatment planning coronal image. The second set of patient position movement vectors may include at least one patient position movement vector reflecting an adjustment along the Y-axis of the patient surface based on a transverse difference determined from a comparison of the acquired axial image with the treatment planning axial image and / or a comparison of the acquired coronal image with the treatment planning coronal image. The second set of patient position movement vectors may include at least one patient position movement vector reflecting an adjustment along the Z-axis of the patient surface based on a vertical difference determined from a comparison of the acquired axial image with the treatment planning axial image and / or a comparison of the acquired sagittal image with the treatment planning sagittal image.

[0295] With respect to rotation of the patient surface about the patient surface axis and / or rotation of the radiation source about the radiation source axis, the second set of patient position movement vectors may include a rotation correction of the patient surface about the patient surface Y axis based on a comparison of the acquired sagittal image with the treatment planning sagittal image, a rotation correction of the patient surface about the patient surface Z axis based on a comparison of the acquired coronal image with the treatment planning coronal image, and / or a rotation correction of the radiation source about the radiation source X axis (e.g., the X axis of the gantry coextensive with the X axis of the patient surface) based on a comparison of the acquired axial image with the treatment planning axial image. For example, moving or panning an acquired sagittal or coronal image to match a treatment planning sagittal or coronal image can be translated into a set of patient position movement vectors representing movement in the X, Y, and Z axes. Tilting an acquired sagittal or coronal image to match a treatment planning sagittal or coronal image can be translated into a set of patient position movement vectors representing pitch and / or roll position corrections. Thus, the amount by which the patient position or orientation should be adjusted along or about each of the X, Y, and Z axes can be reflected by a second set of patient position movement vectors based on the differences between the treatment planning image and the corresponding acquired images taken in each of the axial, sagittal, and coronal planes of the patient.

[0296] In some embodiments, the second set of patient position movement vectors may reflect an amount of correction of the patient surface along or about each of the X-axis, Y-axis, and Z-axis required relative to the position and / or orientation of the patient surface after movement according to the first set of patient position movement vectors to improve alignment between the second patient target region and the position of the second patient target region when the treatment planning image was acquired. Thus, in some embodiments, an amount by which the patient position or orientation should be adjusted along or about each of the X-axis, Y-axis, and Z-axis may be calculated by first determining a difference between a treatment planning image of the second patient target region and a corresponding acquired image of the second patient target region taken in each of the axial, sagittal, and coronal axes of the patient, and then taking into account the first set of patient position movement vectors (e.g., subtracting the first set of patient position movement vectors from the determined difference between the treatment planning image and the acquired image) such that the second set of position movement vectors are relative to the first set of patient position movement vectors. Thus, the surface on which the patient is located may transition from a position and / or orientation corresponding to the first set of patient position movement vectors to a position and / or orientation corresponding to the second set of patient position movement vectors without first returning to the position and / or orientation of the surface when the treatment planning image was initially acquired.

[0297] In some embodiments, rather than comparing the coordinate locations of specific voxels of an acquired image to a treatment planning image or comparing three two-dimensional acquired images to three corresponding two-dimensional treatment planning images, a first set of patient position motion vectors may be calculated by comparing an acquired three-dimensional image of a first patient target region to a three-dimensional treatment planning image of the first patient target region. A second set of patient position motion vectors may be calculated by comparing an acquired three-dimensional image of a second patient target region (which may be the same image or a different image than the acquired three-dimensional image of the first patient target region) to the three-dimensional treatment planning image of the second patient target region and taking into account the first set of patient position motion vectors (e.g., subtracting the first set of patient position motion vectors from an intermediate set of patient position motion vectors calculated by comparing the acquired image of the second patient target region to the treatment planning image of the second patient target region).

[0298] In some embodiments, the first and second sets of patient position movement vectors may be calculated prior to activating the therapeutic radiation source. In some embodiments, the first treatment planning image and the second treatment planning image are the same treatment planning image. In some embodiments, the first treatment planning image and the second treatment planning image are different treatment planning images.

[0299] In some embodiments, the first position difference and / or the second position difference may be calculated and used to determine whether the corresponding tumor or tumor portion of the patient has changed shape, size or position to the extent that the patient may not be positioned or oriented to effectively or accurately receive radiation using the existing treatment plan. For example, the first position difference may be calculated by comparing the coordinate position of a specific voxel in the first patient target region in the acquired image with the coordinate position of a corresponding voxel in the first patient target region in the treatment planning image. The distance between the position of the specific voxel in the first patient target region in the acquired image and the position of the corresponding voxel in the first patient target region in the treatment planning image may be the first position difference. Similarly, the second position difference may be calculated by comparing the coordinate position of a specific voxel in the second patient target region in the acquired image with the coordinate position of a corresponding voxel in the second target region in the treatment planning image. The distance between the position of the specific voxel in the second patient target region in the acquired image and the position of the corresponding voxel in the second patient target region in the treatment planning image may be the second position difference. In some embodiments, the first position difference may be calculated by comparing the coordinate position within a two-dimensional image of a cross section of the patient in the first patient target region in the acquired image with the coordinate position within a two-dimensional image of a cross section of the patient in the first patient target region in the treatment planning image. The second position difference can be calculated by comparing the coordinate position in the two-dimensional image of the cross section of the patient in the second patient target area in the acquired image with the coordinate position in the two-dimensional image of the cross section of the patient in the second patient target area in the treatment planning image. The first position difference and the second position difference can be based on the direction and / or distance information included in the first group of patient position movement vectors and the second group of patient position movement vectors as described above, respectively. In some embodiments, the second position difference can be calculated based on the direction and / or distance information included in the first group of patient position movement vectors and the second group of patient position movement vectors. In some embodiments, if the first position difference and / or the second position difference exceeds the position difference threshold, a notification can be generated and / or the radiotherapy session can be automatically suspended. For example, the maximum corrective movement of the patient platform for lateral, longitudinal and vertical correction is about 3cm, and the maximum corrective movement of rotation, pitch and roll correction does not exceed 3°. In some embodiments, the clinician or clinic can select the maximum corrective movement of the patient platform for lateral, longitudinal and vertical correction and the maximum corrective movement for rotation, pitch and roll correction. For example, the maximum corrective motion of the patient platform for lateral, longitudinal, and vertical corrections may be from about 1.5 cm to about 10 cm, and / or the maximum corrective motion for rotation, pitch, and roll corrections may be from about 2° to about 20°. Thus, the position difference threshold will be any position difference that results in a corrective motion that exceeds the maximum corrective motion of the patient platform in any respect.

[0300] The patient can be positioned in a first position according to a first set of patient position movement vectors, at (108). In some embodiments, the patient can be positioned by moving a radiotherapy patient platform on which the patient is positioned relative to a therapeutic radiation source according to the first set of patient position movement vectors. For example, the platform can be tilted in any direction prior to irradiation, which can include translation of the platform relative to the therapeutic radiation source in an inclined orientation. In some embodiments, the radiotherapy patient platform on which the patient is positioned can be moved along or around an X-axis, Y-axis, and / or Z-axis (e.g., around a yaw, pitch, and / or roll axis) of the radiotherapy patient platform. Additionally, in some embodiments, the yaw and / or pitch of the radiotherapy patient platform can be adjusted. In some embodiments, the radiotherapy patient platform on which the patient is positioned can be moved along an X-axis, Y-axis, and / or Z-axis of the radiotherapy patient platform and around a yaw axis and / or a pitch axis, while the radiation source can be moved around a roll axis (e.g., by movement of a gantry). As another example, transitioning the patient from a first position to a second position can include moving and / or bending a portion of the patient, such as a head, a knee, or an elbow, on the platform. The therapeutic radiation source can then be activated so that the first patient target area is irradiated.

[0301] In some embodiments, a roll correction for the patient position (e.g., as defined by the first set of patient position movement vectors) can be achieved by rotating the radiation source (e.g., by rotating the gantry) in the opposite direction of the calculated roll correction. For example, if the roll correction for the patient position is 3° clockwise, the position of the radiation source can be adjusted to provide radiation from a gantry position (e.g., a gantry firing position) that is -3° counterclockwise relative to each requested radiation source delivery position. Thus, if the treatment plan includes delivering radiation from the radiation source with a gantry at 0° based on the treatment planning images, and the roll correction is 3° based on the difference between the treatment planning images and the acquired images, the radiation source can be adjusted 3° counterclockwise and deliver radiation (e.g., radiation) from 357° instead of 0°.

[0302] The patient may then be positioned according to the second set of patient position movement vectors such that the patient transitions from the first position to the second position at 110. Similar to the above, positioning the patient according to the second set of patient position movement vectors may include moving a radiation therapy patient platform on which the patient is positioned relative to the therapeutic radiation source and / or adjusting a rotational position of the radiation source according to the second set of patient position movement vectors. The therapeutic radiation source may then be activated such that a second patient target area is irradiated.

[0303] In some embodiments, the method may include defining not only a first patient target region and a second patient target region, but also any suitable number of target regions, acquiring an image of each target region, and positioning the patient based on a position movement vector based on the first patient target region and the second patient target region as described above.

[0304] Fig. 11B is a flowchart representation of a variation of a method (200) for patient setup. The method (200) includes acquiring (202) images of one or more patient target regions at the beginning of a radiation treatment session. In some embodiments, for example, a CT system may be used to acquire the one or more images prior to or at the beginning of a treatment session. In some embodiments, the CT system may be attached to the same gantry as a radiation source intended to deliver radiation treatment during the treatment session. In some embodiments, the CT system may be attached to a gantry different from the gantry supporting the radiation source. One or more treatment zones may be defined (204) based on the position and / or location of the one or more patient target regions in the acquired images and the position and / or location of the one or more patient target regions in the treatment planning images. For example, the acquired images and / or treatment planning images may be divided into a first treatment zone and a second treatment zone. Each treatment zone may include one or more patient target regions such that the one or more patient target regions in the acquired images may be compared to one or more corresponding patient target regions in the treatment planning images. Each treatment zone may correspond to a portion of a patient within which the one or more patient target regions are located, which portion is to be irradiated when the patient is positioned according to a particular setup during a particular portion of the radiation treatment session. A treatment zone may be mapped to a series of patient platform positions or stages (e.g., beam stations) and / or a series of patient platform movements along its longitudinal axis where one or more target areas in the treatment zone intersect with a radiation beam from a therapeutic radiation source. A treatment zone may correspond to a particular patient position and / or platform orientation. For example, a first treatment zone may be associated with a first patient position and orientation for irradiating a first patient target area within the first treatment zone, and a second treatment zone may be associated with a second patient position and orientation for irradiating a second patient target area within the second treatment zone. Thus, in some embodiments, a first treatment zone may be associated with a first portion of a radiation treatment session (e.g., movement of the patient platform through a first set of beam stations), a first patient target area, and a first position of the patient, and a second treatment zone may be associated with a second portion of a radiation treatment session (e.g., movement of the patient platform through a second set of beam stations), a second patient target area, and a second position of the patient.

[0305] A set of patient position movement vectors may be calculated (206) for each treatment zone based on the position and / or location difference between the patient target region in the acquired image and the patient target region in the treatment planning image. The position of the patient target region in the acquired image may be compared to the position of the patient target region in the treatment planning image in 2D and / or 3D. In embodiments where two treatment zones have been defined, a first set of patient position movement vectors may be calculated for the first treatment zone and a second set of patient position movement vectors may be calculated for the second treatment zone. Each set of position movement vectors may include a distance and / or directional translation. In some embodiments, the directional translation may include a tilt angle. In some embodiments, the first set of patient position movement vectors may be calculated by moving the acquired image relative to the treatment planning image to align or register the first patient target region of the treatment planning image with the first patient target region of the acquired image. For example, in some embodiments, the first patient target region may be divided into sub-regions (e.g., sub-volumes) that may be represented by voxels, and the coordinates of each voxel of the first patient target region of the acquired image may be compared to the coordinates of the corresponding voxel of the first patient target region in the treatment planning image. For example, each voxel of the acquired image may be translated along or around the X, Y, and / or Z axis, maintaining the relative position of each coordinate of each voxel of the acquired image to each other during the movement of the acquired image, until the acquired image and the treatment planning image have improved alignment with respect to the first patient target region (e.g., the overlap between the first patient target region in the image is increased or optimized). A first set of patient position movement vectors may then be calculated based on the position and / or location differences between the acquired image before and after being moved to increase alignment with the treatment planning image. The first set of patient position movement vectors may reflect the distance and / or direction that each voxel of the acquired image must be translated to improve the alignment between the first patient target region of the acquired image and the first patient target region of the treatment planning image. In addition, the first set of patient position movement vectors may include or correspond to instructions associated with a first position and / or first orientation of the patient (e.g., a first position and / or first orientation of a surface on which the patient is placed) such that the first patient target region of the patient is located close to the position where the first patient target region was located when the treatment planning image was acquired. This may facilitate delivery of therapeutic radiation to the patient target region that is closer to the treatment plan. Additionally, the first set of patient position movement vectors may include information regarding any tilt, pitch, yaw and / or roll corrections that need to be achieved by positioning the patient platform so that the position of the first patient target area approximates the position of the first patient target area in the first treatment planning image.

[0306] In some embodiments, the acquired image of the first patient target area and the treatment planning image of the first patient target area can each be a two-dimensional image. The two-dimensional acquired image can be compared with the two-dimensional treatment planning image to calculate a first set of patient position movement vectors. In some embodiments, multiple two-dimensional images of the first patient target area can be acquired along different orientations or planes (e.g., three or more orientations or planes), and the images can be compared with corresponding treatment planning images of the first patient target area acquired along the same orientation or plane. The first set of patient position movement vectors can be calculated using changes in the position of the first patient target area along each image plane at each orientation. For example, the acquired images can include an acquired axial image, an acquired sagittal image, and an acquired coronal image of the first patient target area of ​​the patient. When the patient lies in a supine position on a surface such as a patient platform or a treatment couch and the patient is oriented so that the patient will first encounter the head of the treatment radiation source, the acquired axial image may be taken along the patient's axial plane (e.g., a plane dividing the body into upper and lower parts), the acquired sagittal image may be taken along the patient's sagittal plane (e.g., a plane dividing the patient into left and right parts), and the acquired coronal image may be taken along the patient's coronal plane (e.g., a plane dividing the patient into abdomen and back). The axial plane is disposed perpendicular to the sagittal plane, and the coronal plane is disposed perpendicular to both the axial plane and the sagittal plane. The treatment planning images may include a treatment planning axial image, a treatment planning sagittal image, and a treatment planning coronal image of a first patient target area of ​​the patient. Therefore, the acquired axial image corresponds to the treatment planning axial image, the acquired sagittal image corresponds to the treatment planning sagittal image, and the acquired coronal image corresponds to the treatment planning coronal image.

[0307] The amount by which the patient position and / or orientation should be adjusted along or about each of the X-axis, Y-axis, and Z-axis (e.g., by moving the patient surface and / or rotating the radiation source) for treatment of the first patient target region can be reflected by a first set of patient position movement vectors based on the difference between the treatment planning image and the corresponding acquired image taken in each of the axial, sagittal, and coronal planes of the patient. In some embodiments, the X-axis of the patient surface can be parallel to the intersection of the sagittal and coronal planes of the patient and can be disposed in the sagittal plane. The Y-axis of the patient surface can be parallel to the intersection of the axial and coronal planes of the patient and can be disposed in the axial plane. The Z-axis of the patient surface can be parallel to the intersection of the sagittal and axial planes of the patient and can be disposed in the sagittal or axial planes of the patient. To determine the first set of patient position movement vectors, each acquired image of the first patient target region can be compared with a corresponding treatment planning image of the first patient target region taken in the same plane to determine a distance correction and / or a rotation correction of the patient in the same plane (e.g., by movement of the patient surface and / or rotation of the radiation source). One or more vectors in the first set of patient position movement vectors may indicate an amount and direction by which the patient surface will be moved (e.g., displaced and / or rotated) so that the first patient target region approximates the position of the first patient target region in the treatment planning image. One or more vectors in the first set of patient position movement vectors may also indicate an amount and direction by which the radiation source may be moved (e.g., rotated on a gantry) so that the position of the first patient target region approximates the position of the first patient target region in the treatment planning image. In some embodiments, the first set of patient position movement vectors may reflect up to six corrections (i.e., an amount of adjustment along or around each of the X-axis, Y-axis, and Z-axis of the patient platform). In some embodiments, a DICOM spatial registration object (SRO) may be used to determine each of the six corrections associated with the first set of patient position movement vectors (i.e., an amount of adjustment along or around each of the X-axis, Y-axis, and Z-axis of the patient platform).

[0308] In some embodiments, the first set of patient position movement vectors can be calculated by moving (e.g., by shifting and / or rotating) each acquired image relative to its respective treatment planning image to align or register the first patient target region of the treatment planning image with the first patient target region of the acquired image. Each acquired image can be moved a specific distance and / or rotated a specific amount to improve the registration of the first patient target region of the treatment planning image with the first patient target region of the acquired image. For example, an image acquired along an axial plane during treatment can be compared with a treatment planning image acquired along the patient's axial plane to determine the amount of correction required along the transverse axis (i.e., Y axis) and the vertical axis (i.e., Z axis) of the patient surface (e.g., table or bed) in the axial plane and the amount of correction required about the gantry roll axis (e.g., about the X axis). An image acquired along a sagittal plane during treatment can be compared with a treatment planning image acquired along the patient's sagittal plane to determine the amount of correction required along the longitudinal axis (i.e., X axis) and the vertical axis, and the amount of pitch correction (e.g., rotation about the Y axis) of the patient surface (e.g., table or bed) in the sagittal plane. Images acquired along the coronal plane during treatment can be compared to treatment planning images acquired along the patient's coronal plane to determine the amount of correction required along the transverse and longitudinal axes and the amount of yaw correction (i.e., about the Z axis) of the patient surface (e.g., table or couch) in the coronal plane.

[0309] The first set of patient position movement vectors may reflect an amount of correction of the patient surface required along or about each of the X-axis, the Y-axis, and the Z-axis to improve the alignment between the first patient target region and the position of the first patient target region when the treatment planning image was acquired. Thus, in some embodiments, the first set of patient position movement vectors may include at least one patient position movement vector reflecting an adjustment along the X-axis of the patient surface based on a longitudinal difference determined from a comparison of an acquired sagittal image with a treatment planning sagittal image and / or a comparison of an acquired coronal image with a treatment planning coronal image. The first set of patient position movement vectors may include at least one patient position movement vector reflecting an adjustment along the Y-axis of the patient surface based on a transverse difference determined from a comparison of an acquired axial image with a treatment planning axial image and / or a comparison of an acquired coronal image with a treatment planning coronal image. The first set of patient position movement vectors may include at least one patient position movement vector reflecting an adjustment along the Z-axis of the patient surface based on a vertical difference determined from a comparison of an acquired axial image with a treatment planning axial image and / or a comparison of an acquired sagittal image with a treatment planning sagittal image.

[0310] With respect to rotation of the patient surface about the patient surface axis and / or rotation of the radiation source about the radiation source axis, the first set of patient position movement vectors may include a rotation correction of the patient surface about the patient surface Y axis based on a comparison of the acquired sagittal image with the treatment planning sagittal image, a rotation correction of the patient surface about the patient surface Z axis based on a comparison of the acquired coronal image with the treatment planning coronal image, and / or a rotation correction of the radiation source about the radiation source X axis (e.g., the X axis of the gantry coextensive with the X axis of the patient surface) based on a comparison of the acquired axial image with the treatment planning axial image. For example, moving or panning an acquired sagittal or coronal image to match a treatment planning sagittal or coronal image can be translated into a set of patient position movement vectors representing movement in the X, Y, and Z axes. Tilting an acquired sagittal or coronal image to match a treatment planning sagittal or coronal image can be translated into a set of patient position movement vectors representing pitch and / or roll position corrections. Thus, the amount by which the patient position or orientation should be adjusted along or about each of the X, Y, and Z axes can be reflected by a first set of patient position movement vectors based on the differences between the treatment planning image and the corresponding acquired images taken in each of the axial, sagittal, and coronal planes of the patient.

[0311] In some embodiments, similar to what is described above with respect to the first set of patient position movement vectors, a second set of patient position movement vectors may be calculated by moving the acquired image relative to the treatment planning image to align the second patient target region of the treatment planning image with the second patient target region of the acquired image. For example, in some embodiments, the second patient target region may be divided into sub-regions (e.g., sub-volumes) that may be represented by voxels, and the coordinates of each voxel of the second patient target region of the acquired image may be compared with the coordinates of the corresponding voxel of the second patient target region in the treatment planning image. For example, each voxel of the acquired image may be translated along or around the X, Y, and / or Z axis, maintaining the relative position of each voxel of the acquired image to each other during the movement of the acquired image until the acquired image and the treatment planning image have improved alignment relative to the second patient target region (e.g., the overlap between the second patient target region in the image is increased or optimized). The second set of patient position movement vectors may then be calculated based on the difference in position and / or location between the acquired image before and after being moved to increase alignment with the treatment planning image. The second set of patient position movement vectors may reflect the distance and / or direction that each voxel of the acquired image must be translated to improve the alignment between the second patient target region of the acquired image and the second patient target region of the treatment planning image. In some embodiments, the second set of position movement vectors may be calculated based on the first set of patient position movement vectors such that the distance and / or direction information included in the second set of position movement vectors is relative to the first set of patient position movement vectors, rather than the initial coordinates of the voxels of the acquired image. Thus, the position and / or orientation instructions based on the second set of patient position movement vectors may include or correspond to instructions recording the modification to be made to the position and / or orientation of the patient relative to the first position and / or first orientation of the patient based on the first set of patient position movement vectors, such that the patient will be in the second position and / or orientation to irradiate the second patient target region. Additionally, the second set of patient position movement vectors may include information about any tilt, pitch, yaw, and roll corrections that need to be implemented by moving the patient platform and / or by adjusting the roll of the gantry for radiation source coupling (e.g., correcting the gantry launch position) so that the alignment of the second patient target region with the position of the first patient target region in the first treatment planning image is improved.

[0312] In some embodiments, similar to what is described above with respect to the first set of patient position movement vectors, multiple two-dimensional images of the second patient target region may be acquired along different orientations or planes (e.g., three or more orientations or planes), and the images may be compared with corresponding treatment planning images of the second patient target acquired along the same orientations or planes. In some embodiments, the multiple two-dimensional images of the second patient target region may be the same as the two-dimensional images acquired for the first patient target region used to calculate the first set of patient position movement vectors. The second set of patient position movement vectors may be calculated using changes relative to the position of the second patient target region along each image plane at each orientation. For example, the acquired images may include an acquired axial image, an acquired sagittal image, and an acquired coronal image of the second patient target region of the patient. When the patient lies in a supine position on a surface such as a patient platform or a treatment couch and the patient is oriented so that the patient will first encounter the head of the treatment radiation source, the acquired axial image may be taken along the patient's axial plane (e.g., a plane dividing the body into upper and lower parts), the acquired sagittal image may be taken along the patient's sagittal plane (e.g., a plane dividing the patient into left and right parts), and the acquired coronal image may be taken along the patient's coronal plane (e.g., a plane dividing the patient into abdomen and back). The axial plane is disposed perpendicularly to the sagittal plane, and the coronal plane is disposed perpendicularly to both the axial plane and the sagittal plane. The treatment planning images may include a treatment planning axial image, a treatment planning sagittal image, and a treatment planning coronal image of a second patient target area of ​​the patient. Therefore, the acquired axial image corresponds to the treatment planning axial image, the acquired sagittal image corresponds to the treatment planning sagittal image, and the acquired coronal image corresponds to the treatment planning coronal image.

[0313] The amount by which the patient position and / or orientation should be adjusted along or about each of the X-axis, Y-axis, and Z-axis (e.g., by moving the patient surface and / or rotating the radiation source) for treatment of the second patient target region can be reflected by a second set of patient position movement vectors based on the difference between the treatment planning image of the second patient target region and the corresponding acquired image of the second patient target region taken in each of the axial, sagittal, and coronal planes of the patient. In some embodiments, the X-axis of the patient surface can be parallel to the intersection of the sagittal and coronal planes of the patient and can be disposed in the sagittal plane. The Y-axis of the patient surface can be parallel to the intersection of the axial and coronal planes of the patient and can be disposed in the axial plane. The Z-axis of the patient surface can be parallel to the intersection of the sagittal and axial planes of the patient and can be disposed in the sagittal or axial planes of the patient. To determine the second set of patient position movement vectors, each acquired image of the second patient target region can be compared with the corresponding treatment planning image of the second patient target region taken in the same plane to determine a distance correction and / or a rotation correction of the patient in the same plane (e.g., by movement of the patient surface and / or rotation of the radiation source). One or more vectors in the second set of patient position movement vectors may indicate an amount and direction by which the patient surface will be moved (e.g., displaced and / or rotated) so that the second patient target region approximates the position of the second patient target region in the treatment planning image. One or more vectors in the second set of patient position movement vectors may also indicate an amount and direction by which the radiation source may be moved (e.g., rotated on a gantry) so that the position of the second patient target region approximates the position of the second patient target region in the treatment planning image. In some embodiments, the second set of patient position movement vectors may reflect up to six corrections (i.e., an amount of adjustment along or around each of the X-axis, Y-axis, and Z-axis of the patient platform). In some embodiments, a DICOM spatial registration object (SRO) may be used to determine each of the six corrections associated with the second set of patient position movement vectors (i.e., an amount of adjustment along or around each of the X-axis, Y-axis, and Z-axis of the patient platform).

[0314] In some embodiments, the calculation may be performed by moving (e.g., by shifting and / or rotating) each acquired image relative to its respective treatment planning image to align or register the second patient target region of the treatment planning image with the second patient target region of the acquired image. Each acquired image may be moved a specific distance and / or rotated a specific amount to improve the registration of the second patient target region of the treatment planning image with the second patient target region of the acquired image. For example, an image acquired along an axial plane during treatment may be compared with a treatment planning image acquired along the patient's axial plane to determine the amount of correction required along the transverse axis (i.e., Y axis) and the vertical axis (i.e., Z axis) of the patient surface (e.g., a table or bed) in the axial plane and the amount of correction required about the gantry roll axis (e.g., about the X axis). An image acquired along a sagittal plane during treatment may be compared with a treatment planning image acquired along the patient's sagittal plane to determine the amount of correction required along the longitudinal axis (i.e., X axis) and the vertical axis, and the amount of pitch correction (e.g., rotation about the Y axis) of the patient surface (e.g., a table or bed) in the sagittal plane. Images acquired along the coronal plane during treatment can be compared to treatment planning images acquired along the patient's coronal plane to determine the amount of correction required along the transverse and longitudinal axes and the amount of yaw correction (i.e., about the Z axis) of the patient surface (e.g., table or couch) in the coronal plane.

[0315] The second set of patient position movement vectors may reflect the amount of correction of the patient surface required along or about each of the X-axis, the Y-axis, and the Z-axis to improve the alignment between the second patient target region and the position of the second patient target region when the treatment planning image was acquired. Thus, in some embodiments, the second set of patient position movement vectors may include at least one patient position movement vector reflecting an adjustment along the X-axis of the patient surface based on a longitudinal difference determined from a comparison of the acquired sagittal image with the treatment planning sagittal image and / or a comparison of the acquired coronal image with the treatment planning coronal image. The second set of patient position movement vectors may include at least one patient position movement vector reflecting an adjustment along the Y-axis of the patient surface based on a transverse difference determined from a comparison of the acquired axial image with the treatment planning axial image and / or a comparison of the acquired coronal image with the treatment planning coronal image. The second set of patient position movement vectors may include at least one patient position movement vector reflecting an adjustment along the Z-axis of the patient surface based on a vertical difference determined from a comparison of the acquired axial image with the treatment planning axial image and / or a comparison of the acquired sagittal image with the treatment planning sagittal image.

[0316] With respect to rotation of the patient surface about the patient surface axis and / or rotation of the radiation source about the radiation source axis, the second set of patient position movement vectors may include a rotation correction of the patient surface about the patient surface Y axis based on a comparison of the acquired sagittal image with the treatment planning sagittal image, a rotation correction of the patient surface about the patient surface Z axis based on a comparison of the acquired coronal image with the treatment planning coronal image, and / or a rotation correction of the radiation source about the radiation source X axis (e.g., the X axis of the gantry coextensive with the X axis of the patient surface) based on a comparison of the acquired axial image with the treatment planning axial image. For example, moving or panning an acquired sagittal or coronal image to match a treatment planning sagittal or coronal image can be translated into a set of patient position movement vectors representing movement in the X, Y, and Z axes. Tilting an acquired sagittal or coronal image to match a treatment planning sagittal or coronal image can be translated into a set of patient position movement vectors representing pitch and / or roll position corrections. Thus, the amount by which the patient position or orientation should be adjusted along or about each of the X, Y, and Z axes can be reflected by a second set of patient position movement vectors based on the differences between the treatment planning image and the corresponding acquired images taken in each of the axial, sagittal, and coronal planes of the patient.

[0317] In some embodiments, the second set of patient position movement vectors may reflect an amount of correction of the patient surface along or about each of the X-axis, Y-axis, and Z-axis required relative to the position and / or orientation of the patient surface after movement according to the first set of patient position movement vectors to improve alignment between the second patient target region and the position of the second patient target region when the treatment planning image was acquired. Thus, in some embodiments, an amount by which the patient position or orientation should be adjusted along or about each of the X-axis, Y-axis, and Z-axis may be calculated by first determining a difference between a treatment planning image of the second patient target region and a corresponding acquired image of the second patient target region taken in each of the axial, sagittal, and coronal axes of the patient, and then taking into account the first set of patient position movement vectors (e.g., subtracting the first set of patient position movement vectors from the determined difference between the treatment planning image and the acquired image) such that the second set of position movement vectors are relative to the first set of patient position movement vectors. Thus, the surface on which the patient is located may transition from a position and / or orientation corresponding to the first set of patient position movement vectors to a position and / or orientation corresponding to the second set of patient position movement vectors without first returning to the position and / or orientation of the surface when the treatment planning image was initially acquired.

[0318] In some embodiments, rather than comparing the coordinate locations of specific voxels of an acquired image to a treatment planning image or comparing three two-dimensional acquired images to three corresponding two-dimensional treatment planning imag...

Claims

1. A system for virtual target area positioning and radiation delivery, the system comprising: A controller configured to: acquiring an image of the patient in a treatment position and identifying a target region of the patient in the acquired image; selecting a positioning reference point in the acquired image, wherein the positioning reference point corresponds to a planned positioning reference point; calculating a fluence for delivery to a target region of the patient at each firing position of a therapeutic radiation source by calculating a localization function based on the localization reference points and applying the localization function to a translationally invariant transmit filter derived based on the planning localization reference points; and The therapeutic radiation source is used to emit a delivery radiation flux to the target area of ​​the patient. 2 . The system of claim 1 , wherein applying the positioning function to the shift-invariant transmit filter comprises convolving the positioning function with the shift-invariant transmit filter.

3. The system of claim 2, wherein the positioning function is one of a delta function, a Gaussian function, a circular function, and an interpolation. The system of claim 3 , wherein the Gaussian function is a truncated Gaussian function.

5. The system of claim 3, wherein the interpolation is one of linear, bicubic, spline, or Fourier shift.

6. The system of claim 1, wherein the acquired images include one or more of a positron emission tomography (PET) image, an X-ray projection image, a computed tomography (CT) image, and a magnetic resonance imaging (MRI) image.

7. The system of claim 1, wherein the controller is further configured to: identifying a second patient target region in the acquired image; selecting a second positioning reference point for the second patient target area within the acquired image, wherein the second positioning reference point corresponds to a second planned positioning reference point; calculating a second delivered fluence at each transmit position of the therapeutic radiation source by calculating a second localization function based on the second localization reference point and applying the second localization function to a second translation-invariant transmit filter based on the second planning localization reference point; and The second delivered fluence is emitted to the second patient target region using the therapeutic radiation source.

8. The system of claim 2, wherein the controller is further configured to: identifying a second patient target region in the acquired image; selecting a second positioning reference point for the second patient target area within the acquired image, wherein the second positioning reference point corresponds to a second planned positioning reference point; calculating a second delivered fluence at each transmit position of the therapeutic radiation source by calculating a second delta function based on the second positioning reference point and convolving the second delta function with a second shift-invariant transmit filter based on the second planning positioning reference point; and The second delivered fluence is emitted to the second patient target region using the therapeutic radiation source.

9. The system of any one of claims 7 or 8, wherein emitting the first delivery fluence to the first patient target area and emitting the second delivery fluence to the second patient target area occur simultaneously.

10. The system of any one of claims 7 or 8, wherein emitting a first delivery fluence to a first patient target area and emitting the second delivery fluence to the second patient target area occur sequentially.

11. The system of claim 8, wherein the localization function is a first localization function (δ), wherein the first translation-invariant transmit filter comprises a first set of fluence map filters (p1, p2, ..., p2) calculated during treatment planning for each transmit position (i) of the therapeutic radiation source. i ), and the controller is further configured to perform the following operations: calculate a first set of projections (δ i ), d i =proj i (d) Each projection (δ i ) is the 2-D fluence distribution, wherein calculating a first delivered fluence comprises dividing the first set of projections (δ i ) and the corresponding fluence map filter (p i ) is convolved to calculate a first delivered fluence map (f i ), f i =p i *d i and wherein delivering the first delivery fluence comprises moving the therapeutic radiation source to each emission position (i) and delivering the therapeutic radiation source according to the first delivery fluence map (f i ) transmits radiation to a first patient target area.

12. The system according to claim 11, wherein each projection (δ i ) is an m x n matrix, where m is the number of multileaf collimator leaves and n is the number chosen during treatment planning.

13. The system of claim 12, wherein n is the number of beam stations selected during the treatment planning.

14. The system of claim 11, wherein the first positioning function is one of a delta function, a Gaussian function, a circular function, and an interpolation.

15. The system of claim 14, wherein the Gaussian function is a truncated Gaussian function.

16. The system of claim 14, wherein the interpolation is one of linear, bicubic, spline, and Fourier shift.

17. The system according to claim 11, wherein each projection (δ_2 i ) is an m×n matrix.

18. The system of claim 17, wherein m is the number of multileaf collimator leaves and n is a number selected during treatment planning.

19. The system of claim 18, wherein n is the number of beam stations selected during the treatment planning.

20. The system of claim 7, wherein the second positioning function is one of a delta function, a Gaussian function, a circular function, and an interpolation.

21. The system of claim 20, wherein the Gaussian function is a truncated Gaussian function.

22. The system of claim 20, wherein the interpolation is one of linear, bicubic, spline, and Fourier shift.

23. The system of any one of claims 11-16, wherein delivering the calculated fluence comprises transferring the delivered fluence map (f i ,f_2 i ) into multiple radiation therapy system machine instructions for each transmission position.

24. The system of any one of claims 1 or 2, wherein delivering a calculated fluence comprises splitting the calculated fluence into a plurality of radiation therapy system machine instructions for each shot position.

25. The system of any one of claims 7 or 8, wherein delivering the second calculated fluence comprises splitting the second calculated fluence into a plurality of radiation therapy system machine instructions for each shot location.

26. The system of claim 25, wherein the plurality of radiotherapy system machine instructions include one or more multi-leaf collimator configurations for each emission position, and wherein emitting a radiation fluence further comprises moving leaves of a multi-leaf collimator to the multi-leaf collimator configuration corresponding to the emission position location of the therapeutic radiation source and emitting a radiation pulse.

27. The system of claim 26, wherein the plurality of radiation therapy system machine instructions further include therapeutic radiation source emission parameters for each emission location.

28. The system of claim 27, wherein: The therapeutic radiation source emission parameters include therapeutic radiation source pulse parameters, and emitting the radiation pulse includes emitting radiation having the therapeutic radiation source pulse parameters, the therapeutic radiation source pulse parameters corresponding to the emission location of the therapeutic radiation source.

29. The system of claim 1, wherein the positioning reference point is a user-selected location within the acquired image.

30. The system of claim 1, wherein the positioning reference point corresponds to a treatment plan isocenter defined relative to the patient target region during treatment planning.

31. The system of claim 7, wherein the first patient target region is in a first treatment volume of the patient defined during treatment planning, and the second target region is in a second treatment volume of the patient defined during treatment planning.

32. The system of claim 31 , wherein the first treatment zone has an axial length of 8 cm or less and comprises a first set of axial planes, and the second treatment zone has an axial length of 8 cm or less and does not overlap with the first treatment zone, wherein the second treatment zone comprises a second set of axial planes.

33. The system of claim 32, wherein the center of the first treatment volume and the center of the second treatment volume are co-linear along and / or co-planar with the IEC-Y axis.

34. The system of claim 31 , wherein the first treatment volume and the second treatment volume overlap.

35. The system of claim 1, wherein the emission position of the therapeutic radiation source comprises a position of the therapeutic radiation source relative to a patient table position.

36. The system of claim 35, wherein the therapeutic radiation source is mounted on a gantry that is rotatable about a longitudinal axis, and the position of the therapeutic radiation source is specified by a gantry angle about the longitudinal axis.

37. The system of claim 36, wherein the patient platform is movable to different positions along the longitudinal axis.

38. A system for virtual target area positioning and radiation delivery, the system comprising: A controller configured to: acquiring an image of the patient in a treatment position and identifying a target region of the patient in the acquired image; selecting a positioning reference point in the acquired image, wherein the positioning reference point corresponds to a planned positioning reference point; Calculate a spatial offset based on movement between the positioning reference point and the planned positioning reference point; moving a bound of a planned region of interest based on the spatial offset, wherein the bound of the planned region of interest surrounds the patient target region; acquiring imaging data that has been spatially filtered by the moved region of interest; calculating a fluence for delivery to a target region of the patient at each emission position of a therapeutic radiation source by convolving a set of emission filters with the acquired imaging data; and The therapeutic radiation source is used to transmit a calculated fluence to the patient target area.

39. The system of claim 38, wherein the boundaries of the planned region of interest include a spatial filter.

40. The system of claim 38, wherein moving the bounds of the planned region of interest comprises moving the bounds of the planned region of interest by a rolling correction factor applying a rotation and a translation to the planned region of interest, the roll correction factor representing a rotational translation of the positioning reference point relative to the planned positioning reference point, and wherein calculating the fluence for delivery comprises combining the set of transmit filters with the roll correction factor Circular convolution.

Images