Method and apparatus for facilitating optimization of radiation treatment plan

Abstract

The invention relates to a method and apparatus for facilitating optimization of a radiation treatment plan. The control circuit identifies at least one field geometry value and then determines dosimetric robustness of the at least one field geometry value to produce a robustness assessment. The control circuit may then determine if the robustness assessment is satisfactory and, when true, optimize the radiation treatment plan using the at least one field geometry value.

Description

[0001] Copyright notice

[0002] A portion of the disclosure of this patent document contains material which is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the Patent and Trademark Office patent file or records, but otherwise reserves all copyright rights whatsoever. TECHNICAL FIELD

[0003] These teachings relate generally to treating a planned 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

[0004] The use of energy to treat medical conditions is a known area of prior art endeavor. For example, radiation therapy comprises an important component of many treatment plans for reducing or eliminating unwanted tumors. Unfortunately, the energy applied does not inherently discriminate between unwanted matter and adjacent tissue, organs, and the like that are desirable or even critical to the continued survival of the patient. As a result, energy such as radiation is typically applied in a carefully managed manner to at least attempt to limit the energy to a given target volume. So-called radiation treatment plans typically function in this regard.

[0005] A radiation treatment plan typically includes specified values for each of various treatment platform parameters during each of a plurality of successive fields. Treatment plans for radiation treatment sessions are typically automatically generated by so-called optimization processes. As used herein, "optimization" will be understood to mean improving a candidate treatment plan, without necessarily ensuring that the result of the optimization is in fact a single best solution. Such optimization typically includes automatically adjusting one or more physical treatment parameters (typically while adhering to one or more respective limits on these aspects) and mathematically computing 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 therapeutic result and avoiding undesirable side effects.

[0006] In external beam radiotherapy (photons or protons), beam placement is one parameter that typically needs to be set and can impact plan quality. Placement of fields is typically done according to planner experience, templated solutions, or in some cases using a beam geometry optimizer. BRIEF DESCRIPTION OF DRAWINGS

[0007] The above needs are at least partially met by methods and apparatuses for facilitating optimization of radiation treatment plans described in the following detailed description, particularly when studied in conjunction with the drawings, in which:

[0008] In the drawings:

[0009] Figure 1 including block diagrams configured according to various embodiments of the present teachings;

[0010] Figure 2 including flow diagrams configured according to various embodiments of the present teachings;

[0011] Figure 3 including schematic diagrams configured according to various embodiments of the present teachings;

[0012] Figure 4 including graphs configured according to various embodiments of the present teachings; and

[0013] Figure 5 including graphs configured according to various embodiments of the present teachings.

[0014] 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 improve the understanding of various embodiments of the present teachings. Further, common but well-understood elements that are useful in a commercially feasible embodiment have not been depicted in order to facilitate a less obstructed view of these various embodiments of the present teachings. Certain actions and / or steps can be described or depicted in a particular order of occurrence, but that is not necessarily meant to be limiting, and in fact many of the actions and / or steps can occur in different orders or concurrently with other actions or steps, including directly sequentially one after another or with other actions and / or steps doing incremental progress over time. The terminology used by the inventor in this disclosure was chosen to best explain the principles underlying the various embodiments of the application, and is not intended to limit the scope of the application, which is limited only by the appended claims. Unless specifically stated otherwise, the terms and expressions used herein have the ordinary technical meaning associated with them within the technical field concerned. The various embodiments of the present teachings are described in the following detailed description with reference to the drawings listed below. DETAILED DESCRIPTION

[0015] Generally, according to these various embodiments, a control circuit identifies at least one field geometry parameter value, then determines a dosimetric robustness of the at least one field geometry parameter value to produce a robustness assessment. The control circuit can then determine whether the robustness assessment is satisfactory, and when true, use the at least one field geometry parameter value to optimize a radiation treatment plan.

[0016] By one method, identifying at least one field geometry parameter value can include at least one of accessing a default field geometry parameter value and / or receiving user input specifying a field geometry parameter value. Examples of field geometry parameter values include, but are not limited to, a start point gantry angle for a volumetric modulated arc therapy field, a stop point gantry angle for a volumetric modulated arc therapy field, a start angle for a avoidance sector in a volumetric modulated arc therapy radiation treatment plan, a stop angle for a avoidance sector in a volumetric modulated arc therapy radiation treatment plan, a gantry angle for an intensity modulated radiation therapy field, a collimator angle, a patient support surface angle, and / or a patient constraint angle.

[0017] By a method, determining the dosimetric robustness of at least one field geometry parameter value to produce a robustness assessment can include optimizing the radiation treatment plan at a plurality of field geometry parameter values that are very close to, but not equal to, the at least one field geometry parameter value.

[0018] By a method, the plurality of field geometry parameter values that are very close to, but not equal to, the at least one field geometry parameter value can include at least two field geometry parameter values on opposite sides of the at least one field geometry parameter value. By a method, the foregoing can include a first plurality of field geometry parameter values on a first side of the at least one field geometry parameter value and a second plurality of field geometry parameter values on a second side of the at least one field geometry parameter value, the second side being on an opposite side of the at least one field geometry parameter value from the first side.

[0019] These teachings are highly flexible in practice, and will accommodate a variety of modifying and / or supplemental features. For example, when the robustness assessment is only partially, but not entirely, satisfactory, these teachings will still accommodate using field geometry parameter values that are modified from the at least one field geometry parameter value to optimize the radiation treatment plan. In this case and by a method, the field geometry parameter values that are modified from the at least one field geometry parameter value can be constrained to fall within a range of previously tested field geometry parameter values in determining the dosimetric robustness.

[0020] As another example of the flexibility of these teachings, these teachings will accommodate identifying at least one second field geometry parameter value of a second field geometry parameter that is different from the at least one field geometry parameter. In this case, determining the dosimetric robustness can include determining the dosimetric robustness of both the at least one field geometry parameter value and the at least one second field geometry parameter value.

[0021] Sensitivity of a treatment planning system with respect to one or more field geometry parameters refers to a situation when small changes in these parameter values within a (typically small) range of field geometry variations result in significant changes in some metric related to the generated plan and / or dose distribution. Metrics used to analyze the sensitivity of the system to such changes in field geometry parameter values can include any of a variety of dosimetric metrics, such as those based on clinical objectives or optimization cost function(s), as well as other plan-related metrics such as monitor unit or treatment delivery time. For example, when small modifications are made in the value of a particular field geometry parameter, the given treatment platform / system can be considered sensitive to this particular field geometry parameter when a significant change in one or more optimization cost function values is observed. When such small changes in the value of a field geometry parameter do not result in significant changes in the considered metric, we can say that the system is robust to such changes.

[0022] Small variations in the foregoing aspects can occur due to uncertainties that can arise, for example, with respect to patient positioning and / or patient anatomy at a given treatment session. Without these teachings, when the field geometry happens to include a non-robust region in which slight changes in patient geometry can cause the radiation field to deviate from its optimal position and result in non-optimal dose measurement variations of the radiation treatment plan.

[0023] The present teachings can help identify robust field geometries that are less susceptible to such dose inaccuracies due to uncertainties in patient anatomy or positioning

[0024] These and other benefits will become more apparent upon review of the following detailed description, which proceeds with reference to the drawings. Now, with reference to the drawings, and in particular to Figure 1 An illustrative apparatus 100 compatible with many of these teachings is first presented.

[0025] In this particular example, the enabled apparatus 100 includes a control circuit 101. As a "circuit," the control circuit 101 thus includes structure that includes at least one (and typically a plurality of) electrically conductive path(s) (such as a path that includes an electrically conductive metal such as copper or silver) that transports electricity in an ordered manner, the path(s) typically further including corresponding electrical components (including passive (such as resistors and capacitors) and active (such as any of a variety of semiconductor-based devices) as appropriate) to permit the circuit to implement the control aspects of these teachings.

[0026] 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 customized for a particular use rather than a general purpose use), a field programmable gate array (FPGA), etc.), or can include a partially or wholly programmable hardware platform (including but not limited to a microcontroller, a microprocessor, etc.). These architectural options for such structure are well known and understood in the art, and need not be further described here. This control circuit 101 is configured (e.g., through use of corresponding programming that will be well understood by those skilled in the art) to perform one or more of the steps, actions, and / or functions described herein.

[0027] It will be appreciated that the control circuit 101 can include a single integrated platform, or can include multiple such circuits that work in cooperation with one another.

[0028] The control circuit 101 is operably coupled to a memory 102. The memory 102 can be integral to the control circuit 101, or can be physically separate (in whole or in part) 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, chassis, power supply, and / or housing), or can be partially or entirely remote with respect to the control circuit 101 (where, for example, the memory 102 is physically located at 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 memory platforms that collectively comprise the "memory" of the apparatus 100.

[0029] In addition to information such as optimization information for a particular patient and information regarding a particular radiation treatment platform as described herein, the memory 102 can also be used to, for example, non-transitorily store computer instructions that, when executed by the control circuit 101, cause the control circuit 101 to operate as described herein. (As used herein, such a reference to "non-transitory" will be understood to refer to the non-temporal nature of the storage of the contents (and thus excludes the case that the storage contents merely form a signal or wave), as opposed to the volatility of the storage medium itself, and thus includes non-volatile memory such as read-only memory (ROM) as well as volatile memory such as dynamic random access memory (DRAM).

[0030] 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 transducers, printers, etc.) to facilitate the receipt of information and / or instructions from a user and / or the provision of information and / or instructions to a user.

[0031] 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 (both within the apparatus 100 and external thereto) via the network interface. Network interfaces, including wireless and non-wireless platforms, are well known in the art and need not be specifically described here.

[0032] By one approach, some or all of any desired patient-related imaging information can be obtained by a computed tomography apparatus 106 and / or other imaging apparatus 107 as known in the art.

[0033] In this illustrative example, the control circuit 101 is configured to ultimately output an optimized energy-based treatment plan, such as, for example, an optimized radiation treatment plan 113. This energy-based treatment plan typically includes specified values for each of various treatment platform parameters during each of a plurality of sequential exposure fields. In this case, the energy-based treatment plan is generated by an optimization process, examples of which are also provided herein.

[0034] By one approach, the control circuit 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 (denoted by first through Nth organs at risk 108 and 109 in Figure 1 typical application settings, the energy-based treatment platform 114 will include an energy source, such as a radiation source 115 of ionizing radiation 116.

[0035] By one approach, this radiation source 115 can be selectively moved along an arcuate path (where the path at least to some extent encloses the patient herself during administration of the treatment) via a gantry. The arcuate path can include a full or nearly full circle, as desired. By one approach, the control circuit 101 controls movement of the radiation source 115 along this arcuate path, and can accordingly control when the radiation source 115 starts moving, stops moving, accelerates, decelerates, and / or control the speed at which the radiation source 115 travels along the arcuate path.

[0036] As one illustrative example, the radiation source 115 can include a radio frequency (RF) x-ray source of, for example, a (linac-based) linear particle accelerator. A linac is a type of particle accelerator that greatly increases the kinetic energy of charged subatomic particles or ions by subjecting them to a series of oscillating electric potentials along a linear beamline, which can be used to generate ionizing radiation (e.g., x-rays) 116 and high-energy electrons.

[0037] A typical energy-based treatment platform 114 can also include one or more support devices 110 (such as a couch) to support the patient 104 during the treatment session, one or more patient fixation devices 111, a gantry or other movable mechanism that permits selective movement of the radiation source 115, and one or more energy-shaping devices (e.g., beam-shaping devices 117 such as jaws, a multi-leaf collimator, etc.) that provide selective energy shaping and / or energy modulation, as desired.

[0038] In a typical application setting, it is assumed herein that the patient support device 110 is selectively controllable by the control circuit 101 to move in any direction (i.e., any X, Y, or Z direction) during an energy-based treatment session. As the foregoing elements and systems are well understood in the art, no further elaboration of these aspects is provided here unless pertinent to the description.

[0039] Reference is now made to Figure 2 A process 200 that can be performed, e.g., in connection with the above-described application setting (and more specifically via the above-described control circuit 101) will be described. Generally speaking, this process 200 serves to facilitate generating an optimized radiation treatment plan 113, thereby facilitating treating a particular patient with therapeutic radiation using a particular radiation treatment platform in accordance with the optimized radiation treatment plan.

[0040] At block 201, the process 200 provides for the control circuit 101 identifying at least one field geometry parameter value corresponding to a radiation treatment plan to be optimized. This identification can be implemented in any of a variety of ways. For example, by one approach, the control circuit 101 accesses a default field geometry parameter value stored in the above-described memory 102. For example, this default value can constitute a value that is an average of this particular parameter in the experience of one or more treatment facilities. By another approach, the control circuit 101 can receive user input specifying a field geometry parameter value (e.g., via the above-described user interface 103). These teachings will accommodate these aspects as well as other approaches as desired. As one example of these aspects, a suitably configured and trained machine learning model can provide a field geometry parameter value.

[0041] These teachings will also accommodate any of a variety of field geometry parameters. By one general approach, the field geometry parameter value can comprise a value for gantry position. As noted above, a gantry is a mechanism that enables selective movement of a radiation source while applying radiation to a patient. More specifically, a gantry is a movable frame that houses a linear accelerator head that generates a high-energy radiation beam to be directed to a target volume such as a tumor. A typical gantry is designed to rotate around a patient positioned on a treatment table, allowing precise aiming of radiation from multiple angles while protecting surrounding healthy tissue.

[0042] A non-limiting list of potentially useful field geometry parameter values can include a start point gantry angle for a volumetric modulated arc therapy field, a stop point gantry angle for a volumetric modulated arc therapy field, an avoidance sector start angle in a volumetric modulated arc therapy radiation treatment plan, an avoidance sector stop angle in a volumetric modulated arc therapy radiation treatment plan, a gantry angle for an intensity modulated radiation therapy field, a collimator angle, a patient support surface angle, and / or a patient constraint angle, to name a few examples.

[0043] If desired, and as illustrated by optional block 202, the process 200 can also provide for identifying at least one second field geometry parameter value for a second field geometry parameter, the second field geometry parameter value being different from the field geometry parameter of the at least one field geometry parameter described above.

[0044] At block 203, the control circuit 101 determines a dosimetric robustness of the at least one field geometry parameter value to produce a robustness assessment. When there are two or more additional field geometry parameter values (for additional field geometry parameters), such a determination of dosimetric robustness can include determining a dosimetric robustness of both the at least one field geometry parameter value and the at least one second field geometry parameter value to produce a corresponding multi-dimensional robustness assessment.

[0045] By one approach, determining a dosimetric robustness of the at least one field geometry parameter value can include optimizing a plurality of radiation treatment plans at a plurality of different field geometry parameter values that are very close to, but not equal to, the at least one field geometry parameter value. In many application settings, this can be useful if there are at least two field geometry parameter values that are each located on opposite sides of the at least one field geometry parameter value. In other words, there is at least one field geometry parameter value that corresponds to one side of the identified field geometry parameter value and at least one other field geometry parameter value that corresponds to the other side of the identified field geometry parameter value. If desired, there can be a plurality of values on one side of the identified field geometry parameter value and another plurality of other values on the other side of the identified field geometry parameter value.

[0046] To determine the dosimetric robustness, these teachings will accommodate calculating the radiation dose corresponding to each of the foregoing values at the identified value as well as at other nearby locations. The more closely the dose results of the nearby values match the dose results of the identified value, the more robust the results are.

[0047] If desired, a particular level of robustness can be specified by the user. For example, the robustness can be defined by requiring that the dose values of the nearby field geometry parameter values differ from the dose value of the identified field geometry parameter value by no more than some specified amount, such as, for example, anywhere within a range of 0% to 5%, 10%, or other selected upper limit.

[0048] At block 205, the control circuit 101 can determine whether the determined dosimetric robustness corresponding to the one or more identified field geometry parameter values is sufficiently robust. The criteria for judging such sufficiency can be selected, for example, by the user. It can be noted that certain clinical sites (e.g., breast cancer cases or pancreatic cancer cases) can be more sensitive to small changes in beam geometry parameters than other clinical sites. In such cases, the criteria for determining a sufficient level of robustness can be higher and more selective than the criteria for determining sufficiency of robustness in less sensitive application settings.

[0049] If the robustness is judged to be insufficient, the process 200 will adapt to any corresponding action 207 that can be desired. The latter can include, for example, simply notifying the user of the situation, automatically re-identifying different field geometry parameter values and re-executing the process 200 until a satisfactory result is obtained, or any other selected action.

[0050] When the determined dose metric robustness is satisfactory, at block 206, the control circuit 101 can use the identified field geometry parameter value(s) to optimize the radiation treatment plan, reasonably ensuring that the resulting plan achieves good results not only in the case of being administered exactly according to the identified values, but also in the case of variations in those values when the radiation treatment plan is administered.

[0051] At optional block 208, the process 200 will adapt to administering radiation to the patient using the optimized radiation treatment plan described above. By one approach, feedback information from the administration of the plan can be used to inform, for example, changes in definitions or criteria by which dose metric robustness is determined and / or used to determine a predicted satisfactory outcome.

[0052] It is possible that the determination of whether the dose metric robustness is satisfactory will yield a less definitive result. Instead of being clearly satisfactory or clearly unsatisfactory, the result can indicate that the robustness is partially, though not completely, satisfactory. In this case, and as illustrated by optional block 204, the process 200 will adapt to optimizing the radiation treatment plan using field geometry parameter values that are modified according to the identified field geometry parameter values. For example, it is acceptable to select field geometry parameter values within the range of field geometry parameter values tested when determining the dose metric robustness at block 203.

[0053] Further details consistent with these teachings will now be given. It should be understood that the specific details are intended to illustrate the embodiments and not to limit in any way the scope of these teachings.

[0054] Figure 3A schematic view of a patient 104 is presented. (In this view, the patient 104 is represented by a copyrighted schematic feature of a human patient, typically colored green on the user's display, with a small circle 301, typically colored red on the user's display, corresponding to the patient's nose, a circle 302, also typically colored red on the user's display, corresponding to the patient's left hand at the end of the patient's left arm, and two circles denoted by reference numeral 303, typically colored blue on the user's display, corresponding to the patient's toes. For the purpose of planning a radiation treatment, this schematic representation provides a convenient and useful way of depicting the patient's torso and appendages without reference to gender.) This image also presents a range of a single field geometry parameter 304 to be scanned for field geometry robustness (in this illustrative example, this parameter includes the volumetric modulated arc therapy start gantry angle). In this illustrative example, the identified field geometry parameter value is 330 degrees, and the range of angle values to be investigated is within 10 degrees on either side of the identified value.

[0055] Figure 4 A graph 400 is presented that depicts a situation in which the cost function varies smoothly when the optimization is performed according to the range of gantry angles indicated in Figure 3 Although the dosimetric results can vary somewhat, the degree of these variations does not vary greatly over a small angular distance on either side of 330 degrees, and thus it can be concluded that the value of 330 degrees is a robust value.

[0056] Figure 5 A graph 500 is presented that depicts a situation in which the cost function varies highly between about 330 degrees and about 332 degrees and also has a plateau 501 from 332 degrees to 340 degrees. By one approach, these teachings can suggest simply rejecting 330 degrees as an identified field geometry parameter value that is not sufficiently robust. By another approach, these teachings can suggest using a value of 336 degrees, since this angle is in the middle of the foregoing plateau 501 and thus represents a robust alternative.

[0057] By one approach, these teachings will also accommodate monitoring of clinical target outcomes and non-outcomes within the region of the field geometry parameter that is tested. This approach can provide additional quantitative measures to assess the robustness of the initial field geometry shape selection.

[0058] In general, the foregoing process 200 uses the optimized cost function as a proxy to monitor whether the selected field geometry is in a region of smooth or highly varying dose uncertainty. That is, the metric useful in these regards can differ from the optimization cost. Examples include, but are not limited to, minimum dose values for the objectives, number of monitor units used for a particular field, etc. In general, the applicable metric can be anything that reflects the plan efficacy.

[0059] In general, these teachings can accommodate using and exploiting any radiation treatment plan quality indicator that is substantially not explicitly dependent on the field geometry setup as an indicator of field geometry robustness. Thus, any quantitative value that can be derived from the results of the optimization (i.e., after optimization) can also be used as a proxy to monitor the robustness of the optimized plan as a function of the field geometry parameters.

[0060] It can also be noted that these teachings will accommodate using more than one metric (e.g., two metrics, three metrics, or more as needed) to monitor the robustness of a particular selected field geometry. For example, one metric can be the value of the optimizer's cost function, while another metric is a value derived from the clinical objectives. As a simple example, the plan can be non-robust with respect to the optimizer cost function, but robust with respect to some quality function derived from the clinical objectives. If the treatment facility decides that the plan must be robust with respect to all robustness indicators, then such a plan would not be considered acceptable.

[0061] It should be appreciated that these teachings can be used as a stand-alone method that can help in selecting and defining field geometries during the planning of a treatment session. Instead of or in conjunction with the foregoing, these teachings can also be used as an additional stage in a corresponding selection of beam geometry optimization algorithm.

[0062] Other aspects of the disclosure are provided by the subject matter of the following clauses:

[0063] Clause 1. A method of facilitating optimization of a radiation treatment plan, the method comprising: by control circuitry: identifying at least one field geometry parameter value; determining a dose uncertainty robustness of the at least one field geometry parameter value to produce a robustness assessment; determining whether the robustness assessment is satisfactory; when the robustness assessment is satisfactory, using the at least one field geometry parameter value to optimize the radiation treatment plan.

[0064] Clause 2. The method of any preceding clause or combination of clauses, wherein identifying the at least one field geometry parameter value comprises at least one of: accessing a default field geometry parameter value; receiving user input specifying the field geometry parameter value.

[0065] Clause 3. The method of any preceding clause or combination of clauses, wherein determining a dosimetric robustness of the at least one field geometry parameter value to produce the robustness assessment comprises optimizing a radiation treatment plan at a plurality of field geometry parameter values that are very close to, but not equal to, the at least one field geometry parameter value.

[0066] Clause 4. The method of any preceding clause or combination of clauses, wherein the plurality of field geometry parameter values that are very close to, but not equal to, the at least one field geometry parameter value comprises at least two field geometry parameter values on opposite sides of the at least one field geometry parameter value.

[0067] Clause 5. The method of any preceding clause or combination of clauses, wherein the at least two field geometry parameter values on opposite sides of the at least one field geometry parameter value comprise a first plurality of field geometry parameter values on a first side of the at least one field geometry parameter value and a second plurality of field geometry parameter values on a second side of the at least one field geometry parameter value, the second side being on an opposite side of the at least one field geometry parameter value from the first side.

[0068] Clause 6. The method of any preceding clause or combination of clauses, wherein the at least one field geometry parameter value comprises a value of a gantry position.

[0069] Clause 7. The method of any preceding clause or combination of clauses, wherein the at least one field geometry parameter value comprises at least one of: a start point gantry angle of a volumetric modulated arc therapy field; a stop point gantry angle of a volumetric modulated arc therapy field; a avoidance sector start angle in a volumetric modulated arc therapy radiation treatment plan; a avoidance sector stop angle in a volumetric modulated arc therapy radiation treatment plan; a gantry angle of an intensity modulated radiation therapy field; a collimator angle; a patient support surface angle; a patient constraint angle.

[0070] Clause 8. The method of any preceding clause or combination of clauses, further comprising, when the robustness assessment is partially but not completely satisfactory, optimizing the radiation treatment plan using a field geometry parameter value that is modified from the at least one field geometry parameter value.

[0071] Clause 9. The method of any preceding clause or combination of clauses, wherein the field geometry parameter value that is modified from the at least one field geometry parameter value falls within a range of field geometry parameter values tested when determining the dosimetric robustness.

[0072] Clause 10. The method of any preceding clause or combination of clauses, further comprising: identifying at least one second field geometry parameter value of a second field geometry parameter different from the field geometry parameter of the at least one field geometry parameter; and wherein determining the dosimetric robustness of the at least one field geometry parameter value to produce a robustness assessment comprises determining the dosimetric robustness of both the at least one field geometry parameter value and the at least one second field geometry parameter value to produce a robustness assessment.

[0073] Clause 11. An apparatus to facilitate optimization of a radiation treatment plan, the apparatus comprising: control circuitry configured to: identify at least one field geometry parameter value; determine a dosimetric robustness of the at least one field geometry parameter value to produce a robustness assessment; determine whether the robustness assessment is satisfactory; when the robustness assessment is satisfactory, use the at least one field geometry parameter value to optimize the radiation treatment plan.

[0074] Clause 12. The apparatus of any preceding clause or combination of clauses, wherein identifying the at least one field geometry parameter value comprises at least one of: accessing a default field geometry parameter value; receiving user input specifying the field geometry parameter value.

[0075] Clause 13. The apparatus of any preceding clause or combination of clauses, wherein determining the dosimetric robustness of the at least one field geometry parameter value to produce the robustness assessment comprises: optimizing radiation treatment plans at a plurality of field geometry parameter values very close to but not equal to the at least one field geometry parameter value.

[0076] Clause 14. The apparatus of any preceding clause or combination of clauses, wherein the plurality of field geometry parameter values very close to but not equal to the at least one field geometry parameter value comprises at least two field geometry parameter values on opposite sides of the at least one field geometry parameter value.

[0077] Clause 15. The apparatus of any preceding clause or combination of clauses, wherein the at least two field geometry parameter values on opposite sides of the at least one field geometry parameter value comprise a first plurality of field geometry parameter values on a first side of the at least one field geometry parameter value and a second plurality of field geometry parameter values on a second side of the at least one field geometry parameter value, the second side on an opposite side of the at least one field geometry parameter value from the first side.

[0078] Clause 16. The apparatus of any preceding clause or combination of clauses, wherein the at least one field geometry parameter value comprises a value of gantry position.

[0079] Clause 17. The apparatus of any preceding clause or combination of clauses, wherein the at least one field geometry parameter value comprises at least one of: a start gantry angle of a volumetric modulated arc therapy field; a stop gantry angle of a volumetric modulated arc therapy field; a start angle of an avoidance sector in a volumetric modulated arc therapy radiation treatment plan; a stop angle of an avoidance sector in a volumetric modulated arc therapy radiation treatment plan; a gantry angle of an intensity modulated radiation therapy field; a collimator angle; a patient support surface angle; a patient constraint angle.

[0080] Clause 18. The apparatus of any preceding clause or combination of clauses, further comprising, when the robustness assessment is partially but not completely satisfactory, optimizing the radiation treatment plan using field geometry parameter values modified from the at least one field geometry parameter value.

[0081] Clause 19. The apparatus of any preceding clause or combination of clauses, wherein the field geometry parameter values modified from the at least one field geometry parameter value fall within a range of field geometry parameter values tested in determining the dosimetric robustness.

[0082] Clause 20. The apparatus of any preceding clause or combination of clauses, further comprising: identifying at least one second field geometry parameter value of a second field geometry parameter different from the at least one field geometry parameter; and wherein determining the dosimetric robustness of the at least one field geometry parameter value to produce a robustness assessment comprises determining the dosimetric robustness of both the at least one field geometry parameter value and the at least one second field geometry parameter value to produce a robustness assessment.

[0083] Those skilled in the art will realize that various modifications, variations and combinations of the above described embodiments can be made without departing from the scope of the present invention, and that such modifications, variations and combinations are also regarded to be within the scope of the inventive concepts disclosed and claimed herein.

Claims

1. A method for facilitating optimization of a radiation treatment plan, the method comprising: By the control circuit: identifying at least one field geometry parameter value; determining a dosimetric robustness of the at least one field geometry parameter value to produce a robustness assessment; determining whether the robustness assessment is satisfactory; When the robustness assessment is satisfactory, the radiation treatment plan is optimized using the at least one field geometry parameter value.

2. The method of claim 1 , wherein identifying the at least one field geometry parameter value comprises at least one of: Access default field geometry parameter values; User input specifying values ​​for the field geometry parameters is received.

3. The method of claim 1 , wherein determining the dosimetric robustness of the at least one field geometry parameter value to produce the robustness assessment comprises: The radiation treatment plan is optimized at a plurality of field geometry parameter values ​​that are closely adjacent to, but not equal to, the at least one field geometry parameter value.

4. The method of claim 3, wherein the plurality of field geometry parameter values ​​that are very close to, but not equal to, the at least one field geometry parameter value comprise: At least two field geometry values ​​on opposite sides of the at least one field geometry value.

5. The method of claim 4, wherein the at least two field geometry parameter values ​​on opposite sides of the at least one field geometry parameter value comprise: A first plurality of field geometry parameter values ​​on a first side of the at least one field geometry parameter value and a second plurality of field geometry parameter values ​​on a second side of the at least one field geometry parameter value, the second side being on a side of the at least one field geometry parameter value opposite to the first side. The method of claim 1 , wherein the at least one field geometry parameter value comprises a value of a gantry position.

7. The method of claim 1 , wherein the at least one field geometry parameter value comprises at least one of: The starting point gantry angle of the volumetric modulated arc therapy field; stopping point gantry angle for the volumetric modulated arc therapy field; Avoidance sector starting angle in volumetric modulated arc therapy radiation treatment plans; Avoidance sector stopping angles in volumetric modulated arc therapy radiation treatment plans; gantry angle for the intensity modulated radiation therapy field; collimator angle; Patient support surface angle; Patient restraint angle.

8. The method according to claim 1, further comprising: When the robustness assessment is partially but not fully satisfactory, the radiation treatment plan is optimized using field geometry parameter values ​​modified according to the at least one field geometry parameter value.

9. The method of claim 8, wherein the field geometry parameter value modified according to the at least one field geometry parameter value falls within a range of field geometry parameter values ​​tested when determining the dosimetric robustness.

10. The method according to claim 1, further comprising: identifying at least one second field geometry parameter value of a second field geometry parameter different from said field geometry parameter of said at least one field geometry parameter; And wherein determining the dosimetric robustness of the at least one field geometry parameter value to produce a robustness assessment comprises determining the dosimetric robustness of both the at least one field geometry parameter value and the at least one second field geometry parameter value to produce a robustness assessment.

11. An apparatus for facilitating optimization of a radiation treatment plan, the apparatus comprising: The control circuit is configured as follows: identifying at least one field geometry parameter value; determining a dosimetric robustness of the at least one field geometry parameter value to produce a robustness assessment; determining whether the robustness assessment is satisfactory; When the robustness assessment is satisfactory, the radiation treatment plan is optimized using the at least one field geometry parameter value.

12. The apparatus of claim 11 , wherein identifying the at least one field geometry parameter value comprises at least one of: Access default field geometry parameter values; User input specifying values ​​for the field geometry parameters is received.

13. The apparatus of claim 11 , wherein determining the dosimetric robustness of the at least one field geometry parameter value to produce the robustness assessment comprises: The radiation treatment plan is optimized at a plurality of field geometry parameter values ​​that are closely adjacent to, but not equal to, the at least one field geometry parameter value.

14. The apparatus of claim 13 , wherein the plurality of field geometry parameter values ​​that are very close to, but not equal to, the at least one field geometry parameter value comprise: At least two field geometry values ​​on opposite sides of the at least one field geometry value.

15. The apparatus of claim 14, wherein the at least two field geometry values ​​on opposite sides of the at least one field geometry value comprise: A first plurality of field geometry parameter values ​​on a first side of the at least one field geometry parameter value and a second plurality of field geometry parameter values ​​on a second side of the at least one field geometry parameter value, the second side being on a side of the at least one field geometry parameter value opposite to the first side.

16. The apparatus of claim 11, wherein the at least one field geometry parameter value comprises a value of a gantry position.

17. The apparatus of claim 11 , wherein the at least one field geometry parameter value comprises at least one of: The starting point gantry angle of the volumetric modulated arc therapy field; stopping point gantry angle for the volumetric modulated arc therapy field; Avoidance sector starting angle in volumetric modulated arc therapy radiation treatment plans; Avoidance sector stopping angles in volumetric modulated arc therapy radiation treatment plans; gantry angle for the intensity modulated radiation therapy field; collimator angle; Patient support surface angle; Patient restraint angle.

18. The apparatus according to claim 11, further comprising: When the robustness assessment is partially but not fully satisfactory, the radiation treatment plan is optimized using field geometry parameter values ​​modified according to the at least one field geometry parameter value.

19. The apparatus of claim 18, wherein the field geometry parameter value modified according to the at least one field geometry parameter value falls within a range of field geometry parameter values ​​tested when determining the dosimetry robustness.

20. The apparatus according to claim 11, further comprising: identifying at least one second field geometry parameter value of a second field geometry parameter different from said field geometry parameter of said at least one field geometry parameter; And wherein determining the dosimetric robustness of the at least one field geometry parameter value to produce a robustness assessment comprises determining the dosimetric robustness of both the at least one field geometry parameter value and the at least one second field geometry parameter value to produce a robustness assessment.

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