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

Abstract

To provide multi-target treatment planning and delivery and virtual localization for radiation therapy.SOLUTION: Disclosed herein are methods for patient setup and patient target region localization for the irradiation of multiple patient target regions in a single treatment session. Virtual localization is a method that can be used to register a patient target region without requiring that the patient is physically moved using the patient platform. Instead, the planned fluence is updated to reflect the current location of the patient target region by: selecting a localization reference in the localization image; calculating a localization function based on the localization reference point; and calculating the delivery fluence by convolving the localization function with a shift-invariant firing filter. Mosaic multi-target localization partitions a planned fluence map for multiple patient target regions into sub-regions that can be individually localized.SELECTED DRAWING: Figure 36B

Description

[Background technology]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims priority to U.S. Provisional Patent Application No. 62 / 873,742, filed July 12, 2019, which is incorporated herein by reference in its entirety.

[0002] (Background technology) Radiation therapy involves acquiring planning images of a 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 identifying the tumor region to be irradiated, radiation therapy also seeks to limit irradiation to healthy tissue. This may include identifying radiation sensitive or radiation avoidance regions (e.g., organs at risk or OARs) and designing a treatment plan that does not irradiate these radiation avoidance regions beyond what is prescribed. In most cases, the treatment plan will match (or nearly match) the absolute and / or relative positions of one or more tumor regions, OARs, and healthy tissue regions at the time of treatment to their absolute and / or relative positions at the time the planning images were acquired. Once a treatment plan has been designed that meets the dosimetric objectives of the tumor region and OARs, the patient may be positioned on a patient table or couch of the radiation therapy system so that the patient is reasonably comfortable on the couch and in a suitable position for radiation delivery. One or more registration images (e.g., fan beam CT scan, cone beam CT scan, and / or PET scan) of the patient on the couch may be acquired. The location of each of one or more tumor regions, OARs, and / or other anatomical structures may be determined using the registration image and their absolute positions relative to the therapeutic radiation source, and / or their relative positions relative to each other may be compared to their locations from the treatment planning image. If any of the tumor regions and / or OARs are displaced, the radiation therapy system may calculate how the patient should shift during treatment planning to match their location, and, if possible, adjust the couch to effect that shift.

[0003] However, patient setup and registration of tumor regions and / or OARs with respect to the coordinates of the radiation therapy system can be time-consuming, and in some cases may continue to change during a treatment session, especially since the size, shape, and / or location of the tumor region and / or OARs may change between the time of acquisition of the planning image and the treatment session. In addition, patient setup and registration are typically optimized for the treatment of a single target region and may not easily accommodate the treatment of multiple target regions. For example, one patient setup arrangement and registration may be suitable for one tumor region, but may not allow delivery of the prescribed dose for another tumor region and / or may result in unnecessary irradiation of the OARs. Accurately registering a patient to a plan designed to treat multiple targets simultaneously involves somehow mapping the new actual locations of the multiple targets on the patient at the time of delivery to the original locations of the multiple targets in the treatment plan. Since tumors may be displaced from one another, there may not be a single translational and orientational shift of the patient that can fit all tumors to the plan. That is, adjustments, shifts, and rotations of the patient that fit one tumor to its expected location in the plan may cause the remaining tumors to shift.

[0004] One approach to delivering radiation to multiple patient target regions involves performing a series of patent set-up and registration. For example, for a first patient target region, the couch may be adjusted to position the patient in a set-up position suitable for radiation delivery to the first target region, a registration image may be acquired to register the first target region, and radiation is then delivered to the first target region. These steps are then repeated for each target region, which can be time consuming (especially if the patient set-up involves opening the bunker door so that the clinician or technician can move on to adjusting the patient on the couch), and each iteration is processed separately, which may result in over-exposure to OARs and / or healthy tissue, and / or under-exposure to the target region (e.g., to avoid over-exposure to OARs). Thus, improvements in radiation treatment planning, patient set-up and registration, and registration methods are desirable, especially for the delivery of multiple target regions. Summary of the Invention [Problem to be solved by the invention]

[0005] Disclosed herein are methods for treatment planning, patient setup, registration, and radiation delivery for irradiation of multiple patient target areas in a single treatment session or fraction. [Means for solving the problem]

[0006] A method of treatment planning for irradiation of multiple target regions may include selecting a planned registration reference point for each target region and calculating a shift-invariant ejection filter for each target region based on the selected planned registration reference point. A treatment planning fluence map specifying radiation fluence delivered to the multiple target regions and radiation levels to OARs and healthy tissue may be calculated based on the shift-invariant ejection filter and the planned registration reference point for each target region.

[0007] Additionally or alternatively, the shift-invariant ejection filter may be expressed as a functional shift and orientation operator of the radiation fluence delivered to the multiple target regions based on the planned registration reference points of each target region. For example, the functional shift operator may include a function that interpolates the two-dimensional or three-dimensional map with a shift. The functional orientation operator may include a function that interpolates the two-dimensional or three-dimensional map using, for example, a rotation along an axis in two-dimensional or three-dimensional space. For example, the functional orientation operator may be used to interpolate (e.g., transform) the two-dimensional (or three-dimensional) fluence map for delivery based on the location of the registration reference points on the treatment day. This may include calculating the translation of the fluence map in (x,y) coordinates and / or scaling the fluence map in (x,y,z) and / or rotating the fluence map along axes in (θ,φ,ρ). In some variations, the treatment planning method may include defining a perimeter around each patient target region in the treatment planning fluence map that includes a region of low fluence values. A treatment planning method for multiple target regions may include calculating individual treatment plans including individual fluence maps for each target region, combining the individual fluence maps into a cumulative treatment planning fluence map, and iteratively modifying the cumulative treatment planning fluence map based on one or more constraints (e.g., dose constraints such as keeping high fluence regions separate from each other, meeting OAR fluence limits, meeting dose targets for each target region, etc.). After the cumulative treatment planning fluence map has been iteratively modified according to the desired constraints, the treatment planning method may include defining a perimeter around each patient target region in the treatment planning fluence map that includes regions of low fluence values, and may optionally include separating the iteratively modified cumulative treatment planning fluence map into individual fluence maps for each patient target region along the defined perimeter. In some variations, during optimization of the treatment plan, one or more of a functional shift operator and an orientation operator may be used to calculate a fluence map based on the planned localization reference point for each target region.

[0008] Optionally, in biologically guided radiation therapy (BgRT), where positron annihilation emission path data is acquired during a treatment session and used to calculate the delivered fluence, the treatment planning method may include defining a first region of interest (ROI) or radiation emission zone surrounding the first patient target region and a second ROI or radiation emission zone surrounding the second patient target region for a predetermined range of location displacements of the first and second patient target regions. The output of the treatment planning method described herein may include a treatment planning fluence map that defines the fluence delivered to each patient target region, as well as the level of radiation exposure of the OARs and healthy tissues, and a set of shift-invariant emission filters for each planned registration reference point associated with each patient target region. Alternatively or in addition, in treatment planning for BgRT, the treatment planning method may output a set of shift-invariant emission filters associated with a ROI (e.g., biological emission zone (BFZ)) defined around each patient target region. Additionally or alternatively, the set of shift-invariant injection filters may include a functional shift operator and / or an orientation operator. Optionally, the output of the treatment planning method may include a set of radiation therapy machine instructions for execution by the radiation therapy system after patient setup and patient target region registration.

[0009] In some variations, a method for localization and radiation delivery of a virtual target area may include acquiring images of a patient in a treatment position and identifying a patient target area in the acquired images, selecting a localization reference point in the acquired images, the reference point corresponding to a planned localization reference point, calculating a spatial offset based on a displacement between the localization reference point and the planned localization reference point, shifting a boundary of the planned region of interest based on the spatial offset, the boundary of the planned region of interest surrounding the patient target area, acquiring imaging data spatially filtered by the shifted region of interest, calculating a fluence to deliver to the patient target area at each injection position of a therapeutic radiation source by convolving a set of injection filters with the acquired imaging data, and emitting the calculated fluence to the patient target area using the therapeutic radiation source.

[0010] In some variations, the boundary of the planned region of interest may include a spatial filter. In some variations, shifting the boundary of the planned region of interest may include applying a rotation and shift to the planned region of interest by a roll correction factor φ that represents a rotational translation of the localization reference point relative to the planned localization reference point. Calculating the fluence for delivery may include circularly convolving the set of ejection filters with the roll correction factor φ.

[0011] In some variations, a method of treatment planning for radiation delivery to multiple patient target regions may include identifying a first location of a first patient target region and a second location of a second patient target region in a patient planning image, defining a first region of interest having a boundary surrounding the first patient target region, and defining a second region of interest having a boundary surrounding the second patient target region. The boundary of the second region of interest may be selected to surround the second patient target region for a predetermined range of location displacements of the first and second patient target regions. 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 of the first and second patient target regions that specifies a fluence to be delivered when the selected imaging data indicates that the first patient target region is within the boundary of the first region of interest and the second patient target region is within the boundary of the second region of interest.

[0012] In some variations, the first patient target region may be closer to the planning structure. In some variations, the first region of interest may be smaller than the second injection zone. In some variations, the planning structure may be an organ at risk (OAR). In some variations, the first patient target region may be closer to two or more planning structures than the second patient target region. In some variations, the method may further include designating a treatment planning reference point within the first region of interest as a registration reference point for positioning the patient at the start of the treatment session. In some variations, the selected imaging data may be used to guide radiation delivery during the treatment session. In some variations, the treatment planning reference point may be a center point of the first patient target region.

[0013] In some variations, the imaging data may include positron annihilation emission path data. In some variations, the positron annihilation emission path may be selected if the positron annihilation emission path intersects with at least one of the first and second emission zones. In some variations, the second region of interest may be formed to a size that includes a range of locations of the 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.

[0014] Also disclosed herein is a method for patient setup and patient target area registration for irradiation of multiple target tissue regions. The method for patient setup and target registration / registration may include positioning a patient on a patient table or couch of a radiation therapy system, acquiring one or more registration images of the patient including one or more target areas and / or OARs, and selecting a registration reference point in the one or more acquired registration images. The selected registration reference point may correspond to a planned registration reference point of the specific patient target area and may represent an updated location of the patient target area. A fluence map for delivery of the specific patient target area may be calculated by calculating a registration function based on the selected registration reference point and applying the registration function to a shift-invariant ejection filter derived based on the planned registration reference point. Alternatively or in addition, the shift-invariant ejection 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 3D discrete delta function) based on a selected localization reference point and convolving the delta function with a shift-invariant ejection filter derived based on the planned localization reference point and / or other planning parameters. In another example, a fluence map for delivery to a patient target region may be calculated by interpolating the fluence map with a shift or rotation based on the selected localization reference point. In this manner, the fluence map for delivery may be updated at the current location of the patient target region and may not require adjusting the patient's position using a couch. Localization of a patient target region by calculating a fluence map based on a localization function based on a selected localization reference point (e.g., a delta function or a Gaussian function centered on the selected localization reference point) and a set of shift-invariant ejection filters may be referred to as "virtual localization".In some variations, the patient may be set up once on the couch, while the acquisition of registration images, selection of registration reference points, and calculation of fluence maps for delivery may be performed for each patient target area (e.g., one physical registration / setup, multiple registration image scans, multiple virtual registrations corresponding to multiple patient target areas). Alternatively, the registration images may be acquired once (e.g., when the patient is initially positioned in the radiation therapy system), and the selection of registration reference points and calculation of delivery fluence maps may be performed for each patient target area (e.g., one physical setup using the initially acquired registration images, one registration image scan, multiple virtual registrations corresponding to multiple patient target areas).

[0015] In contrast, conventional treatment delivery methods include acquiring a registration image (e.g., a registration CT image) for physically positioning the patient and a patient target area on a patient table that matches the location of the patient target area determined during treatment planning. To treat multiple patient target areas in a single treatment session, the patient may need to be physically repositioned before irradiating each patient target area, since a particular physical location 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 registration image is acquired. In some variations, the patient positioning and repositioning may be provided by the patient table. Furthermore, some treatment planning systems may be configured to output machine instructions (e.g., a leaf pattern), which may then be altered according to the registration image. However, the treatment planning systems and methods described herein are configured to output a fluence map, and / or an image of the registration fiducials to generate a delivery fluence map, and / or an ejection filter of the delivery system for convolution with the registration function. This may allow for the treatment of multiple patient target regions without the need to reposition the patient for each target region. The delivery fluence map may be segmented into machine instructions by the delivery system immediately prior to dose delivery. Thus, virtual registration may eliminate or reduce the number of times registration images are acquired and the patient is physically positioned (and / or repositioned) for the treatment of multiple patient target regions.

[0016] Alternatively or in addition to virtual registration, the 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 shift vectors may be calculated based on the acquired images of the first patient target area and the treatment planning image. A second set of patient position shift 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 shift vectors. The patient may be positioned at a first location and / or position according to the first set of patient position shift vectors. The patient may be positioned at a second location and positioned according to the second set of patient position shift vectors. Positioning the patient according to the first set of patient position shift vectors may include moving a radiotherapy patient table and / or a therapeutic radiation source according to the first set of patient position shift vectors. The patient may be positioned at a second location and adjusted according to the second set of patient position shift vectors. Positioning the patient according to the second set of patient position shift vectors may include moving the radiotherapy patient table and / or the therapeutic radiation source according to the second set of patient position shift vectors. Moving the radiotherapy patient table may include moving the table along an X-axis, and / or a Y-axis, and / or a Z-axis of the table. Moving the radiotherapy patient table may include adjusting the yaw and / or pitch and / or roll of the table, and moving the therapeutic radiation source may include adjusting the yaw / pitch / roll of a gantry to which the therapeutic radiation source is coupled. 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 shift vectors may be performed before the therapeutic radiation source is activated. In some embodiments, a first location difference may be calculated by comparing a location of the first patient target area in the acquired image to a location of the first patient target area in the first treatment planning image.A second location difference may be calculated by comparing the location of the second patient target region in the acquired image to the location of the second patient target region in the second treatment planning image. A notification may be generated when the first location difference or the second location difference exceeds a location difference threshold. The first patient target region and the second patient target region may include one or more tumor regions. The first patient target region may include a first portion of the tumor and the second patient target region may include a second portion of the tumor. The first and second sets of position shift vectors may include distance and direction translations. The direction translation may include a tilt angle.

[0017] A method for delivering radiation fluence to multiple patient regions may include converting (aka segmenting) the delivery fluence map into radiation therapy system machine instructions (e.g., therapeutic radiation source radiation emission parameters, multi-leaf collimator configurations for each injection location around the patient table, 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 during virtual registration for each of the patient target regions, and machine instructions for delivery to two or more of the patient target regions (e.g., all of the patient target regions) may be segmented simultaneously. Alternatively or in addition, the individual fluence maps for each of the patient target regions may be segmented separately (e.g., sequentially). Optionally, in BgRT, where positron annihilation emission path data is acquired during a treatment session and used to calculate the delivery fluence, the delivery fluence map may be segmented into the radiation therapy system machine instructions in real time, for example, in 500 ms or less between acquisition of the emission path data and delivery of the therapeutic radiation beam. The delivery fluence map may be a fluence map calculated from the emission path data, and virtual registration may be achieved by shifting or rotating the ROI.

[0018] A method for virtual target area registration and radiation delivery may include: acquiring an image of a patient in a treatment position, and identifying a patient target area in the acquired image; selecting a registration reference point in the acquired image, where the registration reference point corresponds to a planned registration reference point; calculating a fluence to deliver to the patient target area at each injection position of a therapeutic radiation source by calculating a registration function based on the registration reference point; applying the registration function to a shift-invariant injection filter derived based on the planned registration reference point; and emitting the delivery fluence to the patient target area using the therapeutic radiation source. The registration function may be a delta function, and applying the registration function to the shift-invariant injection filter may include convolving the delta function with the shift-invariant injection filter. Additionally or alternatively, the shift-invariant injection filter may include one or more functional shift operators and orientation operators of the radiation fluence delivered to the multiple target areas based on the planned registration reference point of each target area. For example, as described above, the functional 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, nearest neighbor, bicubic, spline, or Fourier shift interpolation. The localization reference point may be a user-selected location in the acquired image and / or may correspond to a treatment plan isocenter defined for the patient target region during treatment planning. The first patient target region may be in a first treatment area of ​​the patient defined during treatment planning, and the second target region may be in a second treatment area of ​​the patient defined during treatment planning. The first treatment area may include a first set of axial planes and may have an axial length of about 8 cm or less, and the second treatment area may not overlap the first treatment area, may have an axial length of about 8 cm or less, and may include a second set of axial planes. The center of the first treatment area and the center of the second treatment area may be, for example, collinear along the IEC-Y axis and / or coplanar with the IEC-Y axis. In some variations, the first treatment area may overlap the second treatment area.

[0019] The injection location of the therapeutic radiation source includes the location of the therapeutic radiation source relative to the location of the patient table. The therapeutic radiation source may be mounted on a gantry that is rotatable about a vertical axis, and the location of the therapeutic radiation source may be specified by a gantry angle about the vertical axis. The patient table may be movable to various locations along the vertical axis.

[0020] In some variations, the therapeutic radiation source may be mounted on the gantry such that radiation may be delivered to the patient in discrete, successive arcs (e.g., non-coplanar VMAT, 4-pi VMAT). In some of these variations, these radiation delivery arcs may not be coplanar with one another (e.g., perpendicular to the longitudinal axis). Injection locations may be specified as discrete positions along each arc and may be indexed by the arc. The patient table may be configured to be repositioned to a predetermined position and orientation between each arc.

[0021] In some variations, the therapeutic radiation source may be mounted on a gantry such that radiation may be delivered at fixed points around a 4π or 2π hemispheric envelope. In some of these variations, a set of injection locations may be specified as discrete locations based on a two-dimensional fluence map. The patient table may be configured to move the patient to a predetermined set of positions and / or orientations between each fixed point.

[0022] The method may further include identifying a second patient target area in the acquired image; selecting a second matching reference point for the second patient target area in the acquired image, where the second matching reference point corresponds to a second planned matching reference point; calculating a second delivery fluence at each ejection position of the therapeutic radiation source by calculating a second matching function based on the second matching reference point; applying the second matching function to a second shift-invariant ejection filter based on the second planned matching reference point; and emitting the second delivery fluence to the second patient target area using the therapeutic radiation source. The method may optionally include: identifying a second patient target region in the acquired image; selecting a second registration reference point for the second patient target region in the acquired image, where the second registration reference point corresponds to a second planned registration reference point; calculating a second delivery fluence at each ejection position of the therapeutic radiation source by calculating a second delta function based on the second registration reference point; convolving the second delta function with a second shift-invariant ejection filter based on the second planned registration reference point; and emitting the second delivery fluence to the second patient target region using the therapeutic radiation source. The ejection of the first delivery fluence to the first patient target region and the ejection of the second delivery fluence to the second patient target region may be performed simultaneously and / or sequentially.

[0023] In some variations, a method for virtual target area localization and radiation delivery may include acquiring an image of a patient in a treatment position and identifying a patient target area in the acquired image; selecting localization reference points in the acquired image, where the localization reference points correspond to planned localization reference points; calculating a fluence to deliver to the patient target area at each injection position of the therapeutic radiation source by calculating a localization function based on the localization reference points; applying the localization function to a shift-invariant injection filter derived based on the planned localization reference points; and emitting the delivered fluence to the patient target area using the therapeutic radiation source.

[0024] In some variations, applying the position matching function to the shift-invariant injection filter may include convolving the position matching function with the shift-invariant injection filter. In some variations, the position matching function may be one of a delta function, a Gaussian function, a recursive 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, or a Fourier shift. In some variations, the acquired image may include one or more of a positron emission tomography (PET) image, one or more x-ray projection images, a computed tomography (CT) image, and a magnetic resonance imaging (MRI) image.

[0025] In some variations, the method may further include identifying a second patient target region in the acquired image and selecting a second registration reference point for the second patient target region in the acquired image. The second registration reference point may correspond to a second planned registration reference point. The method may further include calculating a second delivery fluence at each ejection position of the therapeutic radiation source by calculating a second registration function based on the second registration reference point, applying the second registration function to a second shift-invariant ejection filter based on the second planned registration reference point, and emitting the second delivery fluence to the second patient target region using the therapeutic radiation source.

[0026] In some variations, the method may further include identifying a second patient target region in the acquired image and selecting a second localization reference point for the second patient target region in the acquired image. The second localization reference point may correspond to a second planned localization reference point. The method may further include calculating a second delta function based on the second localization reference point and calculating a second delivery fluence at each injection position of the therapeutic radiation source by convolving the second delta function with a second shift-invariant injection filter based on the second planned localization reference point, and emitting the second delivery fluence to the second patient target region using the therapeutic radiation source. In some variations, emitting the first delivery fluence to the first patient target region and emitting the second delivery fluence to the second patient target region are performed simultaneously. In some variations, a first delivery fluence is emitted at a first patient target area and a second delivery fluence is emitted at a second patient target area sequentially.

[0027] In some variations, the position matching function is a first position matching function (δ). The first shift-invariant ejection filter is a first set of fluence map filters (p 1 , p 2 , …, p i) The method may include projecting a first set of location matching functions (δ i ), δ i =proj i (δ). Each projection (δ i ) may be a 2D fluence distribution. Calculating the first fluence for delivery includes calculating the fluence for each projection (δ i ) to the corresponding fluence map filter (p i ) to obtain a first delivered fluence map (f i ), f i =p i *δ i Delivering the first fluence may include moving a therapeutic radiation source to each injection location (i) and generating a first delivered fluence map (f i ) to the first patient target area. In some variations, each projection (δ i ) may be an m by n matrix, where m is the number of multi-leaf 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 first position matching function may be one of a delta function, a Gaussian function, a cyclic 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.

[0028] In some variations, a second shift-invariant injection filter is used to filter the second set of fluence map filters (p_2 1 , p_2 2 , …, p_2 i ) The method may include projecting a second set of second matching functions (δ_2 i ) and δ_2 i =proj i(δ_2), where each projection (δ_2 i ) is a 2D fluence distribution. Calculating the second fluence for delivery is done by calculating the second fluence for each projection (δ_2 i ) to the corresponding fluence map filter p_2 i A second delivered fluence map (f_2 i ), f_2 i =p_2 i *δ_2 i Delivering the second calculated fluence may include moving the therapeutic radiation source to each injection location (i) and calculating a second delivered fluence map (f_2 i ) to the second patient target area. In some variations, each projection (δ_2 i ) may be an m by n matrix. In some variations, m is the number of multi-leaf 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 position matching function may be one of a delta function, a Gaussian function, a cyclic 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 comprises calculating a delivered fluence map (f i , f_2 i ) into a plurality of radiation therapy system machine instructions for each injection location.

[0029] In some variations, delivering the calculated fluence may include segmenting the calculated fluence into a plurality of radiation therapy system machine instructions for each injection location. In some variations, delivering the second calculated fluence may include segmenting the second calculated fluence into a plurality of radiation therapy system machine instructions for each injection location.

[0030] In some variations, the plurality of radiation therapy system machine instructions may include one or more multi-leaf collimator configurations for each ejection location. Emitting the radiation fluence may further include moving leaves of a multi-leaf collimator to a multi-leaf collimator configuration corresponding to a location of the ejection location of the therapeutic radiation source and emitting a pulse of radiation.

[0031] In some variations, the plurality of radiation therapy system machine instructions may further include therapeutic radiation source emission (e.g., pulse) parameters for each injection location. Emitting pulses of radiation may include emitting radiation having therapeutic radiation source pulse parameters corresponding to locations of the therapeutic radiation source injection locations. In some variations, 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 shift-invariant fluence map filter and applying a virtual flattening filter correction factor (FF); (f i )=FF·(p i *δ i );(f_2 i )=FF·(p_2 i*δ_2i .

[0032] In some variations, the virtual flattening filter correction factor (FF) is an m×n matrix and is the inverse of the flatness profile of the radiation beam emitted by the therapeutic radiation source.

[0033] In some variations, the delivery fluence map (f i , f_2 i ) by convolving each projection in the set of projections with a shift-invariant fluence map filter, a virtual flattening filter correction factor (FF), and a distance compensation factor

number

[0034] In some variations, d i represents the distance from injection location i to the center of the patient target area defined during treatment planning,

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[0035] In some variations, the registration reference point may be a user-selected location in the acquired image. In some variations, the registration reference point may correspond to a treatment planning isocenter defined for a patient target area during treatment planning. In some variations, the first patient target area may be in a first treatment area of ​​the patient defined during treatment planning, and the second target area may be in a second treatment area of ​​the patient defined during treatment planning. In some variations, the first treatment area has an axial length of about 8 cm or less and includes a first set of axial planes, and the second treatment area has an axial length of about 8 cm or less and does not overlap with the first treatment area. The second treatment area may include a second set of axial planes. In some variations, the center of the first treatment area and the center of the second treatment area may be collinear along and / or coplanar with the IEC-Y axis. In some variations, the first treatment area and the second treatment area may overlap. In some variations, the injection location of the therapeutic radiation source may include a location of the therapeutic radiation source relative to a location of the patient table. In some variations, the therapeutic radiation source may be mounted on a gantry that is rotatable about the vertical axis, and the location of the therapeutic radiation source may be specified by a gantry angle about the vertical axis, hi some variations, the patient table may be movable to various locations along the vertical axis.

[0036] In some variations, the delivery fluence map (f i , f_2i ) is calculated by dividing each projection in the set of projections by the patient target region at location δ LOC and δ_2 LOC The shift-invariant fluence map filters p', p_2' are circularly convolved with a delta function with an angular shift (φ, φ_2) away from the isocenter, and the delta function δ i , δ_2 i and convolving with

number

[0037] A method for delivering radiation to multiple patient target regions may include obtaining a registration image at the start of a treatment session, identifying a first target region and a second target region in the registration image, shifting a first fluence map subregion of the treatment planning fluence map such that a non-zero high fluence region of the first fluence map subregion co-localizes with the first target region in the registration image, shifting a second fluence map subregion of the treatment planning fluence map such that a non-zero high fluence region of the second fluence map subregion co-localizes with the second target region in the registration image, delivering the shifted first fluence map subregion to the first target region, and delivering the shifted second fluence map subregion to the second target region.

[0038] The treatment planning fluence map may be divided into first and second fluence map sub-regions by defining a boundary of each sub-region along a non-zero low-dose region of the treatment planning fluence map. Delivering the first and second shifted fluence map sub-regions may include segmenting the shifted first and second fluence map sub-regions into a plurality of radiation therapy system machine instructions for each injection location of the therapeutic radiation source. The radiation therapy system machine instructions may include one or more multi-leaf collimator configurations and therapeutic radiation source control parameters for each injection location. The method may optionally include acquiring imaging data during the treatment session and modifying the shifted first fluence map sub-region according to the acquired imaging data before delivering fluence to the first target region. Alternatively or in addition, the method may include acquiring imaging data during the treatment session and modifying the shifted second fluence map sub-region according to the acquired imaging data before delivering fluence to the second target region.

[0039] The delivery of the shifted first fluence map sub-region and the delivery of the shifted second fluence map sub-region may be performed simultaneously and / or sequentially. In some variations, the delivery of the shifted first fluence map sub-region and the delivery of the shifted second fluence map sub-region may be performed sequentially. The registration images may include CT images and / or PET images and / or MRI images. The method may optionally include comparing a high fluence region of the first fluence map sub-region to a location of the first target region to define a first registration correction, comparing a high fluence region of the second fluence map sub-region to a location of the second target region to define a second registration correction, and adjusting the patient table according to the first registration correction before delivering fluence to the first target region. After delivering the fluence to the first target area, the method may adjust the patient table according to the second registration correction before delivering the fluence to the second target area.

[0040] In some variations, delivering the shifted first fluence map sub-region to the first target region may include selecting a matching reference point representing a location in the matching image, applying a matching function calculated from the matching reference point to a first shift-invariant emission filter calculated during treatment planning for the first target region 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 emitting radiation fluence to the first target region in accordance with the first plurality of radiation therapy system instructions.

[0041] Applying the position matching function may include convolving a first position matching function (e.g., a first delta function or a first Gaussian function such as a truncated Gaussian function) calculated from the position matching reference point with a first shift-invariant ejection filter. Delivering the shifted 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 ejection filter calculated during treatment planning for the second target region 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 emitting radiation fluence to the second target region according to the second plurality of radiation therapy system instructions.

[0042] In some variations, the acquired imaging data may be PET imaging data. Delivering the shifted second fluence map sub-region to the second target region may include: selecting a second registration reference point located within the second target region; calculating a second fluence map sub-region by applying a second registration function calculated from the second registration to a second shift-invariant ejection filter; segmenting the calculated second fluence map sub-region into a second plurality of radiation therapy system instructions; and emitting radiation fluence to the first target region according to the second plurality of radiation therapy system instructions. Alternatively or additionally, delivering the shifted second fluence map sub-region to the second target region may include selecting a second localization reference point located within the second target region, calculating the second fluence map sub-region by convolving a second localization function (e.g., a first delta function, or a first Gaussian function such as a truncated Gaussian function) calculated from the second localization with a second shift-invariant ejection filter, segmenting the calculated second fluence map sub-region into a second plurality of radiation therapy system instructions, and delivering radiation fluence to the second target region according to the second plurality of radiation therapy system instructions. In some variations, the method may include adjusting the deliverable radiation dose to satisfy one or more dose constraints. In some variations, the one or more dose constraints may include one or more cost functions. In some variations, the one or more cost functions may include an accumulated cost function having a weighting factor for each cost function given by:

number

[0043] where x is the fluence to the patient target area, A is the dose calculation matrix for the patient target area, Ax cumulative is the cumulative planned dose, x cumulative is the cumulative planned fluence.

[0044] A method of treatment planning for radiation delivery to multiple patient target regions may include identifying a first location of a first patient target region and a second location of a second patient target region in a patient planning image, defining a first region of interest (ROI) (which may be a first injection zone) having a boundary surrounding the first patient target region, defining a second ROI (which may be a second injection zone) having a boundary surrounding the second patient target region, and calculating a treatment planning fluence map for the first patient target region and the second patient target region that specifies a fluence to be delivered if selected imaging data indicates that the first patient target region is within the boundary of the first region of interest and the second patient target region is within the boundary of the second region of interest. The boundary of the second region of interest may be selected to surround the second patient target region for a predetermined range of location displacements of the first and second patient target regions, 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 the 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 position reference point for positioning the patient at the start 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 of the first region of interest, and in some examples, may be a center point of 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. The positron annihilation emission path may be selected if the positron annihilation emission path intersects with at least one of the first and second regions of interest. The second region of interest may be formed to a size that includes a range of locations of the second patient target region.

[0045] In some variations, a method for patient registration 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 lines of response (LORs) using an array of positron emission detectors. If the LORs intersect with either the first region of interest or the second region of interest, the method may include calculating a delivered fluence by convolving the LORs with a shift-invariant ejection filter defined during treatment planning for the corresponding region of interest. The method may further include emitting a delivered fluence using a therapeutic radiation source, where emitting the delivered fluence includes segmenting the delivered fluence into a plurality of radiation therapy system machine instructions for each ejection 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 injection location. In some variations, the images may include one or more of a positron emission tomography (PET) image, a computed tomography (CT) image, and a magnetic resonance imaging (MRI) image.

[0046] A method for positioning and aligning a patient for a radiation therapy treatment session may include positioning a patient on a radiation therapy system table such that a first patient target region is aligned with a location of a therapeutic radiation source and is located within a first predetermined region of interest, and determining whether a location of a second patient target region is within the 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 proceeding with radiation delivery 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 audio 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 is defined relative to the location of the first predetermined region of interest.

[0047] Optionally, some methods may further include acquiring imaging data prior to radiation delivery to the second patient target region, the first and second regions of interest being a spatial mask configured to suppress imaging data with spatial characteristics that do not co-localize with either the first or second radiation regions of interest. In some variations, the method may further include determining whether the second target region is located within the second region of interest based on the acquired imaging data, and proceeding with radiation delivery to the second target region if the second target region is located within the second region of interest. The acquired imaging data may include positron annihilation emission path data (e.g., PET imaging data), CT imaging data, and / or MRI imaging data. Delivering radiation may include segmenting the delivery fluence into a plurality of radiation therapy system machine instructions for each injection location 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 injection location.

[0048] In some variations, the method may further include adjusting the patient position when the location 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 radiation therapy system table to move the location of the second patient target area to be within the second predetermined region of interest. In some variations, the method may further include shifting a planned fluence for the second patient target area according to the location of the second patient target area. In some variations, the method may further include delivering radiation segmenting the delivered fluence into a plurality of radiation therapy system machine instructions for each injection location of the therapeutic radiation source. In some variations, the method may further include the radiation therapy system machine instructions including one or more multi-leaf collimator configurations and therapeutic radiation source pulse parameters for each injection location.

[0049] A method for radiation therapy may include acquiring an image including a first patient target area and a second patient target area, dividing a planned fluence map into a first fluence sub-map that delivers a first prescribed dose to the first patient target area and a second fluence sub-map that delivers a second prescribed dose to the second patient target area, shifting the first fluence sub-map to align with the first patient target area of ​​the acquired image, shifting the second fluence sub-map to align with the second patient target area of ​​the acquired image, calculating a delivered fluence map by combining the shifted first fluence sub-map and the shifted second fluence sub-map, and delivering radiation to the first patient target area if high fluence regions of the shifted first sub-fluence map and high fluence regions of the shifted second sub-fluence map do not co-localize with each other in the delivered fluence map. In some variations, the planned fluence map may be generated by identifying first and second patient target regions in the treatment planning image, calculating a first fluence map for delivering a first prescribed dose to the first patient target region, calculating a second fluence map for delivering a second prescribed dose to the second patient target region, combining the first and second fluence maps, and adjusting the combined fluence map such that high fluence regions of the first and second fluence maps do not co-localize with each other and the first and second patient target regions each receive the corresponding first and second prescribed doses. In some variations, the first fluence sub-map may include the first fluence map, and the second fluence sub-map may include the second fluence map. In some variations, calculating the planned fluence map may include adjusting the combined fluence map based on one or more adjustment constraints such that the first and second fluence maps do not exceed a predetermined dose limit. In some variations, the method may include identifying organs at risk in the treatment planning image.Calculating the planned fluence map may further include adjusting the combined fluence map such that the fluence to the organs at risk does not exceed a predetermined dose limit. In some variations, delivering radiation may include segmenting the delivered fluence into a plurality of radiation therapy system machine instructions for each injection location of the therapeutic radiation source. In some variations, the radiation therapy system machine instructions may include one or more multi-leaf collimator configurations and therapeutic radiation source emission parameters for each injection location. In some variations, the method may include determining whether the delivered fluence map includes a fluence level to the organs at risk that exceeds a predetermined dose limit, and delivering radiation to the first patient target area if the fluence to the organs at risk does not exceed the predetermined dose limit. In some variations, the planned fluence map may be generated by identifying first and second patient target regions in a treatment planning image, calculating a first fluence map for delivering a first prescribed dose to the first patient target region, combining the first and second fluence maps, and calculating the planned fluence map by iteratively adjusting the combined fluence map to satisfy a joint set of constraints while maintaining the first and second fluence maps as separate fluence maps. In some variations, the acquired images may include one or more of positron emission tomography (PET) images, computed tomography (CT) images, and magnetic resonance imaging (MRI) images.

[0050] The planned fluence map may be generated by identifying first and second patient target regions in a treatment planning image, calculating a first fluence map for delivering a first prescribed dose to the first patient target region, calculating a second fluence map for delivering a second prescribed dose to the second patient target region, combining the first and second fluence maps, and adjusting the combined fluence map such that high fluence regions of the first and second fluence maps do not co-localize with each other, and the first and second patient target regions each receive the corresponding first and second prescribed doses. The first fluence sub-map may include the first fluence map, and the second fluence sub-map may include the second fluence map. The planned fluence map may be reoptimized using a joint set of constraints, for example, while keeping the first sub-fluence map and the second fluence sub-map as separate fluence maps. The method may further include identifying an organ at risk in the treatment planning image, and calculating the planned fluence map may further include adjusting the combined fluence map such that the fluence to the organ at risk does not exceed a predetermined dose limit. Delivering radiation may include segmenting the delivered fluence into a plurality of radiation therapy system machine instructions for each injection location 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 parameters for each injection location. Optionally, the method may include determining whether the delivered fluence map includes a fluence level to the organ at risk that exceeds a predetermined dose limit, and delivering radiation to the first patient target area if the fluence to the organ at risk does not exceed the predetermined dose limit.

[0051] In some variations, separate treatment plans may be generated for each patient target region. Each of these plans may be individually optimized, summed, and then re-optimized based on a joint set of constraints while maintaining the treatment plans as separate entities. Separate fluence maps may be generated based on each treatment plan and summed as a combined fluence map. During a treatment session, each separate fluence map may be moved independently and their summed dose volume histograms (DVHs) may be verified prior to dose delivery.

[0052] Additionally or alternatively, one or more adjustment constraints (e.g., artificial constraints in addition to tissue constraints, such as adjustments of structures) may be applied in addition to a predefined set of constraints to ensure that the dose does not exceed a predefined threshold in a given zone (e.g., region). For example, one or more predefined dose constraint zones may be added during treatment planning to maintain the zone as a "low dose valley" that may be useful in reducing the possibility of dose "hot spots" that may occur when the fluence map of each patient target region is independently shifted during a treatment session. In some variations, one or more adjustment constraints may help to facilitate separation of radiation delivery between two or more targets. Some variations of adjustment constraints may limit the dose delivery angle.

[0053] Also disclosed herein is a method for generating a visualization graphic representation of a radiation dose. One variation of the method for generating the visualization graphic may include: generating a treatment plan for irradiating one or more patient target regions, the treatment plan including at least one of at least one treatment plan fluence map, one or more planning images for each patient target region, and a corresponding nominal dose image; calculating, for each patient target region, a plurality of uncertainty data inputs representing the uncertainty of the treatment session; calculating, for each uncertainty data input, an expected dose delivered to each patient target region 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 complex products, each dose image representing a frame within the complex product; and displaying the visualization graphic on a display device.

[0054] In some variations, the treatment plan may further include one or more shift-invariant ejection filters. The multiple data inputs may include one or more scalar values, vector values, and / or volume measurements. In some variations, the complex product may be a 4D volume. The multiple dose images may include 2D dose image slices of each of the one or more patient target regions. The complex product may include a 3D dose volume of each of the patient target regions, and each 3D dose volume may include a 2D dose image slice of each of the patient target regions. In some variations, the method may include iterating over the dose values ​​at each point in each dose image, comparing the dose values ​​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 over each point in the minimum dose volume and calculating a difference between the values ​​of the minimum dose volume and the nominal dose volume, storing the difference and a frequency of the difference in two frames of the delta dose volume, iterating over each point in the maximum dose volume and calculating a difference between the values ​​of the maximum dose volume and the nominal dose volume, storing the difference and a frequency of the difference in another two frames of the delta dose volume, and rendering a surface map for each 4-frame slice of the delta dose volume where the frequency of the maximum values ​​projects along +Z from the 3D plane and the frequency of the minimum values ​​projects along -Z from the 3D plane, and where the values ​​at the points in the surface map are represented by color.

[0055] A variation of a method for generating a visualization graphic may include generating a treatment plan for irradiating one or more patient target regions, the treatment plan may include at least one of one or more treatment plan fluence maps, one or more plan images for each patient target region, and a corresponding nominal dose image; calculating, for each patient target region, a plurality of uncertainty data inputs representing the uncertainty of the treatment session; calculating, for each uncertainty data input, an expected dose delivered to each patient target region 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 complex product, each dose image representing a frame within the complex product; and displaying the visualization graphic on a display device. In some variations, the treatment plan may further include one or more shift-invariant ejection filters. The plurality of data inputs may include one or more scalar values, vector values, and / or volume measurements. The complex product may be a 4D volume. The plurality of dose images may include 2D dose image slices of each of the one or more patient target regions. The composite volume may include a respective 3D dose volume for each patient target region, and each 3D dose volume may include a respective 2D dose image slice for each patient target region. Optionally, the method may include iterating over the dose values ​​at each point in each dose image, comparing the dose values ​​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 over each point in the minimum dose volume and calculating a difference between the values ​​in the minimum dose volume and the nominal dose volume, storing the difference and a frequency of the difference in two frames of the delta dose volume, iterating over each point in the maximum dose volume and calculating a difference between the values ​​in the maximum dose volume and the nominal dose volume, storing the difference and a frequency of the difference in another two frames of the delta dose volume, and rendering a surface map for each 4-frame slice of the delta dose volume, where the frequency of the maximum values ​​projects from the 3D plane along a +Z axis and the frequency of the minimum values ​​projects from the 3D plane along a -Z axis, and where the values ​​at the points in the surface map are represented by color.

[0056] Described herein is a visualization graphic representation of radiation dose. One variation of the visual graphic representation may include a 3D volume representing a patient's anatomy, the 3D volume including a stack of 2D patient anatomical images and a 3D dose surface map corresponding to the dose distribution for each 2D patient anatomical image. The height of the 3D dose surface map may represent the dose level according to the treatment plan for the patient, and the color values ​​across the surface map may represent the probability value of the dose level in the treatment session.

[0057] In some variations, a graphical user interface for multi-target treatment planning may include a first graphical representation of multiple treatment areas, each encompassing one or more patient target regions. Each treatment area may span a different region of the patient and may represent various patient positioning and a second graphical representation of dosimetric characteristics for each treatment area. The first and second graphical representations may be configured to be output simultaneously to a display device.

[0058] In some variations, the dosimetry characteristics of all the multiple treatment areas may be visualized simultaneously on the display device. In some variations, the dosimetry characteristics of each treatment area may be visualized individually. In some variations, the dosimetry characteristics of each treatment area may include one or more of a dosimetry goal, a dose volume histogram, a dose statistics, and a target performance. In some variations, the third graphical representation may include a view of all patient target regions across the multiple treatment areas and visual indications representing the relative spatial relationship between one or more of the patient target regions. In some variations, the graphical user interface may further include a third graphical representation including a view of multiple organs at risk (OARs) across the multiple treatment areas and visual indications representing the relative spatial relationship of each OAR to the one or more treatment areas. In some variations, the graphical user interface may further include a third graphical representation including a view of all patient target regions across the multiple treatment areas and a first visual indication representing a relative spatial relationship between one or more of the patient target regions, and a fourth graphical representation including a view of multiple organs at risk (OARs) across the multiple treatment areas and a second visual indication representing a relative spatial relationship of each OAR to the one or more treatment areas. In some variations, the graphical user interface may include a 3D visualization representing the patient's anatomy. In some variations, the first graphical representation may be layered over the anatomical 3D visualization. In some variations, the first graphical representation may include a band for each of the multiple treatment areas. Each band may have a range representing a dimension of the corresponding treatment area. In some variations, the graphical user interface may include a first projection mode depicting a subset of the multiple treatment areas and a second projection mode depicting all of the multiple treatment areas. In some variations, the subset of the multiple treatment areas may include a user-selected treatment area. The present invention provides, for example, the following: (Item 1) 1. A method for virtual target area localization and radiation delivery, comprising: acquiring an image of a patient in a treatment position and identifying a patient target region in the acquired image; selecting a registration reference point within the acquired image, the registration reference point corresponding to a planned registration reference point; calculating a location matching function based on the location matching reference points, and calculating a fluence of delivery to the patient target area at each injection position of a therapeutic radiation source by applying the location matching function to a shift-invariant injection filter derived based on the planned location matching reference points; and emitting the delivered fluence at the patient target area using the therapeutic radiation source. (Item 2) 2. The method of claim 1, wherein applying the position matching function to the shift invariant injection filter comprises convolving the position matching function with the shift invariant injection filter. (Item 3) 3. The method of claim 2, wherein the position matching function is one of a delta function, a Gaussian function, a circular function, and an interpolation. (Item 4) 4. The method of claim 3, wherein the Gaussian function is a truncated Gaussian function. (Item 5) 4. The method of claim 3, wherein the interpolation is one of linear, bicubic, spline, or Fourier shift. (Item 6) 2. The method of claim 1, wherein the acquired images include one or more of a positron emission tomography (PET) image, one or more X-ray projection images, a computed tomography (CT) image, and a magnetic resonance imaging (MRI) image. (Item 7) identifying a second patient target region in the acquired image; selecting a second registration reference point for the second patient target region within the acquired image, the second registration reference point corresponding to a second planned registration reference point; calculating a second matching function based on the second matching reference point, and calculating a second delivered fluence at each injection position of the therapeutic radiation source by applying the second matching function to a second shift-invariant injection filter based on the second planned matching reference point; 2. The method of claim 1, further comprising: using the therapeutic radiation source to emit the second delivery fluence to the second patient target area. (Item 8) identifying a second patient target region in the acquired image; selecting a second registration reference point for the second patient target region within the acquired image, the second registration reference point corresponding to a second planned registration reference point; calculating a second delta function based on the second registration reference point and calculating a second delivered fluence at each injection position of the therapeutic radiation source by convolving the second delta function with a second shift-invariant injection filter based on the second planned registration reference point; 3. The method of claim 2, further comprising: emitting the second delivery fluence to the second patient target area using the therapeutic radiation source. (Item 9) 9. The method of claim 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 are performed simultaneously. (Item 10) 9. The method of claim 7 or 8, wherein the first delivery fluence is emitted to the first patient target area and the second delivery fluence is emitted to the second patient target area sequentially. (Item 11) The position matching function is a first position matching function (δ), and the first shift-invariant ejection filter is a first set of fluence map filters (p 1 , p 2 , ..., pi ), the method comprising: projecting (δ i ), δ i =proj i (δ) Each projection (δ i ) is the 2D fluence distribution, Calculating the first fluence for delivery is performed by using the first position matching function (δ i ) to the corresponding fluence map filter (p i ) to obtain a first delivered fluence map (f i ), f i =p i*δi Delivering the first fluence includes moving the therapeutic radiation source to each injection location (i) and generating the first delivered fluence map (f i and delivering radiation to the first patient target area according to a method according to any one of claims 2 and 8. (Item 12) Each projection (δ i 12. The method of claim 11, wherein m×n matrix, m is the number of multi-leaf collimator leaves, and n is a number selected during treatment planning. (Item 13) Item 13. The method of item 12, wherein n is the number of beam stations selected during the treatment planning. (Item 14) Item 12. The method of item 11, wherein the first location matching function is one of a delta function, a Gaussian function, a circular function, and an interpolation. (Item 15) Item 15. The method of item 14, wherein the Gaussian function is a truncated Gaussian function. (Item 16) Item 15. The method of item 14, wherein the interpolation is one of linear, bicubic, spline, and Fourier shift. (Item 17) The second shift-invariant injection filter is a second set of fluence map filters (p_2 1 , p_2 2 , ..., p_2 i ), the method comprising: projecting a second set of the second matching function (δ_2 i ), δ_2 i =proj i (δ_2) Each projection (δ_2 i ) is the 2D fluence distribution, Calculating the second fluence for delivery includes calculating the second fluence for each projection (δ_2 i ) to the corresponding fluence map filter (p_2 i ) to obtain a second delivered fluence map (f_2 i) Calculating f_2 i =p_2 i*δ_2i Delivering the second calculated fluence includes moving the therapeutic radiation source to each injection location (i) and calculating the second delivered fluence map (f_2 i and delivering radiation to the second patient target area according to claim 12. (Item 18) Each projection (δ_2 i 18. The method according to claim 17, wherein m x n matrix. (Item 19) 20. The method of claim 18, wherein m is the number of multi-leaf collimator leaves and n is a number selected during treatment planning. (Item 20) 20. The method of claim 19, wherein n is the number of beam stations selected during the treatment planning. (Item 21) Item 18. The method of item 17, wherein the second location matching function is one of a delta function, a Gaussian function, a circular function, and an interpolation. (Item 22) 22. The method of claim 21, wherein the Gaussian function is a truncated Gaussian function. (Item 23) 22. The method of claim 21, wherein the interpolation is one of linear, bicubic, spline, and Fourier shift. (Item 24) Delivering the calculated fluence is i , f_2 i 18. The method of any one of claims 11 to 17, comprising segmenting the first radiation therapy system machine command into a plurality of radiation therapy system machine commands for each injection location. (Item 25) 3. The method of claim 1 or 2, wherein delivering the calculated fluence comprises segmenting the calculated fluence into a plurality of radiation therapy system machine instructions for each injection location. (Item 26) 9. The method of claim 7 or 8, wherein delivering the second calculated fluence includes segmenting the second calculated fluence into a plurality of radiation therapy system machine instructions for each injection location. (Item 27) 27. The method of any one of claims 24-26, wherein the plurality of radiation therapy system machine instructions include one or more multi-leaf collimator configurations for each injection location, and wherein emitting a radiation fluence further includes moving leaves of a multi-leaf collimator to the multi-leaf collimator configurations corresponding to locations of the injection locations of the therapeutic radiation source, and emitting a pulse of radiation. (Item 28) 28. The method of claim 27, wherein the plurality of radiation therapy system machine instructions further include therapeutic radiation source emission (e.g., pulse) parameters for each injection location, and emitting the pulse of radiation includes emitting radiation having the therapeutic radiation source pulse parameters corresponding to a location of the injection location of the therapeutic radiation source. (Item 29) The delivered fluence map (f i, f_2 i ) further comprises convolving each projection in the first or second set of projections with the corresponding shift-invariant fluence map filter and applying a virtual flattening filter correction factor (FF); (f i )=FF·(p i*δi ) (f_2 i =FF·(p_2 i*δ_2i ) 25. The method according to claim 24, wherein the virtual flattening filter correction factor (FF) is an m×n matrix and is the inverse of the flatness profile of the radiation beam emitted from the therapeutic radiation source. (Item 30) The delivered fluence map (f i , f_2 i ) by convolving each projection in the set of projections with the shift-invariant fluence map filter, and computing the virtual flattening filter correction factor (FF) and distance compensation factor (DFC).

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[0059] The present application can be understood by reference to the following description in conjunction with the accompanying figures.

[0060] [Figure 1A] 1 is a flowchart representation of one variation of a method for treatment planning for virtual registration of SBRT. [Figure 1B] 1 is a flowchart representation of one variation of a method for treatment planning for virtual localization of BgRT. [Diagram 2] 13 is a flowchart representation of one variation of a method for treatment planning for mosaic multi-target localization. [Figure 3A] (FIGS. 3A-3B) Depict a flowchart representation of one variation of a method for treatment planning for isolated multi-target localization. [Figure 3B] (FIGS. 3A-3B) Depict a flowchart representation of one variation of a method for treatment planning for isolated multi-target localization. [Figure 4] 1 is a flowchart representation of one variation of a method for treatment planning for BgRT-based localization. [Figure 5A] 1 is a flowchart representation of one variation of a method for treatment planning. [Figure 5B] 1 is a flowchart representation of one variation of a method for treatment planning. [Figure 5C] 1 is a flowchart representation of one variation of a method for treatment planning. [Figure 6] 1 is a flowchart representation of one variation of a method for treatment planning. [Figure 7A] 1 is a flowchart representation of one variation of a method for virtual position matching. [Figure 7B] 1 is a flowchart representation of one variation of a method for virtual position matching. [Figure 8A] 1 is a flowchart representation of one variation of a method for mosaic multi-target localization. [Figure 8B] 1 is a flowchart representation of one variation of a method for mosaic multi-target localization. [Figure 9] 1 is a flowchart representation of one variation of a method for separated multi-target localization. [Figure 10] 1 is a flowchart representation of one variation of a method for BgRT-based location matching. [Figure 11A] 1 is a flowchart representation of an alternative method of positioning a patient for radiation therapy. [Figure 11B] 1 is a flowchart representation of one variant of the method. [Figure 12A] (FIGS. 12A-12F) illustrate one variation of a procedure in which the patient's position may be adjusted. [Figure 12B] (FIGS. 12A-12F) illustrate one variation of a procedure in which the patient's position may be adjusted. [Figure 12C] (FIGS. 12A-12F) illustrate one variation of a procedure in which the patient's position may be adjusted. [Figure 12D] (FIGS. 12A-12F) illustrate one variation of a procedure in which the patient's position may be adjusted. [Figure 12E] (FIGS. 12A-12F) illustrate one variation of a procedure in which the patient's position may be adjusted. [Figure 12F] (FIGS. 12A-12F) illustrate one variation of a procedure in which the patient's position may be adjusted. [Figure 13A] (FIGS. 13A-13F) illustrate one variation of a procedure in which the patient's position may be adjusted. [Figure 13B] (FIGS. 13A-13F) illustrate one variation of a procedure in which the patient's position may be adjusted. [Figure 13C] (FIGS. 13A-13F) illustrate one variation of a procedure in which the patient's position may be adjusted. [Figure 13D] (FIGS. 13A-13F) illustrate one variation of a procedure in which the patient's position may be adjusted. [Figure 13E] (FIGS. 13A-13F) illustrate one variation of a procedure in which the patient's position may be adjusted. [Figure 13F] (FIGS. 13A-13F) illustrate one variation of a procedure in which the patient's position may be adjusted. [Figure 14A](FIGS. 14A-14F) illustrate one variation of a procedure in which the patient may be positioned to irradiate two discrete patient target areas. [Figure 14B] (FIGS. 14A-14F) illustrate one variation of a procedure in which the patient may be positioned to irradiate two discrete patient target areas. [Figure 14C] (FIGS. 14A-14F) illustrate one variation of a procedure in which the patient may be positioned to irradiate two discrete patient target areas. [Figure 14D] (FIGS. 14A-14F) illustrate one variation of a procedure in which the patient may be positioned to irradiate two discrete patient target areas. [Figure 14E] (FIGS. 14A-14F) illustrate one variation of a procedure in which the patient may be positioned to irradiate two discrete patient target areas. [Figure 14F] (FIGS. 14A-14F) illustrate one variation of a procedure in which the patient may be positioned to irradiate two discrete patient target areas. [Figure 15A] 1 depicts one variation of a visualization graphic representing dose distributions and / or probabilities. [Figure 15B] 1 depicts one variation of a visualization graphic showing 3D dose distribution (nominal, minimum, maximum dose levels). [Figure 15C] 13 is a flowchart representation of an alternative method for generating a visualization graphic. [Figure 15D] FIG. 11 is a block diagram of an alternative method for generating a visualization graphic. [Figure 15E] 13 is a flowchart representation of an alternative method for generating a visualization graphic. [Figure 16A-1] 13 is a flowchart representation of an alternative method for generating a visualization graphic. [Figure 16A-2] 13 is a flowchart representation of an alternative method for generating a visualization graphic. [Figure 16B] FIG. 11 is a block diagram of an alternative method for generating a visualization graphic. [Figure 17A]1 depicts one variation of a visualization graphic representing delta dose distribution. [Figure 17B] 1 depicts one variation of a visualization graphic representing delta dose distribution. [Figure 17C] 1 depicts one variation of a visualization graphic representing delta dose distribution at maximum dose level. [Figure 17D] 1 depicts one variation of a visualization graphic representing delta dose distribution at nominal dose levels. [Figure 17E] 1 depicts one variation of a visualization graphic representing delta dose distribution at minimum dose level. [Figure 17F] A variation of the visualization graphic (nominal, minimum, maximum dose levels) is depicted. [Figure 18A] 1 is a flowchart representation of one variation of a method for multi-targeted radiation delivery. [Figure 18B] 1 is a flowchart representation of one variation of a method for multi-targeted radiation delivery. [Figure 18C] 1 is a flowchart representation of one variation of a method for multi-targeted radiation delivery. [Figure 18D] 1 is a flowchart representation of one variation of a method for multi-targeted radiation delivery. [Figure 19] 1 is a flowchart representation of one variation of a method for multi-targeted BgRT-based radiation delivery. [Figure 20] 1 is a flowchart representation of one variation of a method for multi-targeted radiation delivery. [Figure 21A] 1 depicts one variation of a radiation therapy system that may be used in any of the methods described herein. [Figure 21B] 1 illustrates a cross-sectional view of another variation of a radiation therapy system that may be used in any of the methods described herein. [Figure 21C] 1 depicts a schematic diagram of another variation of a radiation therapy system that may be used in any of the methods described herein. [Figure 22A] FIG. 1 is a schematic diagram of a voxel-based delta function in space. [Figure 22B] 1 is an example of a virtual flattening filter correction factor (FF) for a radiation therapy system with 64 MLC leaves and 20 patient table beam stations. [Figure 23A] FIG. 2 is a schematic diagram depicting a shifted registration image of a patient; [Figure 23B] A sinogram is depicted with rows and columns corresponding to the number of MLC leaves and the number of injection locations. [Figure 23C] Dose profiles (from left to right along the X-, Y-, and Z-axes) before and after the fluence shift are depicted. [Figure 23D] Dose profiles (from left to right along the X-, Y-, and Z-axes) are depicted from a 90 degree exit angle / position before and after the fluence shift. [Figure 24] 4 depicts the fluence shift of the delta function across the MLC leaf index for a set of take-off angles. [Diagram 25] 4 depicts the fluence shift of a Gaussian function across the MLC leaf index for a set of take-off angles. [Figure 26] 4 depicts the fluence shift of a truncated Gaussian function across the MLC leaf index for a set of take-off angles. [Figure 27] (Figures 27-29) depict simulated color intensity plots of a matching function that is a truncated Gaussian function with a σ value of 2 mm. [Figure 28] (Figures 27-29) depict simulated color intensity plots of a matching function that is a truncated Gaussian function with a σ value of 2 mm. [Figure 29] (Figures 27-29) depict simulated color intensity plots of a matching function that is a truncated Gaussian function with a σ value of 2 mm. [Diagram 30] 30-32 depict simulation plots of a matching function that is a truncated Gaussian function with a σ value of 4 mm. [Diagram 31]30-32 depict simulation plots of a matching function that is a truncated Gaussian function with a σ value of 4 mm. [Diagram 32] 30-32 depict simulation plots of a matching function that is a truncated Gaussian function with a σ value of 4 mm. [Diagram 33] FIG. 1 is a schematic diagram illustrating virtual registration with roll correction. [Diagram 34] FIG. 13 is a schematic diagram depicting virtual localization with roll correction for BgRT. [Figure 35A] (FIGS. 35A-35C) Depict three different patient treatment plan variations. [Figure 35B] (FIGS. 35A-35C) Depict three different patient treatment plan variations. [Figure 35C] (FIGS. 35A-35C) Depict three different patient treatment plan variations. [Figure 36A] (FIGS. 36A-36B) Diagrams depicting examples of treatment plans. [Figure 36B] (FIGS. 36A-36B) Diagrams depicting examples of treatment plans. [Figure 37A] (FIGS. 37A-37N) Depict a graphical user interface for multi-target mixed position matching. [Figure 37B] (FIGS. 37A-37N) Depict a graphical user interface for multi-target mixed position matching. [Figure 37C] (FIGS. 37A-37N) Depict a graphical user interface for multi-target mixed position matching. [Figure 37D] (FIGS. 37A-37N) Depict a graphical user interface for multi-target mixed position matching. [Figure 37E] (FIGS. 37A-37N) Depict a graphical user interface for multi-target mixed position matching. [Figure 37F] (FIGS. 37A-37N) Depict a graphical user interface for multi-target mixed position matching. [Figure 37G](FIGS. 37A-37N) Depict a graphical user interface for multi-target mixed position matching. [Fig. 37H] (FIGS. 37A-37N) Depict a graphical user interface for multi-target mixed position matching. [Fig. 37I] (FIGS. 37A-37N) Depict a graphical user interface for multi-target mixed position matching. [Figure 37J] (FIGS. 37A-37N) Depict a graphical user interface for multi-target mixed position matching. [Figure 37K] (FIGS. 37A-37N) Depict a graphical user interface for multi-target mixed position matching. [Figure 37L] (FIGS. 37A-37N) Depict a graphical user interface for multi-target mixed position matching. [Figure 37M] (FIGS. 37A-37N) Depict a graphical user interface for multi-target mixed position matching. [Figure 37N] (FIGS. 37A-37N) Depict a graphical user interface for multi-target mixed position matching. [Figure 38A] (FIGS. 38A-38E) Depict a graphical user interface for multi-target treatment area definition. [Figure 38B] (FIGS. 38A-38E) Depict a graphical user interface for multi-target treatment area definition. [Figure 38C] (FIGS. 38A-38E) Depict a graphical user interface for multi-target treatment area definition. [Figure 38D] (FIGS. 38A-38E) Depict a graphical user interface for multi-target treatment area definition. [Figure 38E] (FIGS. 38A-38E) Depict a graphical user interface for multi-target treatment area definition. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0061] Disclosed herein is a method for treatment planning, patient setup, registration, and radiation delivery for irradiation of multiple patient target regions in a single treatment session or fraction. The treatment planning method may include selecting a planned registration reference point for each target region and calculating a shift-invariant ejection filter for each target region based on the selected planned registration reference point. For irradiation of multiple target regions, a treatment planning system performing the method described herein may generate a set of shift-invariant ejection filters associated with the planned registration reference point for each patient target region. Optionally, the treatment planning system may generate a planned fluence map representing radiation fluence across one or more patient target regions, one or more OARs, and / or healthy tissue. In some variations, the treatment planning system does not generate a set of radiation therapy machine instructions to be executed by the radiation therapy system after patient setup and patient target area alignment, but instead, segmentation of the delivery fluence map is performed in "real time", e.g., 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, of calculating the delivery fluence map. By deferring machine instruction segmentation until the treatment session, the planned fluence map can be updated with the latest location data of the patient target area (e.g., calculating the delivery fluence map) before calculating the machine instructions. Shifting the fluence map (e.g., linear shift, fixed shift) can be easily calculated, whereas "shifting" the machine instructions can result in non-linear effects that affect the delivered dose. Additionally, delaying the segmentation of the machine instructions until at least after patient target region registration allows for "virtual registration," in which the fluence map generated by the treatment planning system is adjusted based on the most recent location data. In some variations, virtual registration may include updating the planned fluence map by convolving a shift-invariant injection filter with a registration function derived from the most recent location data (e.g., the current location of the planned registration reference point).By updating the registration reference point during a treatment session and calculating the delivery fluence map based on a delta function (for example) centered on the registration reference point and a set of shift-invariant ejection filters for that target area, the planned fluence map can "follow" the patient target area instead of physically adjusting the patient position (for example, using a patient table) to match the planned fluence map. Segmenting the fluence map that best reflects the actual location of the patient target area can facilitate better accuracy of radiation delivery than delivering radiation based on a fluence map that has not been updated to reflect the actual location of the patient target area. The virtual registration method combined with the BgRT method (wherein the delivery fluence is further updated with imaging data acquired during the session, such as positron annihilation emission path data) can help improve the accuracy of dose delivery to multiple patient target areas. In the virtual registration method described herein, the patient can be physically set up and registered once (for example, to one patient target area), but radiation can be applied to multiple virtually registered patient target areas.

[0062] Radiation delivery to multiple patient target areas and / or irregularly shaped target areas poses challenges to registration / registration and radiation delivery. For example, multiple tumors may change in various ways (e.g., location, shape, and / or size) between when the treatment planning images are acquired and when the patient arrives for treatment. Some tumors may grow while others may shrink, some tumors may shift to the right while others may shift to the left, etc. If the patient loses or gains weight (e.g., due to swelling), the location of the tumor relative to healthy tissue or bone landmarks may change. In addition, when treating multiple target areas in a single treatment session or fraction, the target areas treated in later portions of the treatment session may have moved from their locations in earlier portions of the treatment session (e.g., initially during patient setup and registration). The motion may be cyclic (e.g., due to breathing) or static (e.g., during successive treatments of multiple target regions, the patient may shift position at some point during delivery, making registration of the last target to be treated less effective). Addressing patient and / or target region changes between planning and treatment, as well as changes that may occur during a treatment session, is further complicated by the highly coupled nature of dose delivery to the patient. Radiation applied to one target region may produce scattered dose in other target regions, and in some cases, a radiation beam may intersect two target regions (or a target region and an OAR) and deliver a direct dose to both regions. If these target regions move relative to one another, the treatment plan fluence map may not provide the prescribed dose. Thus, aligning the entire target region or a collection of target regions associated with one or more tumors with the radiation therapy system for the intended (i.e., future) radiation treatment session, such as when a healthcare provider is attempting to register a single target or multiple targets at the beginning of a treatment session, may be difficult and may result in inaccurate dose delivery.

[0063] The treatment planning, registration, and radiation delivery methods described herein may help mitigate some of the dose delivery uncertainties associated with treating multiple patient target regions in a single treatment session. One variation of a method for radiation delivery to multiple patient target regions may include registering (e.g., virtually registering and / or physically registering) each patient target region individually (e.g., independently from the remaining patient target regions) to derive a delivery fluence map for each patient target region, and then delivering radiation to each patient target region according to the corresponding delivery fluence map. Registering each patient target region may include dividing the planned fluence map into fluence map sub-regions for each target region along low fluence regions (either by the treatment planning system during treatment planning or by the radiation therapy system at the start of the treatment session), and deriving the delivery fluence map by shifting the fluence map sub-regions, e.g., by using a virtual registration method that shifts the planned fluence map. Alternatively or additionally, a method for radiation delivery to multiple patient target regions may include individually generating a planned fluence map for each patient target region, individually registering each patient target region (e.g., independently from the remaining patient target regions) to derive a delivered fluence map, combining the individual delivered fluence maps to ensure that the cumulative fluence map meets prescribed dose targets, and if the dose targets are met (i.e., minimum prescribed dose to target region, maximum dose to OARs is not exceeded, etc.), delivering radiation to each patient target region according to each patient target region's individual corresponding delivered fluence map.A BgRT method for radiation delivery to multiple patient target regions may include designating one of the multiple patient target regions as a registration target region, defining regions of interest (ROIs) (e.g., biological firing zones (BFZs)) around the remaining patient target regions that are large enough to encompass a range of location displacements of the remaining patient target regions, registering the registration target region, and delivering radiation to each patient target region according to imaging data that spatially co-localizes with the ROI of each patient target region. The ROI around the registration target region may be smaller than the ROI around the remaining patient target regions.

[0064] Optionally, at one or more stages during treatment planning and / or radiation delivery, the system controller of the treatment planning system and / or radiation therapy system may generate and display one or more visualization graphics showing the deposition of the dose on the patient's anatomy. Additional modifications to the radiation delivery may be included in response to the visualization graphics as may be desired by the clinician or technician. Providing visualization graphics depicting the distribution of the dose on the patient's anatomy, particularly as part of or after a registration / registration procedure, may help the clinician or technician evaluate the interaction of the calculated fluences for each patient target area and determine whether these cumulative levels of fluence are acceptable. For example, if the scattered dose from one target area to another is relatively low or spatially uniform, it may be possible to ignore the effect of spatial changes between the planned fluence map and the delivered fluence map. The visualization graphics can help the clinician or technician identify hot spots, and / or cold spots, and / or dose coupling effects (e.g., when a radiation beam intersects two or more target regions and / or OARs) that may result from the delivery of radiation to multiple target regions. Identifying these unwanted dose interactions prior to radiation delivery and providing spatial information on the dose distribution as feedback to the treatment planning and optimization process can help further refine the planned fluence map and / or ejection filter.

[0065] Alternatively or additionally, the patient setup and target area registration / registration method may include acquiring one or more images of the tumor during the image-guided registration procedure that reflect current information regarding the location, size, and shape of the tumor before applying radiation. The user may compare the acquired images to treatment plan images acquired and / or prepared prior to the procedure. The user and / or the radiation therapy system may then make adjustments to the radiation therapy session (i.e., perform setup corrections to the patient positioning and orientation) based on the acquired images so that the applied radiation may 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 areas (also referred to herein as "zones" and / or "treatment fields") in the image of the one or more tumors for image-guided registration. An image match or position correction may then be defined for each treatment area or region of interest. The radiation therapy system may automate the application of each position correction as the radiation therapy system proceeds with irradiation of a target area (e.g., a tumor or a portion of a tumor) or multiple target areas. The radiation therapy system may provide the user with instructions indicating position correction or adjustment instructions corresponding to the position correction action performed by the user (e.g., moving the patient's arms or legs or tilting and / or rotating the surface on which the patient is disposed). After the position correction is performed, the radiation therapy system may apply radiation to the real-time or updated location of the tumor or tumor portion in each region of interest. Furthermore, the tumor or tumor portion may be more precisely targeted in each region of interest by using the most effective positioning of the patient relative to the therapeutic radiation source for each region of interest, rather than holding the patient in a position that allows high-quality conformal dose delivery to some tumor regions at the expense of low-quality conformal dose delivery to other tumor regions. This may have the advantage of providing better treatment results and overall conformality to the treatment plan. In addition, the duration of the radiation therapy session may be reduced because multiple targets may be treated during a single radiation therapy session.The reduction in time may enable medical facilities to treat more patients per day. Additionally, the reduction in the duration required to treat multiple tumors or multiple tumor portions also improves the patient experience.

[0066] 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 shift vectors may be calculated based on the acquired images of the first patient target area and the treatment planning image. A second set of patient position shift 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 shift vectors. The patient may be positioned at a first location according to the first set of patient position shift vectors. The patient may be moved to a second location and positioned according to the second set of patient position shift vectors.

[0067] It should be noted that the methods for patient setup, patient target area registration / alignment, and radiation delivery for irradiation of multiple patient target areas in a single treatment session described herein can be used alone or in combination in intensity modulated radiation (IMRT), and / or stereotactic body radiation therapy (SBRT), and / or BgRT. For example, a clinician can determine whether all of the patient target areas should be treated using IMRT / SBRT, or all of the patient target areas should be treated using BgRT, or some of the patient target areas should be treated using SBRT / IMRT and others should be treated using BgRT. Some treatment planning and / or radiation therapy systems have two operating modes, the first mode being SBRT / IMRT planning and radiation delivery, and the second mode being BgRT planning and radiation delivery. A single treatment session can include radiation delivery using SBRT / IMRT method for some patient target areas and radiation delivery using BgRT method for other patient target areas, as may be desired.

[0068] Methodology overview Virtual location matching Virtual registration of a patient target region includes modifying (e.g., shifting) a planned fluence map for a particular patient target region to reflect the current / real-time location of that patient target region. The planned fluence map includes a set of radiation beamlets and beamlet intensities to be applied to the patient as calculated by a treatment planning system based on one or more planning images. Conceptually, this can be thought of as adjusting the fluence map as if the registration image were a planning image. In contrast to physical patient set-up, where the patient's position is physically adjusted by the patient table so that the patient target region location at the time of treatment matches the patient target region location during treatment planning, virtual registration may require few, if any, patient table adjustments. Physical patient set-up typically includes acquiring a registration image (e.g., a registration CT image, an MRI image), comparing the registration image to the planning image to calculate an offset representing the change in the patient target region location, and performing a patient table adjustment and / or moving the patient otherwise based on the calculated offset so that the current location of the patient target region is aligned with the location of the patient target region in the planning image. In virtual registration, instead of adjusting the patient table, the planned fluence map is adjusted (e.g., shifted or rolled) by a calculated offset, i.e., conceptually akin to moving the planning image into registration with the registration image. Other fluence corrections may also be included that help ensure that the resulting dose distribution received by the patient is shifted to the appropriate location in the registration image without significant distortion, e.g., due to the fan-beam nature of the radiation beam and the increasing radiation fluence closer to the radiation source.

[0069] The virtual registration method aims to shift the dose received by the patient by modifying the fluence map delivered by the therapeutic radiation source of the radiation therapy system after registration and before or during patient treatment. This is done by calculating a shift-invariant representation of the treatment plan (e.g., a shift-invariant ejection filter) and selecting an appropriate registration reference point during treatment planning. The shift-invariant treatment plan (e.g., a shift-invariant ejection filter) can be applied to the actual reference point locations derived from the registration image to shift the dose received by the patient (and derive a delivered fluence map that can direct radiation to the current location of the patient target area). An example of a shift-invariant treatment plan representation is given by: for each patient target area, the ejection filter p for every ejection position i, where each ejection filter is a 2D fluence map image in the radiation source beam's eye view coordinate system. i (i.e., if there are three patient target regions and 100 injection locations, then the treatment plan will calculate three sets of injection filters, with each set specifying 100 injection filters, one for each injection location.) The injection filters p i may be calculated based on planned localization reference points associated with the patient target area, and in some variations may be selected by the user. i is convolved with the 2D projection of a discrete 3D delta function δ centered on the planned localization reference point in the patient coordinate system for the 2D beam's eye view at each injection location to obtain the fluence f for each injection location i. i can be computed by solving the set of filters that result in f i =p i*δi During the ceremony, δ i =proj i (δ).

[0070] projection δ i can be a 2D discrete delta function (i.e., an image with all zeros except for a single pixel whose value is 1), so that the action p i*δi can be the 2D shift of the emission filter pi, which can be thought of as a location-independent fluence map. i can be determined based on clinician-specified dose constraints and goals for each patient target region using standard radiation therapy dose optimization techniques that minimize a cost function for the patient dose, for example, using gradient descent. Selecting a desired plan alignment reference point (e.g., a point at the center of the target region, a point in the treatment area that includes the target region), and letting δ represent the shift to that reference point. i and f i Apply the inverse shift to

number

[0071] The delta function δ centered on the localization reference point may represent the location of the patient target area and therefore may be used to calculate a shifted fluence map that directs radiation to the current location of the patient target area. Conceptually, the delta function δ may be thought of as encoding the location of the patient target area specified in 3D coordinates. The delta function δ may comprise an all-zero 3D image with a single one voxel of infinitely narrow dimensions centered on the planned localization reference point, but the projection of the delta function δ onto the injection location i (e.g., the "beam's eye view" of the therapeutic radiation source, or multi-leaf collimator spacing) 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 locations where the table rests during delivery of therapeutic radiation) and may encompass one or more non-zero voxels. ican be a matrix (or image) with dimensions that match the number of MLC leaves and the number of patient table beam stations in the MLC of the radiation therapy system. A schematic representation of a delta function based on a voxel in space and its projection onto the injection location is depicted in Figure 22A. Alternatively, the delta function δ may have a finite size that is set during treatment planning.

[0072] In some variations, the virtual localization may include convolving a set of filters with a localization function, which may include a delta function, a Gaussian function, and a truncated Gaussian function centered on the localization reference point. Figures 24-26 depict examples of localization functions that may be used in any of the virtual localization treatment planning and delivery methods described herein and their corresponding values ​​across a set of MLC leaf indices for multiple ejection angles or positions. Figure 24 depicts the delta function values ​​and dose profile, Figure 25 depicts the Gaussian function values ​​and dose profile, and Figure 26 depicts the truncated Gaussian function values ​​and dose profile. In Figures 24-26, the X-axis corresponds to the MLC leaf index, and the Y-axis is the value or magnitude of the localization function projection of the one-dimensional interpolation shift (e.g., interp1 shift, set of plots on the left) and the Fourier shift (set of plots on the right). Each line represents the localization function value for a different ejection angle and / or position. For each of the dose plots, the X-axis corresponds to distance in millimeters and the Y-axis corresponds to fluence (e.g., dose). Peak-to-peak dose variability is measured from the highest peak in the family of curves to the lowest peak in the family of curves.

[0073] FIG. 24 illustrates the values ​​or magnitudes of the position-matched delta function projections over four ejection angles and / or positions, and their corresponding dose (or fluence) profiles. The peak-to-peak dose variability of the one-dimensional interpolation shift is about 40%, and the peak-to-peak dose variability of the Fourier shift is about 7.5%. FIG. 25 illustrates the values ​​or magnitudes of the position-matched Gaussian function projections over four ejection angles and / or positions, and their corresponding dose (or fluence) profiles, while FIG. 26 illustrates the values ​​or magnitudes of the position-matched truncated Gaussian function projections over four ejection angles and / or positions, and their corresponding dose (or fluence) profiles. As shown in FIGS. 25 and 26, the Gaussian function and the truncated Gaussian function may have better peak-to-peak characteristics compared to the delta function shown in FIG. 24. The peak-to-peak dose variability for the Gaussian function is 11% and 1.5%, and the peak-to-peak dose variability for the truncated Gaussian function is 14% and 2.1% (for linear interpolation and Fourier shift, respectively). However, the Gaussian function and truncated Gaussian function have wider curves than the delta function curve. The wider curves correspond to more MLC leaves that must be open to deliver fluence. That is, for a particular exit angle or position, the value of the position matching function spans more MLC leaves for the Gaussian function or truncated Gaussian function than for the delta function. The truncated Gaussian function of FIG. 26 provides improved peak-to-peak characteristics over the delta function, which has a narrower curve than the Gaussian function. Low peak-to-peak variability is desirable so that shifting the fluence does not result in significant dose differences. A treatment planning method incorporating virtual position matching may include selecting a particular position matching function that provides a dose distribution that meets prescription goals for each patient target region and / or OAR.

[0074] In addition to selecting a particular position matching function during treatment planning, some variations of the treatment planning method may also include selecting parameters (e.g., characteristics, constants, etc.) of the position matching function. For example, the treatment planning method may include selecting a truncated Gaussian function as the position matching function and selecting a σ value (e.g., width) of the truncated Gaussian function. The μ value (e.g., mean or center) of the truncated Gaussian function may be the planned position matching reference point. Position matching functions with different σ values ​​may result in delivered fluences with different conformality and / or distortion characteristics. For example, selecting a position matching truncated Gaussian function with a low σ value may result in a shifted dose or fluence with better conformality compared to a similar function with a high σ value. Figures 27-29 depict simulated color intensity plots of a position matching function that is a truncated Gaussian distribution with a σ value of 2 mm. Figures 30-32 depict simulated plots of a position matching function that is a truncated Gaussian distribution with a σ value of 4 mm. The X-axis of the plots in Figures 27-32 is the injection position / angle, and the Y-axis is the MLC leaf index. Figures 27 and 30 depict the projection of the location matching function onto every injection position for the 2 mm and 4 mm truncated Gaussian functions, respectively. Figures 28 and 31 depict the injection filter values ​​for every injection position for the 2 mm and 4 mm truncated Gaussian functions, respectively. Figures 29 and 32 depict the fluence values ​​for every injection position for the 2 mm and 4 mm truncated Gaussian functions, respectively. The projection of the location matching function in Figure 30 (4 mm σ value) is somewhat broader (i.e., spans more MLC leaves) than the location matching function in Figure 27 (2 mm σ value). This may result in the fluence profile for the 4 mm σ value location matching function (Figure 32) being blurrier than the fluence profile for the 2 mm σ value location matching function (Figure 29). However, the fluence peak across multiple injection locations may be more uniform (lower distortion) for a 4 mm σ-value matching function than for a 2 mm σ-value matching function (higher distortion).These different fluence characteristics may be adjusted during treatment planning based on the clinical and / or prescription objectives of each patient target region and / or OAR. For example, as depicted in Figures 27-32, the treatment planning system may balance the tradeoff between fluence conformality and uniformity or distortion by iteratively evaluating different σ values ​​of the position matching function.

[0075] In some variations, the convolution of a three-dimensional or two-dimensional image with a position matching function (e.g., a delta function, a Gaussian function, a truncated Gaussian function) can be equivalently expressed as an operation on the three-dimensional or two-dimensional image followed by a shift by an interpolation operator. The shift with a delta function can be implemented as a linear, Fourier, or bicubic interpolation of the 2D or 3D image. The operation on the three-dimensional or two-dimensional image can be filtering with a Gaussian or truncated Gaussian filter.

[0076] Although the method examples and variations described herein may refer to the use of a delta function, it should be understood that any of the functions discussed above, e.g., Gaussian functions, truncated Gaussian functions, may be used instead.

[0077] While the delta function described above may encode the position of the patient target area via the registration reference points (i.e., the delta function is a function of the 3D coordinates of the registration reference points), optionally, the virtual registration method may include a second rotation transformation function that encodes the orientation of the patient target area. For example, the rotation function R may be a registration function of the pitch, yaw, and roll of the patient table, which may represent the orientation of the patient target area on the patient. That is, the virtual registration method may include two registration functions, i.e., a first delta function that represents the reference position of the patient target area and a second rotation transformation function that represents the orientation of the patient target area. That is,

number

[0078] Just as a shift can be projected to each exit angle, a fluence map rotation effect can also be projected to each exit angle. The 3D rotation effect can be a 2D affine transformation of the fluence map (i.e., rotate the fluence map in 3D and then project it into the same 2D beam's eye view space). The 3D rotation effect implementing pitch and yaw correction can be expressed as follows:

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[0079] For a ring gantry radiation therapy system, one example of roll correction may be implemented by adding a single offset to the gantry encoder position to roll the plan relative to the patient. For multiple targets, there may not be a single roll offset that can be implemented, where each individual injection filter can be rolled individually. If injection filter p i One example of virtual roll correction that can be implemented for a ring gantry system with N is by interpolating the filter over the entire take-off angle. fp An example of a radiation therapy system having an injection position and a rotation angle φroll is negative with respect to the z-axis,

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[0080]

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[0081] Angle φ roll After rotating by a factor of 1, a new injection filter p' may be used in place of the previous filter p. This may impart an order of action that is consistent with applying offsets to the gantry position encoders to implement roll correction. The advantage of calculating a new set of filters in this manner is that any fluences calculated may be summed together. The fluences of all patient target regions may be summed because they are on the same rotational grid.

[0082] In some ring gantry radiation therapy systems, patient target regions that are not at isocenter may undergo a virtual rotation of the patient target region, a rotation of the frame of reference, and a virtual shift of fluence. Figure 33 illustrates the virtual roll correction of an IMRT / SBRT treatment delivery system. Let δ be located at the virtual center of rotation of the patient target region.

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[0083] φ roll corresponds to the amount of roll in the target offset from the isocenter. In some variations, the virtual roll correction is calculated by multiplying φ by φ so that the patient target region can rotate and move based on the location of the patient target region, as depicted in FIG. roll Δx and Δy are the original location xy of the target and the angle φ roll may correspond to the difference between the initial location of the reference frame after rotation of x and y. Δx=x(1-cosφ)+ysinφ Δy=y(1-cosφ)+xsinφ

[0084] Δr θ corresponds to the amount of leaf offset at each therapeutic radiation source (e.g., linac) position to shift the fluence to the center of the new location. For a fan beam therapeutic radiation source, ΔW may correspond to the spacing between the leaves at the target, and the linac source and system D iso divided by the distance between the isocenter of the target D t where θ corresponds to the angle between the injection locations around the ring gantry.

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[0085] In some variations, the leaf offset may be approximately related to the amount that the patient target region has moved in the plane of rotation of the radiation therapy system in both Δx and Δy. Patient target regions farther from the source may experience larger leaf shifts. θ A more accurate solution for may be obtained using a convolution operation to calculate the leaf offsets.

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[0086] In this formulation, the location of the patient target area can be projected into the fan beam projection space: LOC The location of can be projected into the fan beam projection space at a given injection position i. By inverting the projection of the delta function and convolving it with the patient target area location, this action can shift the fluence. The inverse of the projected delta function can be implemented as transposing a discrete representation of the delta function. Alternatively, the inverse of the delta function can represent the negation of the shift of the delta function. This shift with rotation implements a virtual rotation of the planned fluence around any patient target area location.

[0087] Here, a registration reference point is selected in the treatment session with 3D coordinates (x,y,z), where the pitch, yaw, roll, and x,y,z positions reflect the orientation of the patient table / couch in the patient setup (which may correspond to the predetermined orientation of the patient table during treatment planning). Registering the patient target area in both position and orientation may shift the delivery fluence of injection location i accordingly. f delivery,i = δ delivery,i *p i

[0088] In the formula, δ delivery,i is δ at injection position i delivery is the projection of p' i is the projection of the injection filter p' on the injection position i.

[0089] Figure 34 depicts a schematic of virtual roll compensation for a BgRT treatment delivery system. For a virtual roll at the patient target area, the fluence at each injection location i can be a combination of roll combined with a shift in the delivered fluence.

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[0090] The shift-invariant ejection filter p calculated by the treatment planning system for a specific patient target region based on the planned localized reference points iWhen using the CT scan, virtual registration of the patient target region during treatment can be achieved by acquiring a registration image of the patient in a treatment position (e.g., positioned or set up on a patient table), identifying the patient target region in the image, selecting registration reference points that correspond to the planned registration reference points, and calculating a delta function δ based on the registration reference points. local and converting the delta function into a shift-invariant injection filter p i By convolving with, the delivery at each injection position f_delivery i and calculating the fluence for f_delivery i =p i*δ_locali During the ceremony, δ_local i =proj i (δ local )

[0091] Convolving the ejection filter with a delta function centered on the registration reference point has the effect of moving (e.g., shifting) the planned fluence map to reflect the current location of the patient target area. After calculating the delivered fluence, the radiation therapy 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. The virtual registration and machine instruction segmentation can be performed during the treatment session, preferably in real time. This is in contrast to other treatment planning and radiation therapy systems where the machine instructions are calculated during the treatment planning phase, rather than during the treatment session, resulting in a set of machine instructions that deliver radiation to the location of the patient target area in the planning image, rather than to the current location of the patient target area. In the case of SBRT / IMRT radiation delivery, after the virtual registration and segmentation, the radiation therapy system can then proceed to deliver the prescribed fluence to the patient target area by following the newly segmented machine instructions. For BgRT radiation delivery, the region of interest or ROI (e.g., biological ejection zone or BFZ) may be adjusted (e.g., shifted) using virtual registration, and the delivered fluence map may not be segmented into machine instructions until the delivered fluence map has been further updated with imaging data acquired during the treatment session (e.g., positron annihilation emission path data). For example, approximately 500 milliseconds prior to delivery of the therapeutic radiation beam, the radiation therapy system may update the delivered fluence with imaging data acquired in a 500 millisecond window, and then segment the delivered fluence immediately prior to delivery. If multiple patient target areas are to be irradiated in a single session, virtual registration of each patient target area may be performed in a single batch at the start of a treatment session and / or sequentially throughout the treatment session (e.g., register first patient target area, segment transmit fluence into machine instructions, irradiate first patient target area, register second patient target area, segment delivered fluence into machine instructions, irradiate second patient target area, etc.).

[0092] When moving the fluence map to reflect the current location of the patient target area, some registration methods may consider and compensate for one or more physical effects that shift the fluence map. Examples include MLC leaf tongue and groove (T&G) effects, non-flat therapy beam effects, and the effect of attenuation of therapy beam intensity as the inverse square of the distance from the therapeutic radiation source. Optionally, the convolution of the registration function (e.g., delta function, Gaussian type function) with the ejection filter may be convolved with additional elements to calculate a delivery fluence map that accounts for one or more of these effects. To compensate for non-flat therapy beams (i.e., beam intensity that varies across the entire irradiation field in the IEC-X and IEC-Y directions, with the central portion of the field having a greater beam intensity than the edge of the field), a virtual flattening filter correction factor (FF) may be applied to each projection, which is a matrix that is the inverse of the beam intensity flatness profile of the therapeutic radiation source beam along the MLC leaf dimension. (f i )=FF·(p i*δi )

[0093] The virtual flattening filter correction factor (FF) matrix can be a two-dimensional matrix with the number of rows corresponding to the number of MLC leaves and the number of columns corresponding to the number of patient table beam stations. Figure 22B illustrates an example of a virtual flattening filter correction factor (FF) for a radiation therapy system having 64 MLC leaves and 20 patient table beam stations.

[0094] Calculating a delivered fluence map to compensate for the inverse square beam intensity falloff with distance from the therapeutic radiation source includes using a distance compensation scaling factor in the calculation of the delivered fluence.

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[0095] A delivered fluence map that takes into account both the non-flat treatment beam and the inverse square beam intensity falloff is:

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[0096] The virtual registration method described herein may be used for irradiation of multiple patient target areas in a single treatment session or fraction. A method for irradiation of multiple patient target areas in a single treatment session may include defining a patient area or treatment area (e.g., defined by a treatment planning system with or without user input) for each patient target area, where a registration reference point is selected for each patient treatment area for virtual registration according to the steps described herein, and then emitting a therapeutic radiation beam according to a delivery fluence map calculated by virtual registration for each patient treatment area. The patient treatment area may include an area of ​​the patient that is irradiated for a single physical setup and registration. For example, the treatment area may be an area of ​​the patient that is irradiated for a particular patient position on the table (e.g., patient position such as location along the table, arm position, etc.) and a set of IEC-Y table locations. The physical setup and registration may include acquiring one or more unique laser alignment and / or registration images of the patient (e.g., CT or MRI or PET images), acquiring patient positions (e.g., arms up, arms down, abdominal compression, breath holding), and / or adjusting the patient table one or more times so that the patient position matches the position in the treatment plan. The patient treatment area may span the entire area of ​​the patient that is irradiated for a particular physical setup and registration. Each treatment area may have its own physical setup and registration. The patient treatment area may, in some variations, be represented by a set of IEC-Y patient table positions that span the entire irradiated area of ​​the patient. For example, the acquired image and / or the treatment plan image may be partitioned into a first treatment area and a second treatment area. Each treatment area may include one or more patient target areas such that one or more patient target areas in the acquired image may be compared to one or more corresponding patient target areas in the treatment plan image. Each treatment area may correspond to a portion of the patient within which is located one or more patient target regions that are irradiated when the patient is positioned according to a particular set-up during a particular portion of a radiation therapy session.A treatment area may map to a series of patient table positions or steps (e.g., beam stations) and / or ranges of patient table movement along a longitudinal axis of the patient table where one or more target areas of the treatment area intersect with the radiation beam of the therapeutic radiation source. A treatment area may correspond to a particular patient position and / or table orientation. For example, a first treatment area may be associated with a first patient position and orientation for irradiation of a first patient target area in the first treatment area, and a second treatment area may be associated with a second patient position and orientation for irradiation of a second patient target area in the second treatment area. Thus, in some embodiments, a first treatment area may be associated with a first portion of a radiation therapy session (e.g., movement of the patient table through a first set of beam stations), a first patient target area, and a first position of the patient, and a second treatment area may be associated with a second portion of a radiation therapy session (e.g., movement of the patient table through a second set of beam stations), a second patient target area, and a second position of the patient.

[0097] Optionally, the central regions of the defined patient treatment areas may be aligned with one another (e.g., along an "isoline") such that there is no need to adjust the patient position (other than a longitudinal IEC-Y movement to each patient table beam station as IEC-X and IEC-Z are fixed) during delivery of therapeutic radiation for each patient treatment area. This may help reduce the incidence of a user entering a treatment bunker during a treatment session, which may significantly increase overall treatment time. The center of the first treatment area and the center of the second treatment area may be collinear along the IEC-Y axis and / or coplanar with the IEC-Y axis. In some variations, the first treatment area and the second treatment area may overlap, while in other variations, the treatment areas may not overlap. The center of gravity may be along the IEC-X in the same plane (e.g., along an "isoline"). The center of the treatment area does not necessarily have to be the center of the target.

[0098] The registration reference point for each patient target area (or group of patient target areas) may be different from the central area or point of the treatment area. In some variations, the treatment areas defined during treatment planning (e.g., planned patient treatment areas) may be selected based on certain clinical criteria. For example, target areas in different axial planes may be separated into different planned patient treatment areas, and / or target areas separated by more than about 5-10 cm from another target area may be separated into different planned patient treatment areas. During treatment planning, a set of shift-invariant ejection filters may be calculated for each patient target area, and / or for each group of patient target areas that share a registration reference point, using the methods described herein, so that virtual registration of the patient target areas may be performed separately during a treatment session as needed. The delivery of the therapeutic radiation beam according to the delivery fluence map of each planned patient target area may be performed sequentially, and in some variations may include a separate physical patient setup (e.g., by adjusting the orientation of the patient table) before the delivery of radiation to the patient target area of ​​the next patient treatment area. Alternatively or additionally, the delivery fluence maps for each patient target region may be delivered in parallel (rather than stepwise moving the patient table through discrete beam station locations along the vertical axis, i.e., IEC-Y), e.g., segmented together, and delivered without physical patient setup between target regions. For treatment sessions in which one or more of the patient target regions are to receive BgRT radiation and these BgRT patient target regions are registered using virtual registration, a virtual shift is applied to the ROI. A treatment planning method incorporating virtual registration for one or more BgRT targets includes selecting a planned registration reference point for the BgRT patient target region, defining a region of interest (ROI) (e.g., biological injection zone (BFZ)) around the patient target region, and calculating a shift-invariant injection filter (e.g., radiation injection matrix (RFM) or radiation injection filter) based on the ROI and the planning guide image (e.g., planning PET image, MRI image, etc.) that includes the patient target region. iand calculating the ROI. The ROI may be a spatial mask or filter that defines a patient area or region that may include the patient target region and a margin around the patient target region. For example, the ROI may include the tumor region (or any patient target region), and the margin around the tumor region may account for location estimation errors of the tumor region, and / or movement of the tumor region, and / or possible location of the tumor region during radiation delivery, and / or geometric changes of the tumor region. During a treatment session, the radiation therapy system may acquire imaging data (e.g., positron annihilation emission pathway data or LOR data if the patient is injected with a PET tracer, SPECT data if the patient is injected with a SPECT tracer, gamma ray data, MRI data, CT data, and / or X-ray data) that intersects and / or co-localizes with the ROI for that BgRT target region. Imaging data that does not intersect with the ROI or that encompasses data related to structures outside the ROI is not included in the calculation of the delivery fluence map. In this manner, the ROI functions as a spatial mask or filter that may be applied to imaging data acquired during a treatment session.

[0099] A radiation delivery method that combines virtual registration with BgRT delivery may include acquiring images of a patient in a treatment position including a BgRT patient target area and an ROI, selecting a registration reference point in the acquired image, adjusting the ROI by calculating a delta function based on the registration reference point and convolving the delta function with the ROI, acquiring additional image data during the session, calculating a fluence for delivery to the patient target area at each injection position of the therapeutic radiation source by convolving the imaging data with an injection filter, and proceeding to emit the fluence for delivery. (f i )=(p i *proj i (x (ROI*δ i,delivery )))

[0100] where x is additional imaging data acquired (e.g., partial imaging data, time-limited acquired imaging data, positron annihilation emission pathway data, MRI data, SPECT data, gamma data, CT data, and / or X-ray data), and p i is the emission filter (also known as the BgRT emission filter or ray emission matrix) that is the filter used by the virtual registration. In this case, the virtual registration is delivery The adjusted ROI acts to shift the ROI by . Additional acquired imaging data may be spatially filtered (or masked) by the ROI such that only imaging data that co-localizes with the adjusted ROI may be used to calculate the fluence for delivery.

[0101] For BGRT, optionally, a filter p i If you apply roll compensation every time rotates, the ROI may rotate by the same angle. One example would be to implement a 2D rotate function that rotates the ROI mask into place for each plane along Z. The order of operations can be important when embedding roll compensation, in this example you would first apply the roll compensation, then translate by the virtual offset. ROI' = δ(Δx,Δy) * ROT(ROI,φ roll ) Δx=δx(1-cosφ)+δysinφ Δy=δy(1-cosφ)+δxsinφ

[0102] The emission filter is now rotated to coincide with the new frame of reference.

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[0103] Here, for a given injection location f i The fluence at is masked by the rotated and shifted ROI and a virtual offset δ delivery A filter p' shifted by iis the projection of the imaging data convolved with the set of (f i )=(p' i *proj i (x (ROI'*δ delivery ))) ROI' = δ(Δx,Δy)*rot(ROI,θ roll ) (f i )=(p i *proj i (x (ROI'*δ delivery )))

[0104] Optionally, a delivery fluence map for a BgRT target area that takes into account both the non-flat treatment beam and the inverse square beam intensity falloff is as follows:

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[0105] Therapeutic radiation can be delivered to BgRT targets and / or SBRT / IMRT targets in a single session, sequentially and / or in parallel, if desired.

[0106] Optionally, a bounded dose volume histogram curve (bDVH) showing minimum and maximum dose values ​​throughout the patient target region volume may be calculated during treatment planning after the shift-invariant ejection filter has been calculated, taking into account possible dose variability due to patient target region displacement. Outputting a visualization graphic, such as the bDVH or any of the visualization graphics described herein, during treatment planning and / or during patient setup and / or target region registration may help a user assess whether a treatment plan is appropriate for a patient (e.g., for the day of treatment).

[0107] After multi-target virtual registration, each of the patient target regions may have a combined dose component between different patient treatment areas. This dose combination may be a result of the potential for extra beams of fluence to interact with some patient target regions. Knowing the set of virtual registrations, the doses for the patient target regions, OARs, and / or treatment areas may be calculated. A set of normalization coefficients may be applied to each patient target region and / or treatment area to ensure that a specific dosimetry target is met or, alternatively, a specific OAR dose is constrained. One example of implementing these coefficients for each IMRT / SBRT virtual multi-registration j from a set of N registrations is to calculate the dose components for each registration β j The coefficients for can be solved 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 area). One example of such a joint solution is the dosimetry scalar D associated with each patient target region and / or treatment area. j The aim is to minimize the mean sum of squares of

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[0108] For IMRT / SBRT,

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[0109] For BgRT,

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[0110] Dosimetry scalar D j can be one of the following: the mean dose in the PTV, the percentile dose in the PTV, or the maximum dose in the PTV. Alternatively, this dosimetry scalar D jmay be based on a function of the dose to the OARs linked to the target region. Other convex minimization algorithms may be used instead of the root mean square error, such as weighted least squares.

[0111] Although some of the virtual registration methods described above and herein use a delta function derived from the registration reference point and convolve the delta function with a shift-invariant injection filter, it should be understood that the virtual registration methods include other registration functions that encode the orientation of the patient target area based on the pitch, yaw, and roll of the patient table or couch. For example, the virtual registration methods described herein may include convolving a set of filters with registration functions including delta functions, Gaussian functions, and truncated Gaussian functions on the registration reference point that may be selected during a treatment session.

[0112] Mosaic multi-target position matching As briefly mentioned above, one of the challenges of treating multiple patient target regions in a single treatment session is that a registration / registration suitable for one patient target region may not be suitable for the remaining patient target regions. Methods for registration / registration of multiple patient target regions may include registering / registrating each separately (e.g., using a virtual registration method in which the planned fluence map is moved, and / or a physical registration method in which the patient is moved using a table). For example, a treatment session may include one physical registration / registration for the patient target region and one or more virtual registrations for the remaining patient target regions. Using virtual registration, multiple patient target regions may be irradiated without having to physically move and / or reposition the patient to register each target region. In a variation in which a treatment plan may be calculated and optimized for all of the patient target regions, i.e., a single treatment plan that specifies 3D fluence for every patient target region, the "global" treatment plan (e.g., the "global" fluence map) may be divided into discrete sub-regions. The targets of each sub-region may be independently registered or may be registered in a multi-target treatment plan based on a single registration image. Typically, a treatment plan fluence map may include high fluence regions located (e.g., co-localized) on target regions with low fluence regions at almost every other location. These low fluence regions may be referred to as low fluence bands or border regions. A method for treatment planning may include generating a global treatment plan or global fluence map having high fluence regions co-localized with target regions that are surrounded or bordered by low fluence regions or bands, and may further include dividing the global treatment plan or fluence into sub-regions that are surrounded or bordered by low fluence regions. Conceptually, the global treatment plan may be "cut" along the center of these low fluence bands and separated into discrete regions around each target region.These treatment planning fluence map sub-regions or "mosaics" may be independently shifted and oriented around each target using the registration image at the beginning of a treatment session. The planned fluence map sub-region shifts may result in fluence overlap at the low fluence border regions of adjacent sub-regions (i.e., the border regions may receive fluence during irradiation of the target region of two or more adjacent sub-regions), and the low fluence levels of these border regions may be specified during treatment planning to be low enough so that this fluence overlap is not clinically problematic. During treatment planning, the low fluence border regions may be defined broad enough so that the amount of overlap that can be accommodated is large enough to address all sources of registration / registration error. In some variations, adjustment structures and / or constraints may be added during treatment planning to achieve the desired low fluence border regions. After registration of the individual patient target regions of the independent fluence map sub-regions, the delivered fluence map for each sub-region may be segmented into machine instructions for execution by the radiation therapy system. Radiation may be delivered sequentially and / or simultaneously to multiple registered patient target regions or fluence map sub-regions. For example, some patient target regions or fluence map sub-regions may be irradiated sequentially, while other patient target regions or fluence map sub-regions may be irradiated simultaneously with other patient target regions or fluence map sub-regions. A single registration image including all of the patient target regions may be used to register / register each patient target region, or multiple registration images (e.g., one registration image per patient target region or fluence map sub-region). For example, during a treatment session, there may be one physical registration per treatment area (as defined during planning) and one or more virtual registrations for one or more patient target regions within the treatment area. The mosaic registration method may be used for SBRT / IMRT delivery and / or BgRT delivery, and may optionally be used in conjunction with other registration and patient setup methods (e.g., in conjunction with patient table movement, virtual registration methods, rigid body multi-registration methods in which a "best fit" shift is applied to the patient via the table based on the registration images).

[0113] Hybrid Mosaic Multi-Target Localization Optionally, during treatment planning for mosaic registration when the global planned fluence map is divided into planned fluence map sub-regions, the method may include specifying whether the patient target region of each fluence map sub-region should be treated using the SBRT / IMRT method (e.g., designated as a SBRT / IMRT target region) or the BgRT method (e.g., designated as a BgRT target region). A shift-invariant ejection filter may be calculated based on the selected planned registration reference points for all target regions as described herein for virtual registration. Optionally, a bDVH curve may be calculated for each patient target region, which may include generating a series of simulations of all potential shifts of the BgRT target region and / or the SBRT / IMRT target region. The bDVH curves may be reviewed and approved by the clinician during planning. A method for hybrid mosaic multi-target registration may 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 table adjustments (e.g., 6DOF corrections) for each patient target region based on the CT registration images, and selecting a registration reference point for each patient target region. To register / register a particular patient target region, the patient table may first be moved according to the delineated set of patient table adjustments, and a delivery fluence map may be calculated using a virtual registration technique applied to the selected registration reference point for that patient target region. For BgRT delivery, a PET pre-scan may be acquired in conjunction with the acquisition of the registration image. Based on the PET pre-scan, a predicted dose to the BgRT target may be calculated immediately prior to activation of the therapeutic radiation source for irradiation of the BgRT target region, which may help ensure that the actual registration and PET pre-scan images are within a pre-approved dose range. The real-time delivery fluence maps for the BgRT and SBRT / IMRT target regions can be smoothly combined with each other and segmented into machine instructions on the fly (i.e., minutes or seconds before delivery).In beam station delivery, where the patient table remains stationary in a vertical position while the therapeutic radiation source moves around the patient to deliver the calculated fluence, the delivered fluence maps for BgRT and SBRT / IMRT target regions at a particular beam station can be added together and divided into machine instructions from each other while the table is stopped at the beam station. In this way, the delivered fluences for multiple BgRT and SBRT / IMRT target regions can be delivered simultaneously.

[0114] Separated multi-target position matching 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 planned fluence map that specifies the 3D fluence for each individual patient target region) instead of calculating a global treatment plan (i.e., a global fluence map that specifies the 3D fluence for every patient target region). In some variations, a method for treatment planning for isolated registration may include calculating an individual treatment plan for each target region regardless of the presence of the remaining target regions, but taking into account the presence and location of OARs and / or other critical structures, combining the individual treatment plans with each other to form a combined treatment plan, and constraining the combined plan such that high fluence regions from the individual plans do not overlap with other high fluence regions while keeping the individual plans as separate entities, and also to meet original goals such as dose coverage, dose limits, etc. for OARs. Constraining the combined treatment plan so that the treatment plan can accommodate certain independent movements of the target regions may create a planned global fluence map with low fluence regions or bands surrounding each patient target region. In some variations, adjustment structures and / or constraints may be added during treatment planning to achieve the desired low-fluence boundary regions. The combined treatment plan (i.e., the planned global fluence map) can be reviewed and approved by the clinician prior to treatment.

[0115] An example of a treatment planning method for decoupled multi-target localization may include generating a treatment plan for irradiation of a first patient target in a first treatment area and a second patient target area in a second treatment area, dividing the first treatment plan for irradiating the first patient target area in the first treatment area at a first prescribed dose while limiting the irradiation of the OARs to less than a first dose amount, and a second treatment plan for irradiating the second patient target area in the second treatment area at a second prescribed dose while limiting the irradiation of the OARs to less than a second dose amount, combining the first treatment plan and the second treatment plan to generate a combined treatment plan, and iteratively modifying the combined treatment plan to meet desired dose goals and constraints. An example of the dose goals 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 that delivers a first prescribed dose to a first patient target area, and the second treatment plan may include an optimized radiation beam that delivers a second prescribed dose to a second patient target area. The dose amount or level to the OAR resulting from each (e.g., the first and second) treatment plan may be set to a specific percentage of the maximum dose amount. For example, the first dose amount to the OAR (e.g., an OAR located between or spanning both the first and second treatment areas) from the first treatment plan may be 35% of the maximum dose level, and the second dose amount to the OAR from the 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 evaluation of the goal in the combined treatment plan based on iterative calculations within the joint optimization, or through a series of separate optimizations at different contribution levels until an acceptable plan is realized. After the combined treatment plan has been modified to meet desired dose goals and constraints, the combined treatment plan may be split into a first and second treatment plan, and may have optimized beams and / or fluences for delivery.In some examples, a combined treatment plan may include a planned fluence map, where a first treatment plan may include a first fluence sub-map and a second treatment plan may include a second fluence sub-map, and the first and second fluence sub-maps combined to form the planned fluence map.

[0116] Optionally, in some variations, the user may select one patient target area as a higher priority than the other. For example, if the user defines the irradiation of a first patient target area as a higher priority than the irradiation of a second patient target area, the treatment planning method may include dividing the treatment plan into a first treatment plan for irradiating a first patient target area in a first treatment area with a first prescribed dose while limiting the irradiation of the OARs to less than a selected dose amount, and a second treatment plan for irradiating a second patient target area in a second treatment area with a second prescribed dose, combining the first and second treatment plans to generate a combined treatment plan, and iteratively modifying the combined treatment plan to meet desired goals and constraints. In this 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 beams optimized to deliver the prescribed dose to the first patient target area with little or no consideration of the dose to the OARs. The second treatment plan may then consider the dose delivered by the first treatment plan as a "pre-dose" that constrains the beam optimization of the second treatment plan for dose delivery to the second patient target area.

[0117] During a treatment session, each patient target region may be individually registered using one or more registration images (e.g., using typical registration methods by adjusting the patient table or changing the radiation therapy machine instructions, and / or using the virtual registration methods described herein). After all of the patient target regions have been registered, the delivery fluence maps for each patient may be combined with each other to see if there are any "overlapping" dose regions that exceed any constraints. If the desired dose constraints are met, the radiation therapy system may proceed to segment the delivery fluence map into machine instructions and deliver therapeutic radiation to the patient target region. Delaying the segmentation or translation of the delivery fluence map into the radiation therapy system instructions so that the segmentation occurs as close to delivery as possible allows the radiation therapy system to update the delivery fluence to reflect the actual location (and / or any changes in location) of the patient target region, resulting in more accurate delivery of the overall prescribed dose.

[0118] Biologically Guided Radiation Therapy (BgRT) Registration As briefly described, BgRT is a radiation delivery method that uses imaging data acquired during a treatment session to update the exposure fluence and delivers 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 delivery fluence may be relatively sparse (e.g., "partial image data" collected over a short or limited time window that is insufficient for complete image reconstruction) and / or noisy (e.g., having a signal-to-noise ratio that does not allow reliable determination of the centroid of the patient target region). For example, in BgRT, the imaging data used to update or calculate the delivery fluence map may include a partial PET image including one or more lines of response (LOR), a partial MRI image including subsampling of 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 over a limited time window, such as, 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, 200 ms or less. Due to the low latency from image acquisition to 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 area before the target area moves. An ROI (e.g., biological injection zone or biological target zone) may be defined around each BgRT target area that represents a volume used to determine what LOR to use to direct fluence to the target. That is, the ROI may be a spatial filter or mask that may be applied to the LOR, and if a detected LOR intersects with the ROI, the LOR is used in the BgRT delivery algorithm to update the delivered fluence, otherwise the LOR is ignored. A smaller ROI may be preferable because it may reduce the likelihood that non-target PET-avid tissue is included in the ROI (any PET-avid tissue in the ROI will be treated as if it were a target).

[0119] A method of BgRT-based multi-target registration may include designating one of the BgRT target regions as a registration target region and defining an ROI around the remaining ones that is large enough to encompass the range of location shifts of those patient target regions. In some variations, the ROI of the registration target region may be smaller than the ROI of the remaining BgRT target regions. In some variations, the registration target region may be the BgRT target region closest to a critical structure or OAR (e.g., a PET-avid OAR such as the heart). During a treatment session, as long as the ROI of the registration target region is registered / registered and the remaining BgRT target regions are within the ROI (the ROI may be larger or extended to account for expected changes in spatial location relative to the registration target region), the radiation therapy system may proceed to deliver radiation using the BgRT method (i.e., the delivered fluence is calculated by convolving the acquired spatially filtered imaging data with a shift-invariant radiation ejection matrix or ejection filter, and then segmented into machine instructions for immediate execution). The impact of a larger ROI on dose conformality can be calculated and reviewed during treatment planning, and possibly shaped or designed to help reduce the likelihood of including additional PET-avid tissue while helping to increase the probability of accommodating spatial differences between planning and delivery. BgRT-based registration can optionally be used in conjunction with other registration and patient setup methods (e.g., in conjunction with patient table movement, virtual registration methods, rigid body multi-registration methods in which a "best fit" shift is applied to the patient via the table based on the registration images).

[0120] Any of the multi-target registration and radiation delivery methods described herein can be used alone or in combination with registration and delivery methods typically used for single-patient target irradiation and / or irradiation of multiple target regions over multiple treatment sessions.For example, any of the planning, registration, and delivery methods described herein can be used in combination with physical patient setup (e.g., one physical patient setup per patient target region or treatment area in a sequential manner), rigid multi-registration, treatment plan deformation, robust treatment planning (treatment planning that considers position uncertainty during the optimization process and creates a plan that does not vary significantly as a function of position change), and / or online treatment plan adaptation (generating new treatment plans based on registration images).In sequential registration and treatment, each patient target region is registered and treated independently, one after the other.Immediate treatment after registration can help reduce the probability of static patient displacement during treatment, but may require acquisition of multiple registration images (e.g., multiple kVCT images) for each registration instance. Treatment plans for successive registrations and treatments may include jointly optimizing fluence maps across multiple patient target regions and / or may be optimized to be robust to individual displacements of each tumor when registered individually. Rigid body multi-registration may include acquiring a registration image and then calculating a single shift of the registration image relative to the planning image that minimizes a function of the aggregate registration error across all target regions and / or OARs (i.e., performing a "rigid body" registration). To account for these expected registration errors, margins around each target region of the original treatment plan may be expanded. Targets and OARs in the treatment plan may be shifted and oriented as rigid bodies to find the "best" mapping to the actual locations of the targets and OARs in the registration image.The user may choose to consider all registration errors with equal weight and minimize the aggregate registration "error volume", or alternatively, the user may choose to weight some target regions or OARs as more important than others and try to better align those targets at the cost of increased registration error or increased tumor margins elsewhere.

[0121] For example, mosaic multi-target registration and BgRT-based registration may be combined with one or more of the methods described above. Some of the targets in a multi-target treatment plan may be expected to move more as rigid bodies (e.g., target regions associated with the same bone) and therefore may be grouped together and registered using rigid body methods, while the remaining patient target regions may be registered using mosaic multi-target or BgRT-based registration. A robustness algorithm may be used during treatment planning to help ensure that spatial adjustments made to each treatment plan or fluence map sub-region introduce a minimum amount of dose variability. Robust planning may also be used in combination with BgRT-based virtual registration to optimize the shape and placement 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 registration 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, and therefore the dose variability introduced by the soft tissue methods. Alternatively or additionally, a mosaic multi-target registration method may be used to reduce the computational burden of online treatment plan adaptation. For example, patient target regions may be registered based on the planned fluence map using the mosaic multi-target registration method, and then the fluence map for each patient target region may be adapted individually. In yet another example, BgRT treatment planning may incorporate treatment planning steps from the mosaic multi-target registration method, which may help reduce the size of the ROI for each target region.

[0122] In another variation, a treatment plan for multiple patient target regions may include multiple treatment areas, and the patient may be physically set up / registered to each treatment area. Each treatment area may have one or more tumors or patient target regions (e.g., ROIs). During a treatment session, the patient may be physically set up / registered to a first treatment area, and the radiation therapy system may virtually register each of the patient target regions in the first treatment area. For example, the physical registration may provide proper positioning for the first patient target region in the first treatment area, and then the radiation therapy system adjusts the fluence for the remaining patient target regions in the treatment area using the virtual registration method described herein. The fluence for delivery may be calculated or adjusted according to the registration reference points selected during the treatment session from the registration image. The irradiation of the patient target regions in the first treatment area may be performed sequentially and / or in parallel. After the first treatment area is irradiated, the patient may then be physically set up / registered to the second treatment area (e.g., by moving the patient table along the IEC-Y), and the radiation therapy system may virtually register each of the patient target areas in the second treatment area. The patient target areas in the second treatment area may be irradiated as described above for the first treatment area. The first and second treatment areas may overlap in some variations and may not overlap in other variations.

[0123] The method for multi-target treatment planning, registration, and radiation delivery may optionally include generating one or more visualization graphics that may be output to a display device (e.g., a monitor). The visualization graphics may include a dose volume histogram (DVH) or bounded dose volume histogram (bDVH) for each of a plurality of patient target regions, so that a user may be informed that a dose may 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 maps are shifted and / or updated during registration, fluence regions that did not previously overlap during treatment planning may overlap during a treatment session. In mosaic registration, fluence map sub-regions may be registered and shifted individually, and even in separated registration, individual fluence maps of different patient target regions may be registered and shifted individually. Some areas of overlap may include low fluence areas of two or more individual fluence maps or fluence map sub-regions, so that the cumulative fluence of the overlapping areas may not exceed the dose safety threshold of non-target tissues, but such fluence overlaps may exceed the dose safety threshold and / or may co-localize on OARs. A visualization graphic may be generated based on the registration data (e.g., shifted fluence maps or fluence map sub-regions, registration fiducials, registration images, etc.) and output to a display device to help the user evaluate the dosimetric impact of separate registration of multiple patient target regions and / or to help identify any unwanted dosimetric effects resulting from these registration fluence map shifts. The visualization graphic may help the user to better understand the interactions between targets and encode spatial information to evaluate the uncertainty of dose delivery.

[0124] Some visualization graphics can be calculated based on the bDVH curve and calculations, such as the boundaries of the bDVH curve, i.e., the nominal dose (D n ), the potential minimum dose (D pmin), and the maximum potential dose (D pmax ). The visualization graphics may depict representations of the probability of certain dose distributions and levels on certain anatomical structures in 2D slices and / or 3D renderings. Movies or short animations may also depict minimum, nominal, and maximum dose levels so that visual comparisons can be made between these levels. The difference from or variation from the nominal dose (e.g., delta dose) may provide the user with a visual tool to identify hot and cold spots.

[0125] Multi-target treatment planning method Treatment planning methods for treating multiple patient target regions in a single treatment session may include, if desired, calculating various fluence maps (e.g., a global fluence map for all patient target regions and / or OARs, fluence map subregions including a subset of target regions and / or OARs), ejection filters (e.g., a shift-invariant ejection filter), spatial filters (e.g., spatial filtering of imaging data, for regions of interest or ROIs, biological ejection zones or BFZs, biological target zones). Treatment planning methods for treating multiple patient target regions in a single treatment session may include calculating one or more shift-invariant ejection filters for each patient target region for virtual registration, and / or calculating fluence map subregions separated by low fluence bands for mosaic multi-target registration, and / or generating separate treatment plans or fluence maps for each patient target region and constraining the cumulative fluence map for separated multi-target registration. A BgRT treatment planning method for treatment of 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 ROIs for the remaining BgRT patient target regions to accommodate movement of the registration target region and movement of the remaining target regions. A treatment planning method for treating both SBRT / IMRT and BgRT patient target regions (e.g., hybrid mosaic multi-target registration) may further include designating whether the patient target region is a BgRT target region or a SBRT / IMRT target region.

[0126] The treatment planning methods described herein may be used separately or in combination to develop a multi-target treatment plan that is suitable for a particular patient. Some clinicians or clinics may configure a treatment planning system to calculate treatment plan parameters that can accommodate virtual registration of multiple patient target areas and mosaic multi-target registration with sequential or parallel radiation delivery to the patient target areas. Alternatively or in addition, a treatment planning system may be configured to calculate treatment plan parameters that can accommodate virtual registration of multiple patient target areas and separated multi-target registration with sequential or parallel radiation delivery to the patient target areas. For example, some treatment planning systems may be configured to calculate shift-invariant ejection filters for all patient target areas, calculate ejection filters for any BgRT patient target areas, and / or split a treatment plan or a planned fluence map based on the relative positions of the patient target areas, and / or OARs, and / or low fluence areas of the planned fluence map. The BgRT patient target area may be irradiated during a first treatment session and the SBRT / IMRT patient target area may be irradiated during a second treatment session (i.e., on a different day than the first treatment session, if the first and second treatment sessions do not overlap in time, on the same day at different time intervals, etc.). Alternatively, the BgRT patient target area and the SBRT / IMRT patient target area may be irradiated sequentially during the same treatment session. For example, the BgRT patient target area may be irradiated during a first shuttle pass and the SBRT / IMRT patient target area may be irradiated during a second shuttle pass.

[0127] 1A and 1B are flowchart representations of SBRT and BgRT variants, respectively, of a treatment planning method using virtual registration for registration of a single patient target region or multiple patient target regions in a treatment session. FIG 1A illustrates one variant of a treatment planning method incorporating virtual registration for SBRT / IMRT patient target regions. The method (120) may include acquiring one or more treatment planning images of one or more patient target regions (122), defining the contours of one or more patient target regions and / or organs at risk (OARs) and corresponding dose constraints (124), selecting planned registration reference points for each of the one or more patient target regions and / or treatment areas (126), calculating corresponding registration functions for each registration reference point (128), determining a set of therapeutic radiation source injection locations and calculating projections of the registration function onto each injection location (129), and calculating a set of shift-invariant injection filters for each injection location based on the planned registration reference points and the registration function projections for each patient target region (130). Defining the contours of one or more patient target regions (124) may include defining groups of patient target regions that may be linked or associated (e.g., associated with the same bony structure) such that the positions and / or movements of these patient target regions are easily correlated. The method (120) may include selecting (128) a planned registration reference point for the entire group of patient target regions, and calculating (130) a set of shift-invariant ejection filters based on the planned registration reference points for the group of patient target regions. The calculated set of shift-invariant ejection filters and the planned registration reference points for each patient target region, group of patient target regions, and / or treatment area may be transferred (along with other treatment planning parameters) to a radiation therapy system for registration during treatment. In some variations, the calculated shift-invariant ejection filters may represent a planned delivery fluence based on (e.g., centered on) the planned registration reference points.For example, for a particular patient target region (or group of patient target regions), the localization function may be a delta function centered on a planned localization reference point for that patient target region (e.g., tumor centroid). The shift-invariant ejection filter for a particular patient target region may represent a fluence map (e.g., planned fluence map) centered on the planned localization reference point.

[0128] FIG. 1B illustrates one variation of a treatment planning method that incorporates virtual registration for BgRT patient target regions (i.e., patient target regions for which the fluence delivered to those target regions is calculated based on acquired imaging and / or biological data, such as PET emission data). The method (140) depicted in FIG. 1B may include acquiring one or more treatment planning images of one or more patient target regions (142), defining the contours of one or more patient target regions and / or organs at risk (OARs) and corresponding dose constraints (144), defining for each patient target region a region of interest including a margin around the contour of the patient target region (146), selecting a planned registration reference point for each of the patient target regions (148), acquiring imaging data spatially masked by the region of interest (150), determining a set of injection locations of a therapeutic radiation source and calculating projections of the acquired imaging data to each injection location (152), and calculating for each patient target region a set of shift-invariant injection filters based on the planned registration reference points and the imaging data projections (154). In some variations, the boundary of the planned region of interest may include a spatial filter. Defining the contours of the one or more patient target regions (146) may include defining groups of patient target regions that may be linked or associated (e.g., attached to the same bony structure) such that positions and / or motions of the patient target regions are more likely to be correlated. The method (140) may include selecting (148) a planned registration reference point for the entire group of patient target regions and calculating (154) a set of shift-invariant injection filters based on the planned registration reference points for the group of patient target regions.

[0129] Optionally, some treatment planning methods may include designating some patient target regions as SBRT / IMRT target regions and other patient target regions as BgRT target regions. Generating treatment plans for both the SBRT / IMRT target regions and the BgRT target regions may also include acquiring PET images. For each BgRT patient target region, the method may include calculating a shift-invariant ejection filter (e.g., a radiation ejection matrix (RFM)) based on the ROI, one or more planning images of the BgRT patient target region, and a prescribed dose to the BgRT patient target region. Optionally, some treatment planning methods may include determining a set of therapeutic radiation source ejection positions, and calculating a projection of a location matching function, such as a delta function, a Gaussian function, or a truncated Gaussian function, onto each ejection position. Optionally, some treatment planning methods may include calculating a cost function from the location matching fiducial points for each patient target region.

[0130] A radiation ejection matrix (RFM) or ejection 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, that are applied to the patient during a treatment session. An ejection filter or RFM may represent a relationship between a fluence map F for radiation delivery to a patient region and an image X of that patient region. That is, a radiation ejection matrix or ejection filter P may be any matrix such that F=P·X. An ejection 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, e.g., a cost function C(D,F) of the resulting dose distribution D and fluence F, which is formed based on radiation dose constraints and goals and optional restrictions on F. Examples of cost functions may include, but are not limited to, a minimum dose to the target region, an average or maximum dose on the OARs, and / or smoothness of the fluence, total radiation dose, total tissue dose, treatment time, etc. In some variations, generating the radiation projection matrix P may include formulating an optimization problem to minimize a cost function C(D,F) and iterating through different sets of P such that the cost function C(D,F) is minimized while the following condition is satisfied: F=P·X and D=A F=A P X where D is the predicted dose distribution, A is a pre-calculated dose calculation matrix, F is the predicted total delivered radiation fluence, and X is a known complete image (e.g., an image acquired during an imaging session and / or a previous treatment). The predicted dose distribution D and predicted radiation fluence F may be calculated using dose constraints, patient target volume, and / or OAR data, as well as patient planning CT images. An example of a dose calculation matrix A is a (k x n) matrix, where n is the number of candidate beamlets {b i}, where k may be the number of preselected voxels for the ROI. The i-th column (having k elements) of the dose calculation matrix A is a set of single weighted beamlets b i represents the dose contribution to each of the k voxels from

[0131] The dose calculation matrix A may be calculated column-wise, for example, by ray tracing the aperture of each beamlet along a path through the ROI or patient volume and calculating the beamlet's contribution weighted to one for each of the k voxels. The beamlet aperture may be an MLC aperture defined by a single MLC leaf opening (i.e., binary MLC or 2D MLC). Some examples of dose calculation algorithms that may be used in any of the methods described herein include Monte Carlo simulation, collapsed cone convolution superposition, pencil beam convolution, etc.

[0132] The radiation emission matrix P (also known as RFM or emission filter) may be a matrix that, when multiplied by the complete image X, results in a predicted or desired exposure fluence F that minimizes a cost function. The cost function may be convex, allowing the use of well-known convex optimization algorithms such as gradient descent, fast gradient approximation, or interior point methods. The calculated radiation emission matrix P may represent a scaling factor that relates the fluence F to the complete image X. This relationship may be used during a treatment session to calculate, at a particular time, the fluence of a partial image x acquired at that same time by multiplying the partial image by the radiation emission matrix P. i Based on the fluence f i (e.g., f i =P x i ). Additional details regarding BgRT treatment regimens and delivery methods can be found in U.S. Patent No. 15 / 993,325, filed May 30, 2018, which is incorporated herein by reference in its entirety.

[0133] Optionally, some methods (120) may include determining (132) a set of therapeutic radiation source injection locations and calculating a projection of an injection filter onto each of the injection locations. For example, a radiation therapy system with a rotatable gantry may have 100 circumferentially distributed injection locations or angles around a bore through which a patient table can advance. The method (120) may include calculating a projection of each of the injection filters onto each of the 100 injection locations. For an injection filter convolved with a Gaussian or truncated Gaussian function, a width (σ) of the Gaussian function with a mean value (μ) centered on a planned alignment reference point may be selected during treatment planning. For example, the width (σ) of the Gaussian or truncated Gaussian function may be based on the width of an MLC leaf.

[0134] 2 depicts a flowchart representation of one variation of a treatment planning method using mosaic multi-target registration for registration of multiple patient target regions in a treatment session. The method (220) may include acquiring one or more treatment plan images of one or more patient target regions (222), defining the contours and corresponding dose constraints of one or more patient target regions and / or OARs (224), selecting planned registration reference points for each of the one or more patient target regions and / or OARs (228), and calculating a set of shift-invariant ejection filters based on the planned registration reference points for each patient target region and / or OAR (230). The method (220) may include generating a treatment plan fluence map based on the ejection filters and the one or more planning images (234), and defining a perimeter around each patient target region in the treatment plan fluence map that includes a region of low fluence value (236). The calculated set of shift-invariant ejection filters, the planned registration reference points for each patient target area and / or OAR, and the treatment plan fluence map with defined periphery can be transferred (along with other treatment plan parameters) to the radiation therapy system for registration during treatment.

[0135] Optionally, some treatment planning methods (220) may include designating (226) each of the patient target regions as an SBRT / IMRT target region or a BgRT target region. If the patient target region is 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 shift-invariant ejection filter (e.g., RFM), as described above.

[0136] Optionally, some methods (220) may include determining (232) a set of therapeutic radiation source injection locations and calculating a projection of an injection filter onto each of the injection locations. For example, a radiation therapy system with a rotatable gantry may have 100 circumferentially distributed injection locations or angles around a bore through which a patient table may advance. The method (220) may include calculating a projection of each of the injection filters onto each of the 100 injection locations.

[0137] Optionally, some treatment planning methods (220) may include calculating a bounded dose-volume histogram (bDVH) curve for each patient target region and / or OAR (238) and displaying the bDVH curve and / or dose calculation data for each patient target region and / or OAR on a display device (240). The bDVH curves may be calculated for the patient target region by calculating the dose per unit volume for each possible location of the patient target region within the motion envelope (or ROI in case of BgRT targets) to generate a family of dose-volume curves and / or based on biological activity and / or physiological and / or anatomical data acquired before or during the planning session. For example, a family of bounded DVH curves may be calculated for each OAR, ROI, and / or patient target region based on an ejection filter by performing a fixed shift of the PET image of the patient target region within the ROI and calculating the corresponding dose to the OAR, ROI, and / or patient target region for that particular shifted target region location. For example, for a patient target region in a ROI and a patient with one OAR, a family of DVH curves for the patient target region may be calculated for each shifted position of the patient target region in the ROI. The upper threshold boundary of the bDVH curve may include the rightmost point of the family of dose-volume curves, and the lower threshold boundary of the bDVH curve may include the leftmost point of the family of dose-volume curves. Additional details and variations of the method for calculation of bounded DVH curves are described in U.S. Patent Application No. 16 / 016,272, filed June 22, 2018, which is incorporated herein by reference in its entirety.

[0138] 3A and 3B depict a flowchart representation of one variation of a treatment planning method using separated multi-target registration for registration of multiple patient target regions in a treatment session. The method (350) may include acquiring one or more treatment planning images of one or more patient target regions (352), defining one or more patient target regions and / or OARs outlines and corresponding dose constraints (354), selecting planned registration fiducial points for each of the one or more patient target regions (358), and calculating a set of shift-invariant ejection filters based on the planned registration fiducial points for each patient target region (360). The method (350) may include generating a fluence map for each patient target region based on the ejection filters and the one or more planning images (362), and combining all of the patient target region fluence maps into a cumulative treatment planning fluence map (364). Each patient target region may have a separate planned registration fiducial point if the patient target regions are physically separated from each other (e.g., do not overlap). This allows each patient target area to be moved independently. The corresponding patient target area fluence maps of each patient target area may be added together (because dose delivery is linear) to calculate the total dose. For example, if the location of the first and second planned registration reference points changes from planning session to treatment session, the cumulative treatment plan fluence map may be recalculated using the new registration reference point locations. Separate treatment plan fluence maps of multiple patient target areas may allow multiple planned registration reference points to be moved independently of each other, thereby allowing multiple (e.g., two or more) fluence maps to be shifted relative to each other to obtain more optimized dose coverage. Additionally or alternatively, each patient target area fluence map may be individually constrained.

[0139] The method (350) may then include iteratively refining (366) the cumulative treatment plan fluence map based on one or more dose constraints, such as one or more of: (a) high fluence regions remain separated from one another; (b) OAR constraints are met; and (c) initial dose constraints / goals are met.

[0140] In some variations, each of the constraints of the cumulative treatment plan fluence map may be weighted by a linear coefficient that defines or approximates their relative importance. In some variations, the fluence map for a target region may be described as a variable x. The sum of the combined fluences is x cumulative The dose calculation matrix for the patient may be defined as A. The dose to a particular target region may be defined as Ax. Furthermore, the dose to the entire patient may be written as Ax cumulative For example, a dose constraint may include one or more cost functions, optionally weighted by an individual scaling factor. A prescription dose requirement or constraint (C) may include one or more cost functions, such as a cost function C(x) for radiation fluence (x) and / or a cost function C(Ax) for dose in a treatment area, and / or a cost function C(Ax) for total dose. cumulative ), and / or a cost function C(x cumulative ), each of which may optionally include an individual scaling factor (w i , w k , w m , w n) may be used. For example, a cost function on the cumulative fluence map can be used to optimize treatment time in the context of joint delivery. For example, a cost function on the dose for each treatment area can be optimized to ensure that a minimum dose is delivered. This ensures that fluence from different treatment areas delivers very little of the dose to a given target. This significantly reduces coupling between treatment areas and therefore increases the robustness of the treatment plan to relative displacements between treatment areas. For example, D cumulative A cost function for can be used to limit the combined average dose to the heart from all treatment areas combined.

number

[0141] Additional details regarding the cost function and other constraints can be found in U.S. patent application Ser. No. 62 / 966,997, filed Jan. 28, 2020, which is incorporated by reference in its entirety herein.

[0142] Additionally or alternatively, one or more tuning constraints (e.g., artificial constraints, structural tuning, in addition to tissue constraints) may be applied in addition to a predetermined set of dose constraints to ensure that the dose in a given zone (e.g., region) does not exceed a predetermined threshold. In some variations, one or more tuning constraints may allow for separation of radiation delivery between two or more target regions.

[0143] After the cumulative treatment plan fluence map is modified, the method (350) may include defining a perimeter (368) around each patient target region in the cumulative treatment plan fluence map (e.g., adjustment constraints, cost function) that includes regions of low fluence values. Separating the cumulative treatment plan fluence map along the perimeter (370) into individual fluence maps for each patient target region, and calculating (372) a second set of shift-invariant ejection filters for each patient target region based on the planned registration reference points and the fluence map for that patient target region. The second set of shift-invariant ejection filters, the planned registration reference points for each patient target region and / or OAR, and the individual treatment plan fluence map for each patient target region may be transferred (along with other treatment plan parameters) to a radiation therapy system for registration during treatment.

[0144] In some variations, such as in the case of SBRT / IMRT delivery, the treatment planning method may include calculating a delivery fluence for a patient target region and / or treatment area (e.g., based on a prescription dose, a dose constraint, and / or a dose calculation matrix), where the delivery fluence is linked (e.g., fixed) to a planned registration reference point. The calculated delivery fluence may then be segmented (by either the treatment planning system and / or the radiation therapy system) into machine instructions for delivery. During a treatment session, the calculated delivery fluence may be updated based on an updated location of the registration reference point (e.g., selected by a user from a registration image acquired during a treatment session). In this variation, an ejection filter may not need to be calculated by the treatment planning system.

[0145] Optionally, some treatment planning methods (350) may include designating (356) each of the patient target regions as a SBRT / IMRT target region or a BgRT target region. If the patient target region is designated as a BgRT target region, the method (350) may include calculating an ROI for the patient target region. If the patient target regions are physically separated from one another to allow each patient target region to be moved independently, each patient target region may have a separate planned registration reference point, which may allow the fluence maps to be shifted relative to the others for optimized dose coverage. For each BgRT patient target region, the method (350) may also include calculating a shift-invariant ejection filter, as described above.

[0146] Optionally, the method (350) may include displaying (374) a visualization graphic 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 curves for the patient target regions may be calculated as described above.

[0147] 4 depicts a flowchart representation of one variation of a treatment planning method using BgRT-based multi-target registration for registration of multiple patient target regions in a treatment session. The method (450) may include acquiring one or more treatment planning images of one or more patient target regions (452), defining the contours and corresponding dose constraints of one or more patient target regions and / or OARs (454), designating one of the multiple patient target regions as a registration target region (456), and defining the contours of a spatial mask or filter (e.g., ROI, injection zone) for each of the remaining patient target regions (i.e., not the registration target region) to be sized and shaped to accommodate movement of the registration target region and movement of the remaining patient target regions (458). The method (450) may include calculating a set of shift-invariant ejection filters based on the selected planned registration reference points for each patient target region and / or the ROI of the registration target region (462), generating a treatment plan fluence map based on the ejection filters and one or more planning images (466), and calculating doses to the registration target region and remaining patient target regions of all the patient target regions (468). The method (450) may also include calculating shift-invariant ejection filters, such as ejection filters for each ROI of each patient target region, which may be calculated as described above, and the treatment plan fluence map may be generated based on the calculated ejection filters together with the one or more planning images (466). A shift-invariant ejection filter for virtual registration of the ROI and / or a shift-invariant ejection filter (e.g., RFM) for BgRT delivery, planned registration reference points for each patient target area and / or OAR, and / or any treatment plan fluence maps and / or dose calculations can be transferred (along with other treatment plan parameters) to the radiation therapy system for registration and radiation delivery.

[0148] Optionally, some treatment planning methods (450) may include defining (460) the contour of a spatial mask or filter (e.g., injection zone, ROI) of the registration target region to be smaller than the spatial mask or filter of the remaining patient target region. For example, the ROI of the registration target region may be smaller than the ROI of the remaining patient target region. In some variations, the patient target region selected to be the registration target region may be the patient target region closest to a critical structure, such as a highly radiosensitive organ, and / or a PET-avid critical structure, and / or a bone structure. In some variations, the patient target region selected to be the registration target region may be the target region closest to a planning structure (e.g., calculated or user selected), such as an area of ​​potential dose joining between two patient target regions. In some variations, the patient target regions selected to be the registration target regions may be most sensitive to uncertainty, such as regions with high dose gradients, critical dosimetry goals or constraints, inconsistent PET activity (e.g., areas of hypoxia or perfusion), or variable motion trajectories near the edges of the ROI.

[0149] Optionally, some methods (450) may include determining a set of therapeutic radiation source injection locations (464) and calculating a projection of an injection filter onto each of the injection locations. For example, a radiation therapy system with a rotatable gantry may have 100 circumferentially distributed injection locations or angles around a bore through which a patient table may advance. The method (450) may include calculating a projection of each of the injection filters onto each of the 100 injection locations. Optionally, the method (450) may include calculating a bDVH curve for each patient target area and / or OAR (470) and displaying the bDVH curve and / or dose calculation data for each patient target area and / or OAR on a display device (472). The bDVH curves for the patient target areas may be calculated as described above.

[0150] As previously indicated, any of the treatment planning methods for multi-target irradiation may optionally include calculating bDVH curves for each patient target area and / or OAR and displaying DVH and other dose data to the clinician for review and / or approval. In some variations, such dose data may be used as feedback (i.e., as additional constraints) to further refine the treatment plan fluence map and / or ejection filter, which may help improve compliance with dosimetric goals and prescriptions. Figures 5A-5C depict flowchart representations of variations of treatment planning methods that modify the planned fluence map and / or ejection filter based on user-selected modifications of the confidence interval of the bDVH and / or shifts of the dose distribution for the patient target area.

[0151] bDVH confidence interval bDVH confidence interval editing can provide a mechanism by which spatial uncertainty can be reduced or eliminated; bDVH calculations are typically calculated with 95% confidence intervals, and patients are represented within these boundaries on the day of treatment. Reducing the width of the boundaries in the bDVH can reduce the potential minimum dose D pmin , and the nominal dose D n Closer to the potential maximum dose D pmax Methods for reducing the difference from the nominal dose may include reducing the confidence interval. For example, an 80% confidence interval is D pmax and D. pmin D n This may result in a narrower bDVH curve that may be closer to . The tradeoff is that, for example, instead of expecting that 1 in 20 patients will fail the bDVH safety check upon treatment, 1 in 5 patients may fail the bDVH safety check and be denied treatment with a non-deterministic treatment method (i.e., BgRT). Similarly, if the bDVH of a target region responds as being significantly compressed upon initial 95% CI calculation, the bDVH may be recalculated with a higher confidence interval (e.g., 99% CI), in which case the bDVH will widen and the D pmin and D. pmax Dn (i.e., broaden / spread the bDVH curve). Using this functionality, clinicians may be able to reduce or eliminate hot and cold spots within existing boundaries.

[0152] FIG. 5A illustrates a treatment planning method including bDVH confidence interval editing. The method (550) may include developing a treatment plan using one or more specified uncertainty vectors (e.g., biological activity, setup position error, etc.) (551) and selecting a confidence interval (CI) for the uncertainty vector (552), which may be determined based on the type of uncertainty. The method (550) may include optimizing a treatment plan fluence map with the uncertainties (553), calculating a bDVH using the CI to describe the likelihood of a treatment day dose fitting within the bDVH boundaries, and evaluating the bDVH to determine whether the boundaries are acceptable (554). For example, the bDVH may be output to a display device and viewed by a user. If the boundaries are deemed acceptable, the method (550) may include calculating a final dose for the treatment plan (556) and approving the boundaries for the treatment plan (557). The method (550) may include determining (558) how to adjust the boundaries if the boundaries are not acceptable. In some variations, the method (550) may include expanding the boundaries to increase the acceptable uncertainty and setting a new CI that is larger than the original CI (559). In some variations, the method (550) may include compressing the boundaries to decrease the acceptable uncertainty and setting a new CI that is less than the original CI (560). After the CI is adjusted, the method (550) may include optimizing the treatment plan with the uncertainty (561), calculating a new bDVH using the new CI that describes the likelihood of a treatment day dose fitting within the bDVH boundaries, and then evaluating the new bDVH and determining whether the boundaries are acceptable (554). The evaluation and calculation of the bDVH (554-561) may be repeated until a bDVH with acceptable boundaries is calculated.

[0153] In some variations, the confidence interval editing may include determining whether it is necessary to reoptimize the treatment plan fluence map after the CI is adjusted. FIG. 5B illustrates a treatment planning method including a determination as to whether to reoptimize after the bDVH confidence interval editing. The method (570) may include developing a treatment plan using one or more specified uncertainty vectors (e.g., biological activity, setup position error, etc.) (571) and selecting a confidence interval (CI) for the uncertainty vector (572), which may be determined based on the type of uncertainty. The method (570) may include optimizing the treatment plan fluence map with the uncertainties (573), calculating a bDVH using the CI to describe the likelihood of a treatment day dose fitting within the bDVH boundary, and evaluating the bDVH and determining whether the boundary is acceptable (574). For example, the bDVH may be output to a display device and viewed by a user. If the boundaries are deemed acceptable, the method (570) may include calculating a final dose for the treatment plan (576) and approving the boundaries for the treatment plan (577). If the boundaries are not acceptable, the method (570) may include determining how to adjust the boundaries (578). In some variations, the method (570) may include expanding the boundaries to increase the acceptable uncertainty and setting a new CI that is larger than the original CI (579). In some variations, the method (570) may include compressing the boundaries to decrease the acceptable uncertainty and setting a new CI that is less than the original CI (580). After the CIs are adjusted, the method (570) may include determining whether a new optimization is needed. If so, the method (570) may include optimizing the treatment plan with the uncertainty (581), using the new CI to calculate a new bDVH that describes the likelihood of a treatment day dose fitting within the bDVH boundaries, and then evaluating the new bDVH and determining whether the boundaries are acceptable (574). If it is determined that optimization is not required, the method (570) may proceed directly from the CI adjustment to evaluating the new bDVH (574).The evaluation and calculation of the bDVH (574-581) may be repeated until a bDVH with acceptable bounds 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.

[0154] Some treatment planning methods may include displaying a treatment plan dose distribution (e.g., calculated from a treatment plan fluence map) overlaid on a patient anatomical image that also includes each of the patient target regions to be treated in the treatment session, receiving clinician input related to dose shifts, and recalculating the treatment plan fluence map and / or the ejection filter based on the dose shifts entered by the clinician. In some variations, the dose shift may be a fixed shift of dose by only about 0.1 mm to about 1 mm in any direction. These small dose shifts may help to avoid unnecessary fluence delivery to the spine and / or reduce hot spots caused by two interacting fluence maps between two in-plane target regions. For example, when fluence map sub-regions are registered separately in a mosaic multi-target registration, and / or when individual fluence maps of different patient target regions are registered separately in a separated multi-target registration, the cumulative delivery fluence map (i.e., the sum of all delivery fluence map sub-regions and / or the sum of all individual fluence maps for each patient target region) may have regions of undesirable fluence, such as high fluence levels at OARs or healthy tissue regions. These regions of unwanted fluence may not have been present in the planned fluence map, but when fluence map modifications (e.g., shifts) are performed during registration, undesirable fluence map artifacts may appear in the delivery fluence map. The radiation therapy system may generate a visualization graphic reflecting these fluence map modifications (and / or dose modifications) overlaid with an anatomical image of the patient so that the user may determine whether any of the delivery fluence maps may be shifted to mitigate any unwanted dose or fluence. Alternatively or additionally, in some variations, dose shifting may be performed after fluence map optimization during treatment planning, which may help facilitate the generation of treatment plans and / or planned fluence maps that meet dosimetric objectives.After the dose shift, an additional fluence map optimization step may be optional (i.e., re-optimization may not be necessary). The updated fluence map and / or emission filter may be transmitted to the radiation therapy system for registration and treatment.

[0155] 5C depicts a flowchart of one variation of a treatment planning method (590) that includes calculating a treatment plan fluence map (and / or an ejection filter such as any described herein) for all of the patient target regions (591), calculating a dose distribution map based on the treatment plan fluence map (592), generating a composite image including the dose distribution map overlaid on a patient anatomical image including one or more of the patient target regions (593), receiving user (e.g., clinician, dosimetrist) input regarding shifting the dose on the dose distribution map (594), and calculating an updated treatment plan fluence map based on the dose shift entered by the user (595). Fluence map optimization after the dose shift may be optional.

[0156] In some treatment planning methods, dose variance (aka delta dose) may be used as a constraint for optimizing the treatment plan fluence map. A minimum or maximum allowable dose variance may be selected as the constraint. For example, setting a maximum dose variance as a treatment plan fluence map optimization constraint may help reduce the width of the bDVH while maintaining a default confidence interval (e.g., CI=95%). FIG. 6 illustrates a treatment planning method that includes setting a dose variance as a constraint for generating a treatment plan fluence map. The method (670) includes planning (671) a treatment plan with one or more specified uncertainty vectors (e.g., biological activity, setup position error, etc.) and determining a maximum allowable dose variance D of the uncertainty vector, which may be determined based on the type of uncertainty. plan and selecting (672) a maximum allowable dose variance D. planOptimize the treatment plan fluence map with (673) and use the CI to calculate the bDVH that describes the likelihood of a treatment day dose match falling within the bDVH boundary, and the resulting dose variance D actual Evaluating the actual and determining (674) whether D is acceptable. actual If D is deemed acceptable, the method may include calculating (676) a final dose for the treatment plan and approving (677) the dose variance for the treatment plan. actual If D is not acceptable, the method may include determining (678) how to adjust the dose distribution. In some variations, the method (670) may include determining how to increase the acceptable dose distribution and adjust the dose distribution to the initial D. plan New dose dispersion D larger than plan In some variations, the method (670) may include setting (559) the initial D plan New dose dispersion D larger than plan The method (670) may include setting (580) D plan After is adjusted, the updated dose variance D plan 'Optimizing treatment plans with constraints (681) and D plan 'Selecting a geometry that may be more or less sensitive to dose dispersion based on constraint values, and then creating a new D actual and determining whether the dose variance is acceptable (674). The evaluation and calculation of dose variance (674-681) may be repeated until an acceptable dose variance is calculated.

[0157] Multi-target location matching method The method for virtual registration shifts the planned fluence map for the patient target area to reflect the current / real-time location of the patient target area during treatment. During treatment planning, a set of shift-invariant ejection filters calculated based on the planned registration reference points and the desired dosimetry objectives can be calculated, and in a treatment session, the shift-invariant ejection filters can be used to calculate the delivery fluence that results in the delivery of the dose to the patient treatment area. The method for virtual registration can include selecting a registration reference point corresponding to the planned registration reference point. For example, if the planned registration reference point is the center of the patient target area, during registration, the registration reference point should also be selected as the center of the patient target area to be reflected in the registration image. Then, a registration function (such as a delta function, a Gaussian function, a truncated Gaussian function, etc.) based on the selected registration reference point can be calculated. For example, the location matching function can be a delta function, which can be an impulse function centered on the location matching reference point, or the location matching function can be a Gaussian function with a width (σ) selected during treatment planning, and the mean value (μ) is centered on the location matching reference point. The delivery fluence for every injection position of the therapeutic radiation source (which can be predetermined by treatment planning) can be calculated by convolving the projection of the delta function at that injection position with the projection of the shift-invariant injection filter at that injection. The delivery fluence for every injection position of that patient target area can then be segmented into a radiation therapy system machine command for radiation delivery.

[0158] FIG. 7A depicts a flowchart representation of one variation of a method for virtual registration for SBRT / IMRT delivery. This method may be used for virtual registration of a single patient target region or multiple patient target regions, and may be used at the beginning of a treatment session or multiple times throughout a treatment session. In some variations, a treatment plan may include multiple treatment areas, each having one or more patient target regions. The patient may be physically set up / registered once to a treatment area, and each of the patient target regions within the treatment area may be virtually registered. In some variations where groups of patient target regions are defined during treatment planning, each group may share a single registration reference point and be registered together. The method (700) may include acquiring one or more registration images of one or more patient target regions (702), selecting registration reference points in the acquired images for each of the patient target regions (704), where the registration reference points correspond to planned registration reference points selected during treatment planning, calculating a registration function (e.g., delta, Gaussian, truncated Gaussian, etc.) from the registration reference points for each patient target region, calculating a projection of the registration function onto each therapeutic radiation source (706), and calculating a fluence for delivery to each patient target region for each injection position by convolving the corresponding registration function projection with a shift-invariant injection filter derived based on the planned registration reference points (708). As mentioned above, in some variations, the fluence for delivery to each injection position of the therapeutic radiation source may be calculated by convolving the projection of the registration function at each injection position with the injection filter. Optionally, the method (700) may include proceeding with radiation delivery (i.e., emitting a delivery fluence to each patient target region using a therapeutic radiation source) (710). A shift-invariant ejection filter may be calculated during treatment planning based on (e.g., centered on) the planned localization reference point. In some variations, the localization function may be a delta function, and the shift-invariant ejection filter calculated during treatment planning may represent a fluence map (e.g., planned fluence map) centered on the planned localization reference point.In this example, calculating fluence for delivery (708) may include convolving the calculated delta function (centered on the selected registration reference point) with a shift-invariant ejection filter, resulting in a delivery fluence map that is a shift of the planned fluence map. In some variations, the radiation therapy system may segment the delivery fluence map into machine instructions in real time, i.e., minutes or seconds before radiation delivery. The patient target region to be registered may be included in a single registration image, or may be included in multiple registration images acquired at the beginning of a treatment session and / or throughout the 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. These images may be separate images acquired at separate times or at the same time, or may be sub-regions of a single image. The planned registration reference point may be the treatment isocenter, but in some variations, the planned registration reference point may not be the treatment isocenter, but may be any point selected by the user. The registration reference point may be specified by coordinates. The registration function used to register the patient target region may be an impulse function or a peak or pixel centered on a selected registration reference point, as previously described. The method (700) may be used with any of the treatment planning methods of Figures 1-4, e.g., the method of Figures 1A, 1B.

[0159] FIG. 7B depicts a flowchart representation of one variation of a method for virtual registration for BgRT delivery to one or more patient target regions. Virtual registration for BgRT patient target regions includes adjusting a location ROI based on an offset between a planned registration reference point and a registration reference point selected during a treatment session. The method (720) may include acquiring one or more registration images of one or more patient target regions (722), selecting a registration reference point in the acquired images for each of the patient target regions (724), where the registration reference point corresponds to a planned registration reference point selected during treatment planning, calculating a spatial offset based on a shift between the selected registration reference and the planned registration reference positioning (726), and shifting a boundary of the planned region of interest (ROI) based on the calculated spatial offset (728). In some variations, shifting a boundary of the planned region of interest (ROI) includes applying a rotation and shift to the planned region of interest by a roll correction factor φ that represents a rotational translation of the registration reference point relative to the planned registration reference point. The method (720) may further include acquiring imaging data, spatially masking (e.g., filtering) the imaging data using the shifted region of interest (730), calculating a fluence for delivery to each patient target region at each injection position of the therapeutic radiation source by convolving a projection of the acquired imaging data with a corresponding shift-invariant injection filter (732), and proceeding with radiation delivery (i.e., emitting a delivery fluence to each patient target region using the therapeutic radiation source) (734). The acquired imaging data (730) may include PET imaging data (e.g., positron annihilation emission pathway, LOR), x-ray imaging data, MRI imaging data, ultrasound imaging data, optical imaging data (e.g., from a camera), etc.Calculating the delivery fluence for a particular injection location (732) may include projecting acquired spatially masked imaging data onto that injection location and convolving the imaging data projection with an injection filter for that injection location and target region. The injection filter may be one of the injection filters calculated during treatment planning (e.g., using the method of FIG. 1B). In variations where a roll correction factor is applied to the planned region of interest, calculating the fluence for delivery (732) may include convolving the set of injection filters with a roll correction factor φ, and in some variations may include shifting the ROI (e.g., as described and depicted in FIG. 34) as described above. The method (720) may be used with any of the treatment planning methods of FIGS. 1-4, e.g., the methods of FIGS. 1A, 1B.

[0160] FIG. 8A depicts a flow chart representation of one variation of a method for mosaic multi-target registration. This method may be used at the beginning of a treatment session (e.g., to register / register all of the patient target regions) or multiple times throughout a treatment session (e.g., to sequentially register / register the patient target regions). The method (800) may include acquiring one or more registration images of one or more patient target regions (802), dividing a treatment plan fluence map into one or more fluence map subregions according to a perimeter around each patient target region defined during the treatment plan (804), and shifting each of the fluence map subregions (806) such that a high fluence region co-localizes with the corresponding patient target region of the high fluence region. Shifting the fluence map subregions (806) may be performed using the virtual registration method described herein (e.g., selecting a registration reference point for each of the patient target regions, calculating a delta function based on the registration reference point, and convolving the delta function with a shift-invariant ejection filter). Alternatively or additionally, shifting the fluence map sub-regions (806) may be performed by shifting radiation therapy system machine instructions (eg, MLC, gantry, linac, jaws, etc.).

[0161] Optionally, some variations of the method (800) may include calculating a dose for each of the patient target regions based on the shifted 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 on a display device (808). Optionally, the method (800) may include proceeding with radiation delivery (i.e., using a therapeutic radiation source to emit a delivered fluence to each patient target region) (810). In some variations, the radiation therapy 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 regions to be registered may be included in a single registered image, or may be included in multiple registered images acquired at the beginning and / or throughout a treatment session, as described above. The method (800) may be used in conjunction with any of the treatment planning methods of FIGS. 1-4, for example, the method of FIG.

[0162] 8B depicts a flowchart representation of one variation of a method for mosaic multi-target registration, including shifting or adjusting the patient table. In some methods, the patient setup may include adjusting the patient table orientation (e.g., roll, pitch, yaw, xyz translation, etc.) based on the registration image and the treatment planning image. This method may be used at the beginning of a treatment session (e.g., to register / register all of the patient target regions) or multiple times throughout the treatment session (e.g., to sequentially register / register patient target regions). The method (820) may include acquiring one or more registration images of one or more patient target regions (822), dividing the treatment planning fluence map into one or more fluence map subregions according to a perimeter around each patient target region defined during the treatment planning (824), calculating a patient table position shift vector for each fluence map subregion based on the registration image and the treatment planning image (826), shifting the fluence map subregions such that, for each patient table position, a high fluence region colocalizes with the corresponding patient target region of the high fluence region (828), and calculating the fluence for each patient target region at each patient table position shift vector (830). Shifting the fluence map subregions (828) may be performed using a virtual registration method described herein (e.g., selecting a registration reference point for each of the patient target regions, calculating a delta function based on the registration reference point, and convolving the delta function with a shift-invariant injection filter). Alternatively or additionally, shifting the fluence map subregion (828) may be performed by shifting radiation therapy system machine instructions (eg, MLC, gantry, linac, jaws, etc.).

[0163] Optionally, some variations of the method (820) may include calculating a dose for each of the patient target regions based on the shifted 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 on a display device (832). Optionally, the method (820) may include proceeding with radiation delivery (i.e., using a therapeutic radiation source to emit a delivered fluence to each patient target region) (834). In some variations, the radiation therapy 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 regions to be registered may be included in a single registered image, or may be included in multiple registered images acquired at the beginning and / or throughout a treatment session, as described above. The method (820) may be used in conjunction with any of the treatment planning methods of FIGS. 1-4, for example, the method of FIG.

[0164] 9 depicts a flowchart representation of one variation of a method for isolated multi-target registration. The method (900) may include acquiring one or more registration images of one or more patient target regions (902), each patient target region having a separate individual treatment plan including a set of treatment plan parameters including a set of shift-invariant ejection filters, selecting a registration reference point for each patient target region and calculating a delivery fluence map for each target region using a virtual registration method (e.g., calculating a delta function based on the registration reference points and convolving the delta function with the shift-invariant ejection filters to obtain a delivery fluence map for each patient target region) (904), and calculating a cumulative fluence map by combining the delivery fluence maps for all patient target regions and calculating a dose for each of the patient target regions (906). The method (900) may include evaluating (908) whether dose targets for all patient target regions have been met and / or whether high fluence areas of the individual delivered fluence maps are sufficiently separated from one another (i.e., not co-localized with other high fluence areas). If dose targets for all patient target regions have been met and / or high fluence areas of the individual delivered fluence maps are sufficiently separated from one another, the method (900) may include proceeding with radiation delivery (912), which may include segmenting (914) one or more of the following: (a) the individual fluence maps for each patient target region, and / or (b) the cumulative fluence map into radiation therapy system instructions. The method (900) may include generating (916) a visual and / or audio notification if dose targets for all patient target regions have not been met and / or high fluence areas of the individual delivered fluence maps are not sufficiently separated from one another. The user may optionally be presented with dose calculation data and / or DVH curves so that the user may evaluate the next course of action. In some variations, the radiation therapy 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 registered may be included in a single registered image, or may be included in multiple registered images acquired at the beginning and / or throughout a treatment session, as described above. The method (900) may be used with any of the treatment planning methods of Figures 1-4, such as the method of Figures 3A-3B.

[0165] FIG. 10 depicts a flow chart representation of one variation of a method for isolated multi-target registration. The method (1000) may include acquiring one or more registration images of one or more patient target regions (1002), positioning the patient target regions designated as registration target regions during treatment planning using a treatment isocenter (e.g., a central portion of a therapeutic radiation beam) (1004), and determining whether the remaining patient target regions are located within the boundaries of a spatial ejection filter (e.g., ejection zone, ROI) designated during treatment planning (1006). If the remaining patient target regions are located within the boundaries of the spatial mask or filter (e.g., located within the ROI), the method (1000) may include proceeding with radiation delivery (1002). If the remaining patient target regions are not located within the boundaries of the spatial mask or filter (e.g., not located within the ROI), the method (1000) may include generating a visual and / or audio notification (1010). The user may optionally be presented with location data of the patient target area related to the associated ROI of the patient target area so that the user may evaluate the next course of action. Optionally, one or more of the ROIs of these non-registered target areas may be registered using the virtual registration method described herein. Positioning the registration target area (1004) may use one or more setup and / or registration methods. For example, positioning the registration target area (1004) may include one or more of the following: (a) shifting the radiotherapy system machine command (e.g., MLC, gantry, linac); (b) selecting a registration reference point for the ROI of the registration target area, calculating a delta function based on the registration reference point, and convolving the function (e.g., delta, Gaussian, truncated Gaussian) with the ROI; and / or (c) calculating a patient table position shift vector and adjusting the patient table accordingly. In some variations, radiation delivery may include segmenting one or more of the following into the radiation therapy system instructions: (a) individual fluence maps for each patient target area, and / or (b) a cumulative fluence map.In some variations, the radiation therapy 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 regions to be registered may be included in a single registration image, or may be included in multiple registration images acquired at the beginning of a treatment session and / or throughout the session, as described above. The method (1000) may be used with any of the treatment planning methods of Figs. 1-4, e.g., the method of Fig. 4. For example, each of the multiple patient target regions may have a separate planned registration reference point and set of ejection filters. During a treatment session, the location of the registration reference point for each of the multiple patient target regions may be updated based on the acquired registration images (e.g., the registration reference point may be selected by a user). Separate and / or independent virtual registration of each patient target region based on the updated registration reference point effectively shifts the delivery fluence map to the real-time location of the multiple patient target regions. In this manner, the fluence maps for each of the multiple patient target regions may move relative to each other. For example, in a treatment session involving two or more patient target areas, the radiation delivery method may include performing one or more (e.g., two or more) virtual registrations and shifting the planned fluence map for each of the two or more patient target areas.

[0166] FIG. 11A is a flow chart illustrating a method (100). The method (100) may be used to position a patient for radiation therapy. As shown in FIG. 11A, the method (100) includes acquiring (102) images of a first patient treatment area and a second patient treatment area. In some embodiments, the first patient treatment area and the second patient treatment area may include one or more tumor regions (e.g., patient target regions). For example, in some embodiments, the first patient treatment area may include a first portion of a tumor and the second patient treatment area may include a second portion of a tumor. In some embodiments, the first patient treatment area and the second patient treatment area may each include one or more discrete tumors located in different regions of the patient's body. The acquired images may be images acquired via one or more of, for example, PET, CT, MRI, ultrasound, optical imaging modalities, combinations thereof (e.g., surface tracking / maps, optical CT to predict internal positions based on external surface data), and / or any other suitable method. In some embodiments, one or more images may be acquired prior to or at the beginning of a treatment session, for example using a CT system. In some embodiments, the CT system may be mounted on the same gantry as the radiation source intended for delivery of radiation therapy during the treatment session. In some embodiments, the CT system may be mounted on a gantry separate from the gantry supporting the radiation source. In some embodiments where radiation is delivered at discrete patient table locations or positions (i.e., beam stations), the location of the first patient treatment area may correspond to the location of the first beam station of the therapeutic radiation source, and the location of the second patient treatment area may correspond to the location of the second beam station. In some variations, the first and second treatment areas may overlap, while in other variations, the first and second treatment areas do not overlap.

[0167] A first set of patient position shift vectors may be calculated (104) based on the acquired images of the first patient target region and the treatment planning image (also referred to herein as the "first treatment planning image"). The location of the first treatment area and / or patient target region in the acquired images may be compared to the location of the first treatment area and / or patient target region in the treatment planning image in 2D and / or 3D. For example, in some embodiments, the patient target region may be partitioned into sub-regions (e.g., sub-volumes) that may be represented by voxels, and the coordinates of each voxel in the acquired images may be compared to the coordinates of the corresponding voxel of the patient target region in the treatment planning image. Each of the vectors of the first set of patient position shift vectors may represent a distance and directional difference between the coordinates of a voxel in the acquired images and the coordinates of the corresponding voxel in the treatment planning image. In some embodiments, the directional difference may include a tilt angle. In some embodiments, the first set of patient position shift vectors may be calculated by moving the acquired image relative to the treatment plan image to align or register the first patient target region of the treatment plan image with the first patient target region 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, and the relative position of each voxel of the acquired image may be maintained relative to each other during the movement of the acquired image until the acquired image and the treatment plan image are approximately aligned with the first patient target region (e.g., aligned within a predetermined acceptable tolerance or margin such that there is an acceptable area or percentage of overlap between the first patient target region in the images). The first set of patient position shift vectors may then be calculated based on the location and / or position difference between the acquired image before and after being moved to enhance alignment with the treatment plan image. The first set of patient position shift vectors may reflect the distance and / or direction that each voxel in the acquired images will be translated for acceptable alignment between the first patient target area in the acquired images and the first patient target area in the treatment planning image.Furthermore, the first set of patient position shift vectors may include or correspond to instructions related to a first position and / or a first orientation of the patient (e.g., a first position and / or a first orientation of a surface on which the patient is positioned) such that the first patient target area of ​​the patient is located approximately where the first patient target area was when the treatment planning image was acquired. This may facilitate delivery of therapeutic radiation to the patient target area closer to the treatment plan. In addition, the first set of patient position shift vectors may include information regarding any tilt, pitch, yaw, and / or roll corrections that need to be implemented via positioning of the patient table and / or via adjusting the roll of a gantry to which a radiation source (e.g., a therapeutic radiation source) is coupled (e.g., to correct a gantry injection position) such that the location of the first patient target area approximates the location of the first patient target area in the first treatment planning image.

[0168] In some embodiments, the acquired image of the first treatment area and / or patient target region and the treatment planning image of the first patient target region may each be a two-dimensional image. The acquired two-dimensional image may be compared to the two-dimensional treatment planning image to calculate a first set of patient position shift vectors. In some embodiments, multiple two-dimensional images of the first treatment area and / or 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 to corresponding treatment planning images of the first patient target region acquired along the same orientations or planes. The change in position of the first patient target region along each image plane at each orientation may be used to calculate a first set of patient position shift vectors. For example, the acquired images may include an acquired axial image, an acquired sagittal image, and an acquired coronal image of the first patient target region of the patient. When a patient is lying supine on a surface such as a patient table or treatment couch and oriented such that the patient first encounters the therapeutic radiation source head, the acquired axial image may be taken along the patient's axial plane (e.g., a plane that divides the body into upper and lower portions), the acquired sagittal image may be taken along the patient's sagittal plane (e.g., a plane that divides the patient into right and left portions), and the acquired coronal image may be taken along the patient's coronal plane (e.g., a plane that divides the patient into ventral and dorsal portions). The axial plane is disposed perpendicular to the sagittal plane, and the coronal plane is disposed perpendicular to both the axial and sagittal planes. The treatment planning image may include a treatment planning axial image, a treatment planning sagittal image, and a treatment planning coronal image of the first patient target region of the patient. Thus, 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.

[0169] The amount by which the patient position and / or orientation should be adjusted (e.g., via moving the patient surface and / or rotating the radiation source) along or about each of the X, Y, and Z axes for treatment of the first patient target region may be reflected by a first set of patient position shift vectors based on the difference between the treatment planning image and each acquired image taken in each of the patient's axial, sagittal, and coronal planes. In some embodiments, the X-axis of the patient surface may be parallel to the intersection of the patient's sagittal and coronal planes and may be located in the sagittal plane. The Y-axis of the patient surface may be parallel to the intersection of the patient's axial and coronal planes and may be located in the axial plane. The Z-axis of the patient surface may be parallel to the intersection of the patient's sagittal and axial planes and may be located in the patient's sagittal or axial plane. To determine the first set of patient position shift vectors, each of the acquired images of the first patient target area may be compared to a respective treatment planning image of the first patient target area taken in the same plane to determine a patient distance correction and / or rotation correction (e.g., via a movement of the patient surface and / or a rotation of the radiation source) in the same plane. One or more vectors of the first set of patient position shift vectors may represent a magnitude and a direction by which the patient surface will be moved (e.g., shifted and / or rotated) so that the first patient target area approximates the location of the first patient target area in the treatment planning image. One or more vectors of the first set of patient position shift vectors may also represent a magnitude and a direction by which the radiation source may be moved (e.g., rotated on the gantry) so that the location of the first patient target area approximates the location of the first patient target area in the treatment planning image. In some embodiments, the first set of patient position shift vectors may reflect up to six corrections (i.e., adjustments along or about each of the X-axis, Y-axis, and Z-axis of the patient table). In some embodiments, a DICOM Spatial Registration Object (SRO) may be used to determine each of the six corrections (i.e., adjustments along or about each of the X, Y, and Z axes of the patient table) associated with the first set of patient position shift vectors.

[0170] In some embodiments, the first set of patient position shift vectors may be calculated by moving (e.g., via shifting and / or rotating) each acquired image relative to its respective treatment plan image to align or register the first patient target area and / or patient target region of the treatment plan image with the first patient target region of the acquired image. Each acquired image may be shifted a particular distance and / or rotated a particular amount to improve the alignment of the first patient target region of the treatment plan image with the first patient target region of the acquired image. For example, an image acquired along an axial plane during treatment may be compared to a treatment plan image acquired along an axial plane of the patient to determine the amount of correction required along the horizontal axis (i.e., Y axis) and the vertical axis (i.e., Z axis) of the patient surface (e.g., table or couch) in the axial plane, and the amount of correction required about the gantry roll axis (e.g., about the X axis). Images acquired along the sagittal plane during treatment may be compared to treatment planning images acquired along the patient's sagittal plane to determine the amount of correction needed along the longitudinal (i.e., X-axis) and vertical axes, and the amount of pitch correction (e.g., rotation about the Y-axis) of the patient surface (e.g., table or couch) in the sagittal plane. Images acquired along the coronal plane during treatment may be compared to treatment planning images acquired along the patient's coronal plane to determine the amount of correction needed along the horizontal 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.

[0171] The first set of patient position shift vectors may reflect a required correction of the patient surface along or about each of the X, Y, and Z axes to improve alignment between the first patient target region and the location of the first patient target region at the time of acquisition of the treatment planning images. Thus, in some embodiments, the first set of patient position shift vectors may include at least one patient position shift vector reflecting an adjustment along the X axis of the patient surface based on a vertical difference determined from a comparison of the acquired sagittal image to the treatment planning sagittal image and / or a comparison of the acquired coronal image to the treatment planning coronal image. The first set of patient position shift vectors may include at least one patient position shift vector reflecting an adjustment along the Y axis of the patient surface based on a horizontal difference determined from a comparison of the acquired axial image to the treatment planning axial image and / or a comparison of the acquired coronal image to the treatment planning coronal image. The first set of patient position shift vectors may include at least one patient position shift 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 to the treatment planning axial image and / or a comparison of the acquired sagittal image to the 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 shift vectors may be an average of a lateral difference determined from a comparison of the acquired axial image to the treatment planning axial image and a lateral difference determined from a comparison of the acquired sagittal image to the treatment planning sagittal image.

[0172] With respect to rotation of the patient surface about its axis and / or rotation of the radiation source about its axis, the first set of patient position shift vectors may include a rotation correction of the patient surface about the Y axis of the patient surface based on a comparison of the acquired sagittal image to the treatment planning sagittal image, and / or a rotation correction of the patient surface about the Z axis of the patient surface based on a comparison of the acquired coronal image to the treatment planning coronal image, and / or a rotation correction of the radiation source about the X axis of the radiation source (e.g., the X axis of the gantry having the same extension as the X axis of the patient surface) based on a comparison of the acquired axial image to the treatment planning axial image. For example, shifting or panning the acquired sagittal or coronal image to match the treatment planning sagittal or coronal image may result in a set of patient position shift vectors representing shifts in the X, Y, and Z axes. Tilting the acquired sagittal or coronal image to match the treatment planning sagittal or coronal image may result in a set of patient position shift vectors representing pitch and / or roll position corrections. Thus, the amount by which the patient position and / or orientation should be adjusted along or about each of the X, Y, and Z axes may be reflected by a first set of patient position shift vectors based on the difference between the treatment planning image and each acquired image taken in each of the patient's axial, sagittal, and coronal planes.

[0173] A second set of patient position shift vectors may be calculated (106) based on the acquired images of the second treatment area and / or patient target region, the treatment planning image (also referred to herein as the "second treatment planning image"), and the first set of patient position shift vectors. In some embodiments, the second set of position shift vectors may include a distance and / or direction translation. In some embodiments, the direction translation may include a tilt angle. In some embodiments, similar to that described above with respect to the first set of patient position shift vectors, the second set of patient position shift vectors may be calculated by moving the acquired images relative to the treatment planning images such that the second patient target regions of the treatment planning images are aligned or registered with the second patient target regions of the acquired images. For example, each voxel of the acquired image may be translated along or about the X-axis, Y-axis, and / or Z-axis, and the relative position of each voxel of the acquired image may be maintained with respect to each other during the movement of the acquired image until the acquired image and the treatment planning image improve registration with the second patient target image (e.g., the overlap between the second patient target region in the image is increased or optimized). A second set of patient position shift vectors may then be calculated based on the location and / or position difference between the acquired image before and after being moved to improve registration with the treatment planning image. The second set of patient position shift vectors may reflect the distance and / or direction that each voxel of the acquired image had to be translated to improve registration 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 patient position shift vectors may be calculated based on the first set of patient position shift vectors such that distance and / or direction information included in the second set of patient position shift vectors is relative to the first set of patient position shift vectors rather than to the initial coordinates of the voxels of the acquired images.Thus, the position and / or orientation instructions based on the second set of patient position shift vectors may include or correspond to instructions reciting modifications 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 shift vectors such that the patient is in a second position and / or orientation for irradiation of the second treatment area and / or patient target region.

[0174] The patient may be positioned according to the second set of patient position shift vectors such that the patient is transitioned from the first location to the second location. For example, the therapeutic radiation source may be deactivated such that the first patient target area is not irradiated by the therapeutic radiation source, and then the patient may be positioned according to the second set of patient position shift vectors. Positioning the patient according to the second set of patient position shift vectors may include moving a radiotherapy patient table 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 shift vectors. The therapeutic radiation source may then be activated such that the second patient target area is irradiated. In some embodiments, for beam station-based delivery, the patient may be positioned according to a first set of patient position shift vectors at a first location associated with a first beam station during irradiation, and the patient may be positioned according to a second set of patient position shift vectors during a patient table transition between a first location associated with the first beam station and a second location associated with a second beam station (e.g., a second beam station adjacent to the first beam station).

[0175] In some embodiments, the method may include not only defining a first patient target area and a second patient target area, but also defining any suitable number of target areas, acquiring images of each of the target areas, and positioning the patient based on a position shift vector as described above based on the first patient target area and the second patient target area. For example, for beam station-based delivery, the method may include defining multiple patient target areas, each of which may span multiple beam stations. In some variations, there may be as many patient target areas as there are beam stations. Images may be acquired from each of the patient target areas, and a set of position shift vectors associated with each defined patient target area may be generated as described above. Each patient target area and the associated set of position shift vectors may be associated with a particular beam station. While the patient and / or the patient table transition to a location associated with each respective beam station, the patient may be positioned based on the set of position shift vectors associated with that beam station. In some embodiments, a defined target region (and associated set of patient position shift vectors) may be associated with multiple beam stations such that the patient is positioned based on the set of position shift vectors and does not have to be repositioned as the patient table passes through a sequence of two or more beam stations. Thus, the number of defined target regions (and associated respective sets of patient position shift vectors) may be less than or equal to the number of beam stations.

[0176] In addition, the second set of patient position shift vectors may include information regarding any tilt, pitch, yaw, and roll corrections that need to be implemented via movement of the patient table and / or via adjustment of the roll of the gantry to which the radiation source is coupled (e.g., correcting the gantry injection position) to improve positional alignment of the second patient target area with the location of the second patient target area in the second treatment planning image.

[0177] In some embodiments, similar to that described above with respect to the first set of patient position shift vectors, multiple two-dimensional images of the second treatment area and / or 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 to corresponding treatment planning images of the second patient target region 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 two-dimensional images acquired from the first patient target region to calculate the first set of patient position shift vectors. The changes in position of the second patient target region along each image plane at each orientation may be used to calculate the second set of patient position shift vectors. 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 is lying supine on a surface such as a patient table or treatment couch and oriented such that the patient encounters the therapeutic radiation source head first, the acquired axial image may be taken along the patient's axial plane (e.g., a plane that divides the body into upper and lower portions), the acquired sagittal image may be taken along the patient's sagittal plane (e.g., a plane that divides the patient into right and left portions), and the acquired coronal image may be taken along the patient's coronal plane (e.g., a plane that divides the patient into ventral and dorsal portions). The axial plane is disposed perpendicular to the sagittal plane, and the coronal plane is disposed perpendicular to both the axial and sagittal planes. The treatment planning image may include a treatment planning axial image, a treatment planning sagittal image, and a treatment planning coronal image of the patient's second patient target region. Thus, 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.

[0178] The amount by which the patient position and / or orientation should be adjusted (e.g., via moving the patient surface and / or rotating the radiation source) along or about each of the X, Y, and Z axes for treatment of the second patient target region may be reflected by a second set of patient position shift vectors based on the difference between the treatment planning image of the second patient target region and each acquired image of the second patient target region taken in each of the patient's axial, sagittal, and coronal planes. In some embodiments, the X-axis of the patient surface may be parallel to the intersection of the patient's sagittal and coronal planes and may be located in the sagittal plane. The Y-axis of the patient surface may be parallel to the intersection of the patient's axial and coronal planes and may be located in the axial plane. The Z-axis of the patient surface may be parallel to the intersection of the patient's sagittal and axial planes and may be located in the patient's sagittal or axial plane. To determine the second set of patient position shift vectors, each of the acquired images of the second patient target area may be compared to a respective treatment planning image of the second patient target area taken in the same plane to determine a patient distance correction and / or rotation correction (e.g., via a movement of the patient surface and / or a rotation of the radiation source) in the same plane. One or more vectors of the second set of patient position shift vectors may represent a magnitude and a direction by which the patient surface will be moved (e.g., shifted and / or rotated) so that the second patient target area approximates the location of the second patient target area in the treatment planning image. One or more vectors of the second set of patient position shift vectors may also represent a magnitude and a direction by which the radiation source may be moved (e.g., rotated on the gantry) so that the location of the second patient target area approximates the location of the second patient target area in the treatment planning image. In some embodiments, the second set of patient position shift vectors may reflect up to six corrections (i.e., an adjustment amount along or about each of the X-axis, Y-axis, and Z-axis of the patient table). In some embodiments, a DICOM Spatial Registration Object (SRO) may be used to determine each of the six corrections (i.e., adjustments along or about each of the X, Y, and Z axes of the patient table) associated with the second set of patient position shift vectors.

[0179] In some embodiments, the second set of patient position shift vectors may be calculated by moving (e.g., via shifting and / or rotating) each acquired image relative to its respective treatment plan image to align or register the second patient target area of ​​the treatment plan image with the second patient target area of ​​the acquired image. Each acquired image may be shifted a particular distance and / or rotated a particular amount to improve the alignment of the second patient target area of ​​the treatment plan image with the second patient target area of ​​the acquired image. For example, an image acquired along an axial plane during treatment may be compared to a treatment plan image acquired along an axial plane of the patient to determine the amount of correction required along the horizontal axis (i.e., Y axis) and the vertical axis (i.e., Z axis) of the patient surface (e.g., table or couch) in the axial plane, and the amount of correction required about the gantry roll axis (e.g., about the X axis). Images acquired along the sagittal plane during treatment may be compared to treatment planning images acquired along the patient's sagittal plane to determine the amount of correction needed along the longitudinal (i.e., X-axis) and vertical axes, and the amount of pitch correction (e.g., rotation about the Y-axis) of the patient surface (e.g., table or couch) in the sagittal plane. Images acquired along the coronal plane during treatment may be compared to treatment planning images acquired along the patient's coronal plane to determine the amount of correction needed along the horizontal 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.

[0180] The second set of patient position shift vectors may reflect a required correction of the patient surface along or about each of the X, Y, and Z axes to improve alignment between the second patient target region and the location of the second patient target region at the time of acquisition of the treatment planning images. Thus, in some embodiments, the second set of patient position shift vectors may include at least one patient position shift vector reflecting an adjustment along the X axis of the patient surface based on a vertical difference determined from a comparison of the acquired sagittal image to the treatment planning sagittal image and / or a comparison of the acquired coronal image to the treatment planning coronal image. The second set of patient position shift vectors may include at least one patient position shift vector reflecting an adjustment along the Y axis of the patient surface based on a horizontal difference determined from a comparison of the acquired axial image to the treatment planning axial image and / or a comparison of the acquired coronal image to the treatment planning coronal image. The second set of patient position shift vectors may include at least one patient position shift 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 to the treatment planning axial image and / or a comparison of the acquired sagittal image to the treatment plann...

Claims

[Claim 1] The invention described in this specification.

Images