Radiotherapy planning apparatus and method

Abstract

The invention relates to a radiotherapy planning apparatus and method. When optimizing a radiation therapy plan for a particular patient using a particular radiation therapy platform, the radiation therapy plan has a plurality of therapy fields wherein the radiation source moves according to a therapy arc, and wherein in at least one of the therapy fields, the radiation source stops at at least one stop point to deliver an additional dose. As part of optimizing the radiotherapy plan, the control circuitry may optimize the rotation of the collimator relative to the at least one stop point.

Description

TECHNICAL FIELD

[0001] The teachings generally relate to treating a planning target volume of a patient with energy according to an energy-based treatment plan, and more particularly, to optimizing an energy-based treatment plan. BACKGROUND

[0002] The use of energy to treat disease is a known area of endeavor in the art. For example, radiation therapy is an important component of many treatment plans for reducing or eliminating unwanted tumors. Unfortunately, the energy applied often cannot distinguish, by itself, between unwanted matter and adjacent tissue, organs, etc., which are desirable or even vital to the continued survival of the patient. Thus, energy such as radiation is often applied in a carefully administered manner to at least attempt to limit the energy to a given target volume. So-called radiation treatment plans often serve this purpose.

[0003] A radiation treatment plan typically includes a specified value for each of various treatment platform parameters during each of a plurality of successive fields. Treatment plans for a radiation treatment process are often generated automatically through a so-called optimization process. As used herein, "optimization" is to be understood to mean improving a candidate treatment plan, without necessarily ensuring that the result of the optimization is in fact the only best solution. Such optimization often includes automatically adjusting one or more physical treatment parameters (often while observing one or more respective limits for these aspects), and mathematically calculating a possible corresponding treatment result (e.g., a dose level) to identify a given set of treatment parameters that represents a good tradeoff between a desired treatment result and avoiding undesirable collateral effects.

[0004] Collimators, including multi-leaf collimators, are often used to shape or otherwise condition a radiation beam. A multi-leaf collimator is composed of a plurality of individual components, referred to as "leaves," formed of a high atomic number material, such as tungsten, which can be independently moved into and out of the path of a radiation therapy beam, thereby selectively blocking (and thus shaping) the radiation beam. Typically, the leaves of a multi-leaf collimator are arranged in pairs, aligned collinearly with one another, and can be selectively moved closer to and farther from one another. A typical multi-leaf collimator has many such pairs of leaves, often as many as twenty pairs, fifty pairs, or even one hundred pairs.

[0005] In some application settings, one or more collimators can be selectively rotated. For example, rotating a radiation beam collimator during radiotherapy can allow for more precise shaping of the radiation beam to match the profile of the target tumor, thereby optimizing dose delivery to the cancerous tissue while better protecting surrounding healthy tissue. By rotating the collimator, the clinician can also create non-coplanar beam arrangements, which can further minimize exposure to sensitive structures and improve consistency of treatment. In addition, collimator rotation can be used in conjunction with other techniques, such as intensity modulated radiation therapy (IMRT), to modulate the intensity of the radiation beam across the treatment field, thereby enabling a more customized dose distribution. BRIEF DESCRIPTION OF DRAWINGS

[0006] The above needs are at least partially met through provision of the radiotherapy planning device and method described in the following detailed description, when considered in relation to the figures described below.

[0007] Figure 1 including block diagrams configured in accordance with various embodiments of these teachings;

[0008] Figure 2 including flow diagrams configured in accordance with various embodiments of these teachings; and

[0009] Figure 3 including flow diagrams configured in accordance with various embodiments of these teachings.

[0010] The elements in the figures are illustrated for simplicity and clarity and have not necessarily been drawn to scale. For example, the dimensions and / or relative positioning of some of the elements in the figures can be exaggerated relative to other elements to help to improve understanding of various embodiments of the present teachings. Also, certain DETAILED DESCRIPTION

[0011] In general, these various embodiments can be used to facilitate optimizing a radiotherapy plan for a particular patient using a particular radiotherapy platform, the radiotherapy plan having a plurality of treatment fields in which a radiation source moves according to a treatment arc, and in which, in at least one of the treatment fields, the radiation source stops at at least one stopping point to deliver an additional dose.

[0012] In this application setting, as part of optimizing the radiation therapy plan, the control circuit can optimize the collimator rotation relative to the at least one stop point.

[0013] By one approach, the rotatable collimator comprises a multi-leaf collimator, in which case optimizing the collimator rotation relative to the at least one stop point can comprise maximizing optimal leaf positioning of the multi-leaf collimator.

[0014] By one approach, optimizing the collimator rotation can be performed prior to starting a dose optimization iteration (and, if desired, completed).

[0015] By one approach, optimizing the collimator rotation relative to the at least one stop point can comprise optimizing the collimator rotation without physical constraints. In this case, if desired, optimizing the collimator rotation without physical constraints can further comprise optimizing by imposing a weighting that enhances collimator angles at the at least one stop point. By another approach, optimizing the collimator rotation relative to the at least one stop point can comprise optimizing the collimator rotation with physical constraints involving at least one of: collimator rotation values at static angles, collimator rotation values at arc stop positions, start / end arc positions of beam-off sectors, and / or collimator rotation values at arc start positions.

[0016] By one approach, optimizing the collimator rotation relative to the at least one stop point can comprise optimizing the collimator rotation such that patient target volume width in a direction coincident with collimator leaves is minimized. By another approach, instead of or in combination with the above approach, optimizing the collimator rotation relative to the at least one stop point can comprise optimizing the collimator rotation to favor orienting collimator leaves to produce enhanced effective radiation modulation of a target volume.

[0017] By one approach, the teachings will apply to optimizing the collimator rotation relative to the at least one stop point by accessing a two-dimensional matrix comprising a cost map having a first axis corresponding to gantry angles and a second axis corresponding to collimator angles, such that cells in the two-dimensional matrix store costs corresponding to given combinations of gantry and collimator angles, such that collimator angle constraints for static gantry angles and arc start and stop angles are modeled as disabled or high-cost cells. Once so configured, the teachings will apply to determining an optimal path through the two-dimensional matrix for at least the most applicable gantry angles.

[0018] The teachings will then apply to outputting a final optimized radiation therapy plan, and administering radiation therapy to a particular patient using the optimized radiation therapy plan.

[0019] Many prior art methods ignore at least some of the requirements of radiation therapy planning in which the gantry is to be stopped (at least once, and possibly multiple times) during a given radiation therapy session to deliver additional doses. The present teachings can handle multiple fields at the same time, and the resulting collimator rotation trajectories can be different. This is in sharp contrast to some prior art methods, which can often result in scenarios in which two or more arcs have the same collimator rotation, which can be counter to established clinical practice.

[0020] These and other benefits can become clearer upon a thorough review of the following detailed description. Now refer to the drawings, and particularly Figure 1 An illustrative apparatus 100 compatible with many of these teachings is first introduced.

[0021] In this particular example, the enabled apparatus 100 includes a control circuit 101. As a "circuit," the control circuit 101 thus includes a structure that contains at least one (and usually many) electrically conductive paths (such as paths constructed of an electrically conductive metal such as copper or silver), which paths transport electrical current in an ordered manner, and which paths will usually also include corresponding electrical components (including passive components such as resistors and capacitors and active components such as any of a variety of semiconductor-based devices) to allow the circuit to implement the control aspects of these teachings.

[0022] Such a control circuit 101 can include a fixed-purpose, hard-wired hardware platform (including but not limited to an application-specific integrated circuit (ASIC) which is an integrated circuit designed for a particular use, rather than for general use, a field-programmable gate array (FPGA), etc.), or can include a hardware platform that is partially or entirely programmable (including but not limited to a microcontroller, a microprocessor, etc.). These architectural alternatives to such structures are well-known and readily understood in the art, and need not be described further here. The control circuit 101 is configured (e.g., through the use of corresponding programming, well-known to those skilled in the art) to perform one or more of the steps, actions, and / or functions described herein.

[0023] It will be appreciated that the control circuit 101 can include a single integrated platform, or can include multiple such circuits that cooperate with one another.

[0024] The control circuit 101 is operably coupled to a memory 102. The memory 102 can be integrated to the control circuit 101, or can be physically all or partially separate from the control circuit 101 as desired. The memory 102 can also be local with respect to the control circuit 101 (where, for example, both share a common circuit board, frame, power supply, and / or housing), or can be partially or entirely remote from the control circuit 101 (e.g., the memory 102 is physically located in another facility, metropolitan area, or even country as compared to the control circuit 101). As with the control circuit 101, the memory 102 can comprise a single structure, or can comprise multiple storage platforms that collectively comprise the "memory" of the device 100.

[0025] In addition to the following information, such as optimization information for a particular patient and information about a particular radiation treatment platform as described herein, the memory 102 can also, for example, non-transitorily store computer instructions that, when executed by the control circuit 101, cause the control circuit 101 to function as described herein. (As used herein, such a reference to "non-transitory" should be understood to refer to the non-transient nature of the stored content (and thus excludes the case where the stored content merely forms a signal or wave) rather than the volatileness of the storage medium itself, and thus includes non-volatile memory (such as read-only memory (ROM)) and volatile memory (such as dynamic random access memory (DRAM)).)

[0026] By one approach, the control circuit 101 is also operably coupled to a user interface 103. The user interface 103 can include any of a variety of user input mechanisms (such as, but not limited to, keyboards and keypads, cursor control devices, touch-sensitive displays, voice recognition interfaces, gesture recognition interfaces, etc.) and / or user output mechanisms (such as, but not limited to, visual displays, audio sensors, printers, etc.) to facilitate receiving information and / or instructions from a user and / or providing information to a user.

[0027] If desired, the control circuit 101 can also be operably coupled to a network interface (not shown). So configured, the control circuit 101 can communicate with other elements (including elements internal and external to the device 100) via the network interface. Network interfaces (including wireless and non-wireless platforms) are well known in the art and thus need not be set forth in detail here.

[0028] By one approach, a computed tomography device 106 and / or other imaging device 107 known in the art can provide any desired portion or all of the imaging information related to the patient.

[0029] In this illustrative example, control circuitry 101 is configured to ultimately output an optimized energy-based treatment plan (e.g., an optimized radiotherapy plan 113). This energy-based treatment plan typically includes specified values ​​for each of various treatment platform parameters during each of multiple successive exposure fields. In this case, the energy-based treatment plan is generated through an optimization process, examples of which will be further provided herein.

[0030] In one method, control circuitry 101 can be operatively coupled to an energy-based treatment platform 114 configured to deliver therapeutic energy 112 to a corresponding patient 104, having at least one treatment volume 105 and one or more organs at risk (in...) according to an optimized energy-based treatment plan 113. Figure 1 (The organs at risk are represented by 108 and 109 from the first to the Nth). These teachings are generally applicable to any of a variety of energy-based therapeutic platforms / devices. In a typical application setting, the energy-based therapeutic platform 114 includes an energy source, such as a radiation source 115 of ionizing radiation 116.

[0031] By means of a method, a radiation source 115 can be selectively moved along an arcuate path via a gantry (wherein, during treatment, the path at least partially includes the patient). The arcuate path may, as desired, comprise a complete or near-complete circle. By means of a method, control circuitry 101 controls the movement of the radiation source 115 along the arcuate path, and can accordingly control when the radiation source 115 begins to move, stops moving, accelerates, decelerates, and / or the speed at which the radiation source 115 travels along the arcuate path. Furthermore, these teachings apply to radiotherapy platforms where the radiation source can be stopped at at least one stop point during a given radiotherapy procedure to deliver additional doses as required by the corresponding radiotherapy plan.

[0032] As an illustrative example, radiation source 115 may include, for example, an X-ray source based on a radio frequency (RF) linear particle accelerator (linear accelerator). A linear accelerator is a particle accelerator that greatly increases the kinetic energy of charged subatomic particles or ions by subjecting charged particles to a series of oscillating potentials along a linear beamline, which can be used to generate ionizing radiation (e.g., X-rays) 116 and high-energy electrons.

[0033] A typical energy-based treatment platform 114 may also include one or more support devices 110 (e.g., a bed) for supporting the patient 104 during treatment, one or more patient fixation devices 111, a gantry or other movable mechanism to allow selective movement of the radiation source 115, and one or more energy shaping devices. These beam shaping devices 117 may include grippers, multi-leaf collimators, etc., and are used to provide selective energy shaping and / or energy conditioning as desired. One or more of these beam shaping devices 117 may be selectively rotated during radiotherapy.

[0034] In a typical application setting, this document assumes that the patient support device 110 can be selectively controlled by the control circuitry 101 to move in any direction (i.e., any X, Y, or Z direction) during an energy-based treatment procedure. Since the aforementioned components and systems are well known in the art, further elaboration on these aspects is not provided herein unless relevant to the description.

[0035] Now for reference Figure 2 The process 200, which can be performed, for example, in conjunction with the application settings described above (and more specifically via the control circuit 101 described above), will be described. Generally, this process 200 is used to facilitate the generation of an optimized radiotherapy plan 113, thereby facilitating the use of a specific radiotherapy platform to treat a specific patient with radiotherapy according to the optimized radiotherapy plan.

[0036] As indicated by reference numeral 201 in the accompanying drawings, in an illustrative example, process 200 assumes the use of a specific radiotherapy platform to optimize a radiotherapy plan for a specific patient, the radiotherapy plan having multiple treatment fields, wherein radiation sources move according to a treatment arc, and wherein, in at least one of the treatment fields, the radiation sources stop at at least one stop point to deliver an additional dose.

[0037] At block 202, the control circuitry optimizes the radiotherapy plan. In addition to other functions representing this optimization, according to process 200, optimizing the radiotherapy plan also includes optimizing the rotation of the collimator relative to at least one of the aforementioned stopping points. By way of a simple illustrative example, if the radiation source stops at three different stopping points to deliver an additional dose, then process 200 can provide optimized rotation of the collimator relative to each stopping point.

[0038] For illustrative purposes and not intended to imply any limitation in these respects, this specification assumes that the rotatable collimator comprises a rotatable multi-leaf collimator. Therefore, optimizing the rotation of the collimator relative to at least one stop point would involve maximizing the optimal leaf positioning of the multi-leaf collimator. One method for optimizing the rotation of the collimator relative to at least one stop point may include optimizing the collimator rotation such that the patient target volume is minimized in the direction coinciding with the collimator leaflets. In general, these teachings can be used to optimize collimator rotation to facilitate the orientation of the collimator leaflets, thereby producing an enhanced and effective radiomodulation of the target volume.

[0039] Optimization can include various steps and activities. A common activity is optimizing the dose via an iterative optimization process. By way of doing so, these teachings will be applicable to optimizing radiotherapy planning by optimizing collimator rotation before initiating any such dose optimization iterations.

[0040] One method allows for optimized collimator rotation without imposing any physical constraints. In this case, these teachings can be applied to optimize collimator rotation by applying a weight that enhances the collimator angle at at least one stopping point.

[0041] Alternatively, optimizing the collimator rotation relative to at least one stopping point can include optimizing the collimator rotation under physical constraints. These teachings will apply to any of the various physical constraints considered. Examples include, but are not limited to, one or more of the following: collimator rotation values ​​at static angles, collimator rotation values ​​at arc-stopping positions, the start / end arc positions of the beam-closing sector, and / or collimator rotation values ​​at arc-starting positions.

[0042] For reference only Figure 3 The figure illustrates the process 300 for optimizing the rotation of the collimator relative to at least one stop point.

[0043] At block 301, control circuitry 101 accesses a two-dimensional matrix including a cost map having a first axis corresponding to the rack angle and a second axis corresponding to the collimator angle. With this configuration, the cells in the two-dimensional matrix store the cost corresponding to a given combination of rack angle and collimator. Therefore, collimator angle constraints for static rack angle, arc start angle, and arc stop angle can be modeled as disabled or high-cost cells.

[0044] At box 302, control circuit 101 can then determine the optimal path through the two-dimensional matrix. Since there may not be a truly optimal path for every applicable rack angle, these teachings will be applied in a way to determine the optimal path through the two-dimensional matrix in the sense that the sum of costs at each angle is optimal.

[0045] Refer again Figure 2 At box 203, control circuit 101 outputs an optimized radiotherapy plan. At optional box 204, the specific radiotherapy platform described above can be used to administer radiotherapy to the specific patient using the optimized radiotherapy plan generated by the above steps.

[0046] Now, more details consistent with these teachings will be presented. It should be understood that the specific details of these examples are again intended for illustrative purposes and are not intended to imply any particular limitation regarding these teachings.

[0047] For illustrative purposes, this specification assumes that the trajectory defining how the gantry rotates is part of the input, provided by the user or by another independent algorithm. The same applies to other aspects of the input geometry, such as the patient support surface and isocenters. The input can be presented as a sequence of control points. Control points are specific locations or angles at which the radiation beam is turned on or off during treatment. Control points are typically used to help shape the radiation beam and optimize dose distribution, thereby targeting the tumor while protecting surrounding healthy tissue.

[0048] In this example, the output is a sequence of control points where the collimator values ​​have been optimized and all other values ​​remain unaffected. The resulting optimized collimator rotation will result in dynamic collimator rotations for multiple portions of the field for rack rotation, and statically optimized collimator angles for control points where rack rotation is paused.

[0049] This specification also assumes the existence of a separate planning optimization algorithm that optimizes blade position to provide the best possible planned dose based on user requirements (referred to herein as the "blade optimizer"). The basic idea of ​​the direct method described herein is to identify the collimator angle that allows the blade optimizer to achieve better results.

[0050] Optimize collimator for a single field

[0051] Cost function for optimizing collimator rotation

[0052] Collimator rotation can be optimized by minimizing a cost function that depends on the control point geometry and patient anatomy. In the following description, the XY coordinate system describes the beam field of view (BEV) such that the X-axis is aligned with the direction of blade movement, and the Y-axis is orthogonal to the X-axis and related to the number of blades. The target is projected onto the BEV, and the projection is clipped considering the maximum possible aperture of the corresponding grippers(multiple). The size of the projection is described by a discrete volume function V(x, y). Therefore, V(x, y) describes the total target volume projected onto the point (x, y) in the BEV. The effect of collimator rotation can be accounted for by including a rotation parameter α in the volume function, which becomes V(α, x, y); the effect of α is simply to rotate the original projection V(x, y) by α degrees in the BEV.

[0053] The following alternative cost functions can be used individually or in any combination as desired.

[0054] Maximize the number of blades that can reach and regulate the dose in the target. If one assumes the blade thickness is 1, this is equivalent to the range of the target projected onto the Y-axis.

[0055] Not only the range is considered, but also the size of the target projected onto the Y-axis. This cost can be designed to maximize the number of blades that can be adjusted on the target, but it will also further enhance the thicker parts of the target.

[0056] Minimize the target's width in the X direction. Minimizing the target width in the blade's direction of motion tends to minimize the required blade travel. Furthermore, the target's projection in the orthogonal Y direction tends to maximize, thereby further increasing the number of blades available for adjustment.

[0057] Minimize the volume-weighted square width of the target in the X direction. Considering the volume in this way can enhance the target's projection over larger areas.

[0058] Through a method, the cost function can be defined as in

[0059] Alternatively, the definition can be the same, except...

[0060] In another method, the cost is simply the maximum width in the X direction, i.e. For some choices of j and k, the X coordinate must satisfy... .

[0061] Finally, using another method, the geometric mean of the target in the X direction can be defined as... Then, the cost can be calculated as follows:

[0062] Find the optimal collimator rotation for the entire arc

[0063] Using selected metrics, a 2D map (rack, collimator) can be constructed. For each rack value in the input sequence and for each possible collimator angle value, the projection of the target volume into the BEV is calculated. The cost corresponding to the projection is then evaluated and stored in the associated map cell.

[0064] The optimal collimator angle can be simply selected for each rack angle in the input sequence. However, this method does not consider the physical constraints of the arc itself. A well-established trajectory finding method is Dijkstra's algorithm, which identifies the shortest path in a graph. The rack-collimator map can be viewed as a graph where each cell corresponds to a node, and the edge between each cell and its immediate right neighbor is reachable under constraints of maximum collimator rotation speed and maximum rack rotation speed. In this way, Dijkstra's algorithm will provide a collimator trajectory that minimizes the total cost while satisfying the movement constraints.

[0065] Collimator optimized for dynamic fields

[0066] Case 1: Static angle with user-input collimator angle

[0067] These teachings support the following use cases where the user defines a specific collimator angle for each static rack position in a dynamic field, or more generally, defines collimator angles from any subset of input control points.

[0068] For each user-defined rack-collimator pair constraint (g) i , c i These teachings will apply to preventing contact with g i All associated collimator values ​​(c i (Except for). Then, the method can be operated as described.

[0069] Collimator optimized for dynamic fields

[0070] Case 2: Static angle without input constraints

[0071] One approach to this use case, supported by these teachings, is that the user does not define any specific collimator angle for each static rack position. Instead, each static rack position can be assumed to be more important than any other rack angle of the corresponding arc. In this case, static rack angles can be considered high-priority angles, and to ensure near-optimality at these rack positions, cells with relatively high costs at those locations can be prohibited. Constraints can be set loosely enough that transitions between static rack positions do not require excessively abrupt changes in collimator rotation. A prohibited collimator angle for a static rack position can be defined, for example, a cell whose cost exceeds a specified fraction of the average cost of cells with that rack angle. Alternatively, the cost of all cells at a static rack angle can be scaled by a desired priority factor to prioritize the static rack angles without strictly prohibiting any particular collimator angle.

[0072] Optimize multiple fields together

[0073] When a radiotherapy plan involves multiple fields, these teachings will be applied to work in two different modalities depending on the input geometry. Different workflows can be advantageously utilized, as explained below.

[0074] Equivalent geometric field

[0075] Two (or more) fields with the same input geometry (defined here as having the same isocenter, the same patient support surface angle, and the same field opening (typically defined by gripper position)) can be considered a special case. In this setting, these teachings can be applied to generate different collimator angles for the individual fields, since other geometric aspects are identical. In this way, the final planning optimization method can have better dose control.

[0076] To achieve this, when optimizing the second (or other) collimator angle, a penalty can be imposed on map cells that are close to (that is, within the user-defined or default tolerance range) the previously optimized collimator trajectory.

[0077] Collimator redundancy penalty

[0078] These teachings can support the use of different functions to define the penalty applied to each map cell. One approach is to define the penalty for any cell in the map ( , ),make( , The nearest point in the previous trajectory (if a previous trajectory exists) is the point in the current trajectory. The cost for the penalized map cell can be calculated as follows: , = , + ( )

[0079] Some examples of penalty functions can be represented as follows: ( ) = ,when hour ( ) = Where B is a constant, which indicates the baseline value of the penalty.

[0080] In both of the above cases, when The penalty is greatest at the specified time, and decreases as the difference between collimator angles increases.

[0081] exist In the case of B, the penalty can only be applied within the threshold t, and when the threshold is reached, the penalty can be linearly reduced from B to zero, while in other cases it can be evaluated as zero.

[0082] exist In the case of [missing information], the penalty can continue based on the dot product between the collimator angles, and when the values ​​are the same, the penalty can also be evaluated as B. However, the penalty can decrease according to the cosine function, reaching zero when the angle is perpendicular. The principle behind this is that the blade optimizer will have the greatest degrees of freedom to adjust the plan when the collimator angle is perpendicular. In both cases, B is the penalty baseline value calculated based on the existing rack-collimator map (e.g., the average value of the cells) before applying the penalty.

[0083] A higher number of trajectories

[0084] When the number of arc trajectories is high (e.g., four or more), and if the previously described process is applied iteratively, the cost in the map may ultimately be determined by penalties. Since a potential underlying preference might be to keep the original map as the primary cost and use penalties as a secondary criterion, these teachings would apply to penalizing all previously computed trajectories using a budget-based approach. Then, by means of a method that, instead of starting the map from the (k-1)th arc when optimizing the collimator for the k-th arc, these teachings would apply to starting from the original map and penalizing the previous k-1 trajectories, where each trajectory is weighted by a factor a = 1 / (k-1).

[0085] Negative punishment

[0086] If certain preferred trajectories exist, and the process encourages these trajectories to remain close to (rather than distinct from) previously existing trajectories, then these teachings will apply to adding a negative penalty to cells in the map that are close to them. In this case, the effect is that subsequent trajectories will be more likely to follow the same trajectory as those that have been negatively penalized.

[0087] Fields with different geometries

[0088] When two (or more) fields have different input geometries (defined here as differing on at least one of the following axes: isocenter, patient support surface angle, or field opening (typically defined by gripper position)), the collimator for each field can be optimized independently of each other.

[0089] This mode supports the following scenarios.

[0090] When the patient support angle or isocenter axis differs for different fields, these fields have already delivered doses from different directions, so whether the resulting collimator angles differ is usually irrelevant. Furthermore, due to the aforementioned reasons, their BEVs will differ, thus the resulting collimator trajectories are likely to remain different.

[0091] When a user defines different gripper positions for a field, but the rest of the geometry remains the same, the user's intent may be to set up a segmented field where each arc delivers a dose to a different part of the target. In this case, by having no penalty and having the same input geometry, the resulting trajectories can be identical, thus satisfying the user's intent.

[0092] User-defined workflow

[0093] Finally, if desired, instead of automatically detecting whether the geometry is the same as defined in the previous sections, these teachings will support user input that can indicate whether to operate for the case of different collimators for each arc as described above, or for the case without penalty, which may result in the same collimator trajectory.

[0094] Other aspects of the invention are provided by the subject matter of the following clauses (where it should be understood that any one of these clauses may be combined with one or more other clauses as needed).

[0095] Clause 1. A method comprising: using a specific radiotherapy platform to optimize a radiotherapy plan for a specific patient by a control circuit, the radiotherapy plan having multiple treatment fields, wherein a radiation source moves according to a treatment arc, wherein, in at least one of the treatment fields, the radiation source stops at at least one stop point to deliver an additional dose, and wherein optimizing the radiotherapy plan includes optimizing the rotation of a collimator relative to at least one stop point; and outputting the optimized radiotherapy plan.

[0096] Clause 2. The method according to Clause 1, wherein optimizing the radiotherapy plan includes optimizing collimator rotation prior to initiating a dose optimization iteration.

[0097] Clause 3. The method described in Clause 1 or 2, wherein the collimator includes a multi-leaf collimator.

[0098] Clause 4. The method according to Clause 3, wherein optimizing the rotation of the collimator relative to at least one stop point includes maximizing the optimal blade positioning for the multi-leaf collimator.

[0099] Clause 5. The method according to any one of Clauses 1 to 4, wherein optimizing the rotation of the collimator relative to at least one stop point includes optimizing the collimator rotation without physical constraints.

[0100] Clause 6. The method according to Clause 5, wherein optimizing collimator rotation without physical constraints further comprises optimizing by applying a weight that enhances the collimator angle at at least one stopping point.

[0101] Clause 7. The method according to any one of Clauses 1 to 6, wherein optimizing the rotation of the collimator relative to at least one stopping point includes optimizing the collimator rotation under physical constraints, said physical constraints relating to at least one of the following: a collimator rotation value at a static angle; a collimator rotation value at an arc stopping position; and a collimator rotation value at an arc starting position.

[0102] Clause 8. The method according to any one of Clauses 1 to 7, wherein optimizing the rotation of the collimator relative to at least one stop point includes optimizing the collimator rotation such that the width of the patient target volume in the direction coinciding with the collimator blades is minimized.

[0103] Clause 9. The method according to any one of Clauses 1 to 8, wherein optimizing the rotation of the collimator relative to at least one stopping point comprises: accessing a two-dimensional matrix including a cost map having a first axis corresponding to a rack angle and a second axis corresponding to a collimator angle, such that cells in the two-dimensional matrix store costs corresponding to a given combination of rack angles and collimator angles, such that collimator angle constraints for static rack angles and arc start and stop angles are modeled as disabled or high-cost cells; determining an optimal path through the two-dimensional matrix for at least the most suitable rack angle.

[0104] Clause 10. The method according to any one of Clauses 1 to 9, wherein optimizing the rotation of the collimator relative to at least one stop point includes optimizing the collimator rotation to facilitate the orientation of the collimator blades, thereby producing an enhanced and effective radiation modulation of the target volume.

[0105] Clause 11. The method according to any one of Clauses 1 to 10 further includes: administering radiotherapy to a specific patient using an optimized radiotherapy plan.

[0106] Clause 12. An apparatus comprising: control circuitry configured to: optimize a radiotherapy plan for a specific patient using a particular radiotherapy platform, the radiotherapy plan having a treatment field, wherein a radiation source moves according to a treatment arc, wherein, in at least one of the treatment fields, the radiation source stops at at least one stop point to deliver an additional dose, and wherein optimizing the radiotherapy plan includes optimizing the rotation of a collimator relative to the at least one stop point; and outputting the optimized radiotherapy plan.

[0107] Clause 13. The device according to Clause 12, wherein the control circuitry is configured to optimize the radiotherapy plan by optimizing collimator rotation prior to initiating a dose optimization iteration.

[0108] Clause 14. The device described in Clause 12 or 13, wherein the collimator includes a multi-leaf collimator.

[0109] Clause 15. The device according to Clause 14, wherein the control circuitry is configured to optimize the rotation of the collimator relative to at least one stop point by maximizing the optimal blade positioning for the multi-leaf collimator.

[0110] Clause 16. The device according to any one of Clauses 12 to 15, wherein the control circuitry is configured to optimize the rotation of the collimator relative to at least one stop point by optimizing the collimator rotation without physical constraints.

[0111] Clause 17. The device according to Clause 16, wherein the control circuitry is configured to optimize collimator rotation without physical constraints by applying a weighting that enhances the collimator angle for at least one stopping point.

[0112] Clause 18. The device according to any one of Clauses 12 to 17, wherein the control circuitry is configured to optimize the rotation of the collimator relative to at least one stop point by optimizing the collimator rotation under physical constraints, said physical constraints relating to at least one of the following: a collimator rotation value at a static angle; a collimator rotation value at an arc stop position; and a collimator rotation value at an arc start position.

[0113] Clause 19. The device according to any one of Clauses 12 to 18, wherein the control circuitry is configured to optimize the rotation of the collimator relative to at least one stop point by optimizing the collimator rotation such that the width of the patient target volume in the direction coinciding with the collimator blades is minimized.

[0114] Clause 20. The device according to any one of Clauses 12 to 19, wherein the control circuitry is configured to optimize the rotation of the collimator relative to at least one stop point by: accessing a two-dimensional matrix including a cost map having a first axis corresponding to a rack angle and a second axis corresponding to a collimator angle, such that cells in the two-dimensional matrix store costs corresponding to a given combination of rack angles and collimator angles, such that collimator angle constraints for static rack angles and arc start and stop angles are modeled as disabled or high-cost cells; and determining an optimal path through the two-dimensional matrix for at least the most suitable rack angle.

[0115] Clause 21. The device according to any one of Clauses 12 to 20, wherein the control circuitry is configured to optimize the rotation of the collimator relative to at least one stop point by optimizing the collimator rotation to facilitate the orientation of the collimator blades, thereby producing an effective radiation modulation of the target volume.

[0116] Those skilled in the art will recognize that various modifications, alterations, and combinations can be made to the above embodiments without departing from the scope of the invention, and such modifications, alterations, and combinations should be considered within the scope of the inventive concept.

Claims

1. A method comprising: By controlling the circuit: Using a specific radiotherapy platform to optimize a radiotherapy plan for a specific patient, the radiotherapy plan having multiple treatment fields, wherein a radiation source moves according to a treatment arc, wherein in at least one of the treatment fields, the radiation source stops at at least one stop point to deliver an additional dose, and wherein optimizing the radiotherapy plan includes optimizing the rotation of the collimator relative to the at least one stop point; Output an optimized radiotherapy plan.

2. The method of claim 1, wherein optimizing the radiotherapy plan includes optimizing collimator rotation prior to initiating a dose optimization iteration.

3. The method according to claim 1, wherein the collimator comprises a multi-leaf collimator.

4. The method of claim 3, wherein optimizing the rotation of the collimator relative to the at least one stop point comprises maximizing the optimal blade positioning for the multi-leaf collimator.

5. The method of claim 1, wherein optimizing the rotation of the collimator relative to the at least one stop point comprises optimizing the collimator rotation without physical constraints.

6. The method of claim 5, wherein optimizing the collimator rotation without physical constraints further comprises optimizing by applying a weighting that enhances the collimator angle at the at least one stopping point.

7. The method of claim 1, wherein optimizing the rotation of the collimator relative to the at least one stopping point comprises optimizing the collimator rotation under physical constraints, said physical constraints relating to at least one of the following: Collimator rotation value at a static angle; Collimator rotation value at the arc stop position; Collimator rotation value at the starting position of the arc.

8. The method of claim 1, wherein optimizing the rotation of the collimator relative to the at least one stop point comprises optimizing the collimator rotation such that the width of the patient target volume in the direction coinciding with the collimator blades is minimized.

9. The method of claim 1, wherein optimizing the rotation of the collimator relative to the at least one stop point comprises: Access a two-dimensional matrix including a cost map, the cost map having a first axis corresponding to the rack angle and a second axis corresponding to the collimator angle, such that cells in the two-dimensional matrix store the cost corresponding to a given combination of rack angle and collimator angle, such that collimator angle constraints for static rack angle and arc start and stop angles are modeled as disabled or high-cost cells. Determine the optimal path through the two-dimensional matrix for at least the most suitable rack angle.

10. The method of claim 1, wherein optimizing the rotation of the collimator relative to the at least one stop point comprises optimizing the collimator rotation to facilitate the orientation of the collimator blades, thereby producing an effective radiation modulation that enhances the target volume.

11. The method according to claim 1, further comprising: Radiation therapy was administered to the specific patient using an optimized radiation therapy plan.

12. An apparatus comprising: Control circuit, the control circuit being configured to: Using a specific radiotherapy platform to optimize a radiotherapy plan for a specific patient, the radiotherapy plan has a treatment field, wherein a radiation source moves according to a treatment arc, wherein in at least one of the treatment fields, the radiation source stops at at least one stop point to deliver an additional dose, and wherein optimizing the radiotherapy plan includes optimizing the rotation of the collimator relative to the at least one stop point; Output an optimized radiotherapy plan.

13. The device of claim 12, wherein the control circuitry is configured to optimize the radiotherapy plan by optimizing collimator rotation prior to initiating a dose optimization iteration.

14. The device of claim 12, wherein the collimator comprises a multi-leaf collimator.

15. The device of claim 14, wherein the control circuitry is configured to optimize the rotation of the collimator relative to the at least one stop point by maximizing the optimal blade positioning for the multi-leaf collimator.

16. The device of claim 12, wherein the control circuit is configured to optimize the rotation of the collimator relative to the at least one stop point by optimizing the collimator rotation without physical constraints.

17. The device of claim 16, wherein the control circuitry is configured to optimize collimator rotation without physical constraints by applying weights, the weights enhancing the collimator angle for the at least one stopping point.

18. The device of claim 12, wherein the control circuitry is configured to optimize the rotation of the collimator relative to the at least one stop point by optimizing the collimator rotation under physical constraints, the physical constraints relating to at least one of the following: Collimator rotation value at a static angle; Collimator rotation value at the arc stop position; Collimator rotation value at the starting position of the arc.

19. The device of claim 12, wherein the control circuitry is configured to optimize the rotation of the collimator relative to the at least one stop point by optimizing the collimator rotation to minimize the width of the patient target volume in the direction coinciding with the collimator blades.

20. The device of claim 12, wherein the control circuitry is configured to optimize the rotation of the collimator relative to the at least one stop point in such a way as: Access a two-dimensional matrix including a cost map, the cost map having a first axis corresponding to the rack angle and a second axis corresponding to the collimator angle, such that the cells in the two-dimensional matrix store the cost corresponding to a given combination of rack angle and collimator angle, such that collimator angle constraints for static rack angle and arc start and stop angles are modeled as disabled or high-cost cells. Determine the optimal path through the two-dimensional matrix for at least the most suitable rack angle.

21. The device of claim 12, wherein the control circuit is configured to optimize the rotation of the collimator relative to the at least one stop point by optimizing the collimator rotation to facilitate the orientation of the collimator blades, thereby producing an effective radiation modulation that enhances the target volume.

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