Systems and methods for radiotherapy field delivery time optimization

Abstract

Embodiments of the present disclosure relate to systems and methods for radiotherapy field delivery time optimization. Treatment fields can be generated as part of a treatment plan that achieves a desired balance between field delivery time and dose based on machine parameters and knowledge, such as machine-specific beam generation, delivery, and scanning logic, and / or a maximum treatment time value. Treatment parameters can be adjusted using a graphical user interface in order to prioritize treatment time or dose measurement. As a result, overall treatment time is reduced, thus improving treatment quality and patient experience.

Description

[0001] Related U.S. Patents

[0002] This application is a continuation-in-part of application entitled “Systems and Methods for Radiotherapy Field Delivery Time Optimization” of A. Meijers et al. filed on December 8, 2020, Serial No. 17 / 115,639, which is hereby incorporated by reference in its entirety. TECHNICAL FIELD

[0003] Embodiments of the present disclosure relate generally to the field of radiotherapy. More specifically, embodiments of the present disclosure relate to computer-implemented treatment planning methods and systems for radiotherapy treatments. BACKGROUND

[0004] One goal of radiotherapy treatment and biological planning is to maximize the dose applied to a target tumor while minimizing the dose absorbed by surrounding (normal) tissue. Treatment outcome in terms of tumor control and normal tissue toxicity depends not only on physical parameters such as dose, but also on a large number of other parameters such as biological parameters and machine parameters

[0005] While maximizing the dose applied to a target tumor while minimizing the dose absorbed by surrounding tissue remains a primary consideration, other factors can be considered to improve the quality of treatment and / or the experience of the patient receiving treatment. For example, in many cases, it is desirable to reduce or limit the overall treatment time and / or individual treatment fractions. In some cases, treatment can be applied while the patient holds their breath to remain still. However, in existing methods of treatment planning that seek to minimize the dose absorbed by surrounding healthy tissue, it is difficult to accommodate certain types of radiotherapy based on relatively short treatment times.

[0006] One radiotherapy treatment technique is known as spot scanning, also referred to as pencil beam scanning. In spot scanning, a beam is directed to a point in the treatment target as specified by the treatment plan. The specified point locations are typically arranged in a fixed (lattice) pattern for each energy layer of the beam, and the beam is delivered to a fixed scan path within the energy layer. While some existing treatment planning solutions can remove points below a certain monitor unit (MU) threshold after optimization, the resulting dose is redistributed in a manner that is not necessarily optimal in terms of plan quality or field delivery time from the perspective of the treatment delivery equipment. SUMMARY

[0007] Accordingly, there is a need in the art to generate treatment plans for radiotherapy using treatment time as a parameter (optimization goal), e.g., to reduce overall treatment time, or to still maintain a medically acceptable dose metric while limiting total treatment time to an acceptable value. Embodiments of the present disclosure are operable to produce a treatment field as part of a treatment plan that achieves a desired balance between field delivery time and dose based on machine parameters and knowledge, such as machine-specific beam generation, transport, and / or scanning logic, and / or a maximum treatment time value, and wherein treatment parameters can be adjusted using a graphical user interface such that treatment time or dose metric is prioritized.

[0008] Embodiments of a computer-implemented method for radiotherapy treatment planning are disclosed. In embodiments, the method comprises: accessing a radiotherapy treatment plan comprising one or more treatment (energy) layers, wherein each of the treatment layers comprises a plurality of points; receiving a weight for a treatment time objective of the radiotherapy plan, modifying the points from the treatment layers based on the weight and a cost of the points to produce modified layers, or reducing a number of the layers; and generating a modified radiotherapy treatment plan using the modified layers or the reduced number of layers, wherein the modified radiotherapy treatment plan is operable to be executed by a delivery machine to apply a radiotherapy treatment to a target in accordance with the modified radiotherapy treatment plan.

[0009] According to some embodiments, the method further comprises modifying one or more points to produce one or more modified layers, wherein the modified radiotherapy treatment plan is generated using the modified layers.

[0010] According to some embodiments, the points are modified to redistribute a dose contribution of the point to one or more neighboring points.

[0011] According to some embodiments, a weight for a dose metric objective of the radiotherapy treatment plan is also received.

[0012] According to some embodiments, the dose metric objective comprises at least one of: a dose volume histogram (DVH) objective; an equivalent uniform dose (EUD) objective; a minimum dose objective; a maximum dose objective; and a dose fall-off objective.

[0013] According to some embodiments, the method comprises dynamically presenting a dose volume histogram (DVH) on a graphical user interface of a treatment planning system based on a weight for a treatment time objective of the modified radiotherapy treatment plan, and a weight for a dose metric objective of the radiotherapy treatment plan.

[0014] According to some embodiments, the weight of the treatment time objective for the modified radiation therapy treatment plan and the weight of the dose metric objective are defined according to user input received from a control, such as a slider, presented on a graphical user interface of a treatment planning system.

[0015] According to some embodiments, the method includes simulating the radiation therapy according to the modified radiation therapy treatment plan to determine whether the actual dose complies with the predefined quality criteria when applied according to the modified radiation therapy treatment plan.

[0016] According to some embodiments, modifying the points from the treatment layer includes, for each of the points, calculating a cost based on a dose associated with the point and a delivery duration of the point, and modifying at least one of the points having a highest cost among the points.

[0017] According to another embodiment, an electronic system for radiation therapy treatment planning is disclosed. The electronic system includes a display device, a memory, and a processor in communication with the memory. The processor is operable to execute a method for performing radiation therapy treatment planning. The method includes accessing a radiation therapy treatment plan including one or more treatment layers, where each of the treatment layers includes a plurality of points, receiving a weight of a treatment time objective for the radiation therapy treatment plan, modifying the points from the treatment layer based on the weight and a cost of the points to produce a modified treatment layer, or reducing a number of layers, and generating a modified radiation therapy treatment plan using the modified layer or the reduced number of layers, where the modified radiation therapy treatment plan is operable to be applied by a delivery machine to a target according to the modified radiation therapy treatment plan.

[0018] According to a different embodiment, a non-transitory computer-readable storage medium containing instructions for execution by a processor to cause the processor to perform a method of radiation therapy treatment planning is disclosed. The method includes accessing a radiation therapy treatment plan including one or more treatment layers, where each of the treatment layers includes a plurality of points, receiving a weight of a treatment time objective for the radiation therapy treatment plan, modifying the points from the treatment layer based on the weight and a cost of the points to produce a modified treatment layer, or reducing a number of layers, and generating a modified radiation therapy plan using the modified layer or the reduced number of layers, where the modified radiation therapy treatment plan is operable to be executed by a delivery machine to apply radiation therapy treatment to a target according to the modified radiation therapy treatment plan.

[0019] Reduction in treatment time is of significant importance to improve the quality of treatment and patient comfort. Reducing treatment time for delivering a radiation therapy treatment plan can reduce the risk of intra-fraction misalignment, improve machine throughput, and enable or facilitate specialized treatments such as breath-hold fixation treatments, thereby improving the quality of care and / or accessibility of proton therapy.

[0020] Those skilled in the art will realize upon reading the following detailed description that these and other objectives and advantages of embodiments according to the present disclosure are achieved, as illustrated in the various figures. BRIEF DESCRIPTION OF DRAWINGS

[0021] The accompanying drawings, which are incorporated in and form a part of the specification, illustrate embodiments of the present disclosure and, together with the description, serve to explain the principles of the present disclosure. In the drawings:

[0022] Figure 1 is a graphical illustration of isodose lines of an example of a radiation therapy treatment plan generated by a treatment planning system according to embodiments of the present disclosure.

[0023] Figure 2 is a chart depicting the cost of each point of a layer of an example of a treatment plan according to embodiments of the present disclosure.

[0024] Figure 3 depicts an example of a point scan pattern of a conventional treatment plan generated by a treatment planning system without time optimization or cost reduction.

[0025] Figure 4 depicts an example of a point scan pattern of a modified treatment plan according to embodiments of the present disclosure that has the highest cost point in time removed.

[0026] Figure 5 depicts a dosimetry of the modified treatment plan compared to the conventional plan without cost reduction. Figure 4

[0027] Figure 6 depicts isodose lines of an example of an optimized radiation therapy treatment plan with significant cost reduction in time according to embodiments of the present disclosure.

[0028] Figure 7 shows lateral line dose profiles of two example radiation therapy treatment plans according to embodiments of the present disclosure.

[0029] Figure 8 ​is a screen display of an example of a graphical user interface of a treatment planning system according to embodiments of the present disclosure, including a controller (e.g., a slider) for assigning relative weights to a dose metric objective and a treatment time objective for generating an optimized treatment plan with reduced overall cost by removing one or more points.

[0030] Figure 9 is a screen display of an example of a graphical user interface of a treatment planning system according to embodiments of the present disclosure, including an input field for assigning relative weights to a dose metric objective against a treatment time objective for generating an optimized treatment plan with reduced overall cost by removing one or more points.

[0031] Figure 10 is a screen display of an example of a graphical user interface of a treatment planning system according to embodiments of the present disclosure, including a list of treatment delivery times for a field of a treatment plan that was generated using point reduction to reduce treatment delivery times according to a delivery time objective (e.g., timing constraints of a delivery system) while also taking into account dose metric objectives of the treatment plan.

[0032] Figure 11A and Figure 11B is a screen display of an example of a graphical user interface of a treatment planning system according to embodiments of the present disclosure, including a dose-volume histogram and a scan pattern and sequence that are dynamically generated according to relative weights assigned to a treatment time objective and a dose metric objective of a treatment plan.

[0033] Figure 12 is a flowchart of an example of a sequence of computer-implemented steps in a method for optimizing a radiotherapy treatment plan to reduce overall cost / delivery time according to embodiments of the present disclosure.

[0034] Figure 13 is a block diagram depicting an example of an electronic system on which embodiments of the present disclosure can be implemented. DETAILED DESCRIPTION

[0035] Reference will now be made in detail to several embodiments. While the subject matter will be described in the context of alternatives, it will be appreciated that they are not intended to limit the claimed subject matter to these alternatives alone. On the contrary, the claimed subject matter is intended to cover alternatives, modifications and equivalents, which can include other alternatives falling within the spirit and scope of the claimed subject matter as defined by the appended claims.

[0036] Moreover, in the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the claimed subject matter. However, it will be recognized by those of ordinary skill in the art that embodiments can be practiced without these specific details. In other instances, well-known methods, procedures, components, and circuits have not been described in detail so as not to unnecessarily obscure aspects of the subject matter.

[0037] Some embodiments can be described in the general context of computer- executable instructions, such as program modules, being executed by one or more electronic systems (computers or other devices). Generally, program modules include routines, programs, objects, components, data structures, and the like, that perform particular tasks or implement particular abstract data types. Typically, the functionality of the program modules can be combined or distributed as desired in various embodiments.

[0038] Parts of the detailed description are presented and discussed in terms of methods. Although steps and order of steps are disclosed in the figures of the drawings (e.g., Figure 12 ) that depict the operation of methods, such steps and order of steps need not be performed in the precise order described, and such steps and order of steps can be modified, combined, sub-divided, replaced, or omitted.

[0039] Some portions of the detailed description are presented in terms of procedures, steps, logic blocks, processing, and other symbolic representations of operations on data bits that can be performed on computer memory. These descriptions and representations are the means used by those skilled in the data processing arts to most effectively convey the substance of their work to others skilled in the art. A procedure, computer-executed step, logic block, process, etc., is here, and generally, conceived to be a self-consistent sequence of steps or instructions leading to a desired result. The steps are those requiring physical manipulations of physical quantities. Usually, though not necessarily, these quantities take the form of electrical or magnetic signals capable of being stored, transferred, combined, compared, and otherwise manipulated in a computer system. It has proven convenient at times, principally for reasons of common usage, to refer to these signals as bits, values, elements, symbols, characters, terms, numbers, or the like.

[0040] It should be borne in mind, however, that all of these and similar terms are to be associated with the appropriate physical quantities and are merely convenient labels applied to these quantities. Unless specifically stated otherwise as apparent from the following discussion, it is appreciated that throughout the description, discussions utilizing terms such as "accessing," "displaying," "writing," "including," "storing," "transmitting," "traversing," "determining," "identifying," "observing," "adjusting," "receiving," "modifying," "generating," "re-allocating," "emulating," or the like, refer to the actions and processes of an electronic (e.g., computer) system or similar electronic computing device. The computer system manipulates and transforms data represented as physical (electronic) quantities within the computer system's registers and memories into other data similarly represented as physical quantities within the computer system memories, registers or other such information storage, transmission or display devices.

[0041] Embodiments described herein can be discussed in the general context of computer-executable instructions residing on some form of computer-readable storage medium such as program modules, executed by one or more computers or other devices. By way of example, and not limitation, computer-readable storage media can comprise non-transitory computer-readable storage media, and communication media. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform particular tasks or implement particular abstract data types. The functionality of the program modules can be combined or distributed as desired in various embodiments.

[0042] Computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer storage media includes, but is not limited to, random access memory (RAM), read only memory (ROM), electrically erasable programmable ROM (EEPROM), flash memory or other memory technology, compact disc ROM (CD-ROM), digital versatile disks (DVDs) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and that can be accessed to retrieve that information.

[0043] System and method for radiotherapy field delivery time optimization

[0044] According to embodiments of the present disclosure, the beam current of a proton or ion beam, or the number of protons or ions per time segment, can be adjusted to minimize the time required to treat a target volume using radiation. The beam current of a proton or ion beam, or the number of protons or ions per time segment, can be adjusted according to a treatment plan and also according to one or more limitations on the treatment machine equipment that produces the proton or particle beam and delivers and monitors the radiation dose. The treatment plan can be based on one or more computed tomography (CT) images of a target volume (e.g., a cancerous tumor) of a patient's body and / or other suitable images derived from suitable imaging techniques, and can include one or more prescriptions for the amount of radiation to be delivered to the target volume, and at multiple locations within the target volume where the radiation will be delivered.

[0045] To deliver the prescribed dose of radiation, the treatment plan can be converted to machine parameters (e.g., the beam current of a proton or ion beam, the number of protons or ions per time segment to be emitted by the accelerator, the magnetic flow, the settings to achieve the prescribed energy of the protons or ions at the target volume, the measurement range of the dose monitoring system, etc.). This conversion can take into account the limitations of the treatment machine equipment that produces the proton or ion beam and delivers and monitors the radiation treatment.

[0046] Specialized software can be used to generate the treatment plan, and an algorithm or process can be applied that calculates the beam current of a proton or ion beam, or the number of protons or ions per time segment, so that the patient can be treated as quickly as possible or to achieve a desired balance between treatment time and dose measurement goals. In addition, the algorithm or process can take into account the time-optimized beam current of a proton or ion beam, or the time-optimized number of protons or ions per time segment, to determine the duration of each point of the field. The determined duration of each point and the entire field can be taken into account when developing the treatment plan.

[0047] Figure 1 An example isodose line 100 of a radiation therapy treatment plan generated by a radiation therapy treatment planning system (TPS) and used to control a radiation delivery system (e.g., a proton therapy treatment system) for delivering a controlled dose of radiation, according to embodiments of the present disclosure, is depicted. In this example, the isodose line 100 is a two-dimensional representation of a three-dimensional isodose surface that is generated by the TPS and used to control the radiation delivery system. Figure 1In the example of Table I, a single field treatment plan including multiple energy layers is generated to deliver a 50 Gray (Gy) dose in 25 individual treatment fractions (parts) using a partial dose of 2 Gray (Gy). The treatment plan is configured to apply the radiation therapy treatment using eight energy layers and a total of 2969 spots. Each spot is defined by an energy, a spot location for delivering the dose through a beam, and a number of monitor units (MUs) including the dose. The treatment time for different spots is determined by taking into account machine specific parameters (e.g., timing constraints), and summed to determine the total field irradiation time, as shown in the example of Table I.

[0048] Table I

[0049]

[0050] As shown in Table I, the example treatment plan includes a total irradiation time of 66.681 seconds. The spots of the treatment plan can be defined using machine specific knowledge, such as based on functions corresponding to machine parameters for the delivery of a particular plan, field, layer, or spot. For example, these parameters can include a cyclotron beam current, a number of MUs indicating an actual dose delivered for a particular plan or spot, a delivery time, a beam current in a nozzle, a scan magnet velocity profile, scan logic, and other parameters related to a particular machine or system delivering the radiation therapy treatment.

[0051] In general, the cost of a spot of a treatment plan is a function of parameters, such as but not limited to one or more of the following: a time required to deliver the spot, a MU of the spot, a cyclotron beam current during delivery of the spot and a maximum possible cyclotron beam current, and other spot or beam generation, transmission, and delivery system parameters. In embodiments, the cost of a spot of a treatment plan can be expressed using an equation according to machine specific knowledge, such as but not limited to:

[0052] or

[0053] or

[0054] or

[0055] or, more generally,

[0056] c spot = f (t spot , MU spot , I cyclo , I cyclo max， p * )

[0057] In the above equation, c spot represents the cost of an individual spot, I cyclo maxdenotes the maximum possible cyclotron beam current, I cyclo denotes the cyclotron beam current during delivery of a spot, MU spot denotes the MU of an individual spot, t spot denotes the time required to deliver an individual spot, and p* denotes any other spot or beam production, energy selection, beam transport, and / or beam delivery system parameters.

[0058] The total value of the cost function, which represents the total cost of a treatment plan, can be determined as the sum of the individual costs of all spots, where n is the total number of spots occurring in the plan:

[0059]

[0060] To optimize a treatment plan, one or more spots of relatively high cost can be modified without significantly affecting the dose prescription and treatment time. In general, modifying a spot can mean removing the spot from the treatment plan, or mean that the MU or dose contribution from the spot is distributed to one or more neighboring spots, including spots in the same layer or spots in one or more adjacent layers, and / or the position (distribution) of the spots around the modified or removed spot can be adjusted (see also discussion below). Figure 7

[0061] According to some embodiments, spots (e.g., spot weights) are automatically adjusted by the TPS to reduce the cost of the spots and the total cost of the treatment plan, thereby reducing the total treatment time for implementing the treatment plan. The reduction of treatment time is significant for improving treatment quality as well as patient comfort. Reducing the treatment time for implementing a radiation therapy treatment plan can reduce the risk of intra-fraction misalignment, increase machine throughput, and enable or facilitate specialized treatments, such as breath-hold fixation treatments, thereby improving the quality of care and / or the accessibility of proton therapy. Embodiments according to the present disclosure also allow for the fast generation of such efficient radiation therapy treatment plans. Thus, embodiments according to the present disclosure specifically improve the field of radiation treatment planning, and generally improve the field of radiation therapy.

[0062] In the example of Figure 1 , the total cost of the example treatment plan is 41,653,704.38 arbitrary units (AU). Figure 2 is a chart 200 depicting the per-spot cost of the layers (energy layers, also referred to herein as treatment layers or simply layers) of an example treatment plan according to embodiments of the present disclosure. Figure 1

[0063] In the example of Figure 2 ​​In the example, the higher point depicted in graph 200 is associated with a higher time cost compared to the lower point depicted in graph 200. Point 205 at the top of graph 200 indicates the point associated with the highest cost determined by a cost function (such as the cost function described above). By removing point 205 from the treatment (energy) layer, the total cost of the treatment plan with the modified layer can be reduced without significantly affecting dosing. After the point is removed, the value of the cost function for the treatment plan with the modified layer can be recalculated based on machine-specific knowledge (e.g., timing constraints of the delivery system). Specifically, for Figures 1-2 The example depicted shows that the elimination of point 205, which has the highest cost, resulted in a reduction of the total cost of the treatment plan by 13,721.95 AU and a reduction of field delivery time by 0.954 seconds, resulting in a field delivery time of 65.727 seconds compared to the original field delivery time of 66.681 seconds.

[0064] Figure 3 An example of a dot scan pattern 300 of a routine treatment plan generated by TPS without optimization or cost reduction is depicted. Figure 3 In the example, point 305 was the most costly point, but none of these points were removed from the original treatment plan based on their time cost. In contrast, Figure 4 An example of a dot scan pattern 400 of a modified treatment plan according to an embodiment of the present disclosure is depicted, in which the highest cost point (point 305) is removed. Figures 3-4 As shown, the elimination of point 305 had no significant dosimetric consequences on the quality of the treatment plan, and as... Figure 5 As shown, there is no impact on the dose statistics of the target, which will be discussed below. Therefore, by excluding point 305 from the treatment plan, the total irradiation time during treatment can be reduced.

[0065] Figure 5 This is a dose-volume histogram (DVH) depicting the dose measurements of a treatment plan modified according to embodiments of this disclosure compared to an unmodified conventional treatment plan. For example... Figure 5 As shown, the dosage determination and treatment quality 505 of the modified treatment plan with reduced total cost were not significantly affected, and no effect on the dose statistics of the target structure was observed in Table 510; however, the treatment time was advantageously reduced.

[0066] Figure 6 An isodose line 600 is depicted as an example of a radiotherapy treatment plan generated and optimized according to embodiments of the present disclosure. The treatment plan is generated by a radiotherapy TPS and is used to control a radiotherapy system (e.g., a proton therapy system) to deliver a prescribed dose of radiation. Figure 6In the example of Figure 1 In the example of Table I, for example, using 8 energy layers and a total of 1872 points, the treatment plan was substantially reduced to a total cost function value of 14,912.01 AU. Moreover, the delivery time of the treatment plan was advantageously and significantly reduced to 25.285 seconds as compared to the original treatment time of 66.681 seconds (Table I). The treatment times for the different layers determined based on machine-specific parameters are represented in Table II below.

[0067] Table II

[0068]

[0069] While the target volume dose statistics were maintained and comparable to the original plan, the decrease in dose conformance can result in an increase in dose to the organs at risk (OARs), which can be observed in the graph 700 of Figure 7 More specifically, in the example of Figure 7 Plan 3 (which is a faster plan with respect to delivery time relative to Plan 4) has a wider lateral penumbra, which can result in higher OAR dose relative to Plan 4, while Plan 4 (which is a slower plan with respect to delivery time relative to Plan 3) has a sharper lateral penumbra, which can result in lower OAR dose relative to Plan 3. Thus, rather than removing points and their associated dose contributions, the dose contribution of the point can be redistributed to neighboring points, which can advantageously reduce the overall dose metric impact of the treatment time optimization / reduction in certain cases, according to some embodiments.

[0070] As described above, the treatment planning system can use machine-specific knowledge to generate a cost function for optimizing field delivery time, for example, according to timing constraints of the delivery system. Some embodiments of the present disclosure can generate an optimized treatment plan based on a prescribed balance between field delivery time and dose metric characteristics according to user input received by the TPS, for example, via a graphical user interface (GUI). For example, as shown in Figure 8 the end 815 of the slider 805 displayed on the graphical GUI 800 biases the optimization of the treatment plan towards reducing delivery time, and the end 810 of the slider 805 biases the optimization of the treatment plan towards minimizing dose metric impact and / or meeting dose metric objectives. Values in the middle of the slider equally prioritize reduced treatment time and dose metric impact to achieve a balance between treatment time and treatment quality / dose metric. By performing plan optimization to remove the most expensive point or points, as Figure 10 and 11AAs shown, adjusting the slider by interacting with the GUI 800 dynamically updates the delivery time information and corresponding dose allocation as well as the dose-volume histogram (DVH) curve. Of course, other forms of input can be used to define the respective weights of treatment time reduction and dose metric preservation, such as buttons, numerical input fields, etc.

[0071] In Figure 9 In the example, the example on-screen graphical user interface 900 includes a numerical input field 905 for defining the relative weight of the treatment time objective (e.g., treatment delivery time objective). When optimizing a treatment plan, a value between 0 and 100 can be entered by the end user to assign zero weight to treatment delivery time when optimizing the treatment plan, full weight (100) so that the dose metric objective is not considered at all, or a weight between 0 and 100 based on a weighted combination of treatment time reduction and dose metric objective to optimize the resulting treatment plan. During optimization, other optimization objectives related to the planned dose metric characteristics can be considered, such as DVH objectives, equivalent uniform dose (EUD) objectives, minimum and maximum dose objectives, dose fall-off (or normal tissue) objectives, etc. Moreover, these objectives can be defined to be robust to multi-scenario optimization. In one embodiment, the complete set of these objectives can be considered the “dose metric objective” for optimization purposes.

[0072] Figure 10 An example of an on-screen graphical user interface 1000 including a slider 1005 defining the respective weight of the dose metric objective to the delivery time objective for generating an optimized treatment plan, e.g., to reduce delivery time without significant dose metric impact, is depicted in accordance with an embodiment of the present disclosure. Adjusting the slider 1005 in the GUI 1000 dynamically updates the delivery time information 1010 and corresponding dose allocation 1015. In this way, a user can conveniently and efficiently define different weights of the dose metric objective and the delivery time objective and immediately view the resulting impact on treatment delivery time and dose allocation. When a desired balance is achieved, an optimized treatment plan can be generated for delivery of the prescribed radiation therapy treatment defined by the optimized treatment plan, advantageously resulting in better overall treatment quality and / or reduced treatment time.

[0073] Figure 11A and 11B An example of an on-screen graphical user interface 1100 including a DVH 1105 and a corresponding dose allocation 1110 is shown in accordance with an embodiment of the present disclosure, the graphical user interface 1100 including a slider 1105 defining the respective weight of the dose metric objective to the delivery time objective for generating an optimized treatment plan, e.g., to reduce delivery time without significant dose metric impact. Adjusting the slider 1105 in the GUI 1100 dynamically updates the delivery time information 1115 and corresponding dose allocation 1120. In this way, a user can conveniently and efficiently define different weights of the dose metric objective and the delivery time objective and immediately view the resulting impact on treatment delivery time and dose allocation. When a desired balance is achieved, an optimized treatment plan can be generated for delivery of the prescribed radiation therapy treatment defined by the optimized treatment plan, advantageously resulting in better overall treatment quality and / or reduced treatment time. Figure 10The point scan pattern 1110 can be generated by any common form of data input defining the respective weights of the dosimetric and delivery time objectives, to generate an optimized treatment plan. By observing the DVH 1105 and the point scan pattern 1110 corresponding to different weights of the dosimetric and delivery time objectives, an optimized plan can be generated that meets the specific needs of the radiation therapy treatment determined by the user input of the clinician (e.g., taking into account any specific constraints of the delivery system).

[0074] The actual dose delivered by a treatment delivery machine often differs from the static dose defined by a radiation therapy treatment plan. Accordingly, some embodiments of the present disclosure can be used as a verification measure to ensure that the dose actually delivered to a patient is reasonable and in compliance with quality control measures implemented for patient safety. For example, the delivery kinetics at the treatment machine can significantly affect the dose actually delivered by the treatment delivery machine compared to the planned static dose distribution in the treatment planning system. Accordingly, the treatment planning system can be equipped with machine-specific delivery kinetics and / or parameterized models to perform a simulated delivery of the treatment plan and provide a result metric to evaluate the delivered dose distribution compared to the planned dose distribution of the radiation therapy treatment plan. In this way, as a safety / quality control measure, unsafe or impractical treatments can be identified and avoided, and a more optimized treatment plan can be generated that delivers a safe and high-quality dose distribution to effectively treat the target volume, e.g., in compliance with health or safety quality standards.

[0075] While several embodiments of the present disclosure disclosed herein generate optimized treatment plans for proton therapy, embodiments of the present disclosure are also well suited for other forms of radiation therapy treatment (e.g., electron beams, photon beams, ion beams, or atomic nucleus beams such as carbon, helium, and lithium). Moreover, the point-filtering optimization method disclosed herein for reducing the overall cost of a treatment plan can be used for biological-driven treatment planning and dose rate optimization in FLASH applications, where the timing in biological-driven treatment planning and FLASH applications is related to the underlying reaction mechanisms, including but not limited to, prevention of radiation-induced hypoxia and DNA damage / repair. The point-filtering optimization process of the present disclosure embodiments can also be used to filter and redistribute dose across fields to take advantage of the full intensity modulation capabilities of the treatment delivery machine. For example, points that significantly contribute to both delivery time and dose can be cross-checked among other contributing fields to determine whether another layer from a different field contributes to dose in a more time-efficient manner.

[0076] According to some embodiments, further extensions of the cost function's penalties are also considered. For example, additional penalties can be associated with fields that require more stringent time limitations due to treatment and beam orientations that can be affected by patient motion. When a four-dimensional computed tomography (4DCT) scan is required during patient simulation, deformable image registration can be performed between the end of inspiration and end of expiration phases. Based on the acquired deformation vector field, it is possible to determine the main motion direction, and penalize dose contributions from points (fields) pointing perpendicular to the main motion direction, while favoring points (fields) pointing more parallel to the main motion direction, thus adapting the plan to the patient's specific needs.

[0077] Figure 12 is a flowchart depicting an example of a sequence of computer-implemented steps of a method or process 1200 for generating an optimized radiation therapy treatment plan that achieves a desired balance between field delivery time and dose based on machine parameters and knowledge, such as machine-specific scan logic and / or maximum treatment time values. The process 1200 can be implemented as program code (instructions) stored in a non-transitory computer-readable storage medium (memory) and executed on a processor.

[0078] At step 1205, a radiation therapy treatment plan is accessed or generated by a radiation therapy treatment planning system. The radiation therapy treatment plan includes a plurality of (one or more) treatment layers having points with associated doses. The treatment delivery time of the points can be determined according to machine-specific knowledge related to a delivery machine that delivers the radiation therapy treatment according to the treatment plan. The cost of the points can be determined according to the dose and the treatment delivery time.

[0079] At step 1210, a weight is assigned to a treatment time objective of the radiation therapy treatment plan. For example, the treatment time objective can include reducing the total treatment time or setting a maximum treatment time.

[0080] At step 1215, one or more points of a layer of the radiation therapy treatment plan are modified (e.g., removed or reassigned as described above) based on the cost of the respective points and the weight assigned to the treatment time objective. According to some embodiments, the one or more points are modified according to the weight assigned to a dose metric objective of the treatment planning system. The dose metric objective can include, for example, a DVH objective, an equivalent uniform dose (EUD) objective, a minimum and maximum dose objective, a dose fall-off (or normal tissue) objective, etc. According to some embodiments, the points are automatically adjusted by the TPS to reduce the cost of the points and the total cost of the treatment plan, thereby reducing the total treatment time for delivering the treatment plan. According to some embodiments, the MU from a point of a layer can be reassigned to a point of an adjacent layer, or a layer can be removed and the points of that layer can be reassigned.

[0081] In step 1220, the optimized radiotherapy treatment plan is generated based on the layer modified in step 1215 and saved to computer memory.

[0082] Embodiments of this disclosure relate to a computer system for planning and optimizing radiotherapy treatment plans based on machine-specific knowledge as described above to reduce delivery time for radiotherapy treatment. A user (e.g., using a GUI) can input a value that defines a relative weight applied to a delivery time target compared to a dosimetry target by removing relatively high-cost points without significant dosimetry impact. As described above, the use of a treatment planning system that executes consistently on a computer system is important for radiotherapy treatment planning as disclosed herein, due to the different parameters that need to be considered, the range of values ​​for these parameters, the interrelationships of these parameters, the need for an effective treatment plan that minimizes patient risk, and the need for rapidly generating high-quality treatment plans. Examples of such computer systems are described in the following discussion.

[0083] exist Figure 13 In the example, the electronic or computer system 1312 includes a central processing unit (CPU) 1301 for running software applications (e.g., a radiotherapy treatment planning system) and an optional operating system. Computer memory includes random access memory 1302 and / or read-only memory 1303, which stores applications and data used by the CPU 1301. Data storage device 1304 provides non-volatile storage for applications and data and may include fixed disk drives, removable disk drives, flash memory devices, and CD-ROMs, DVD-ROMs, or other optical storage devices. Optional user inputs 1306 and 1307 include devices (e.g., a mouse, joystick, camera, touchscreen, and / or microphone) that pass input from one or more users to the computer system 1312.

[0084] The computer system memory includes computer-readable instructions, data structures, program modules, etc., associated with the treatment planning system. The treatment planning system may be distributed across some combination of computer storage media or across some combination of networked computers. According to the embodiments disclosed herein, the treatment planning system is used to evaluate and generate radiotherapy treatment plans.

[0085] The communication or network interface 1308 allows the computer system 1312 to communicate with other computer systems or networks with an electronic communications network, including the Internet or intranets, for example. The display device 1310 can be any device capable of displaying visual information in response to a signal from the computer system 1312, and can include a flat panel touch-sensitive display, for example. The components of the computer system 1312, including the CPU 1301, the memories 1302 and 1303, the data storage device 1304, the user input device 1306, and the graphics subsystem 1305, can be coupled via one or more data buses.

[0086] In Figure 13 In embodiments, the graphics subsystem 1305 is optional and can be coupled with the data buses and components of the computer system 1312. The graphics system 1305 can include a physical graphics processing unit (GPU) and graphics / video memory. The GPU can include one or more rasterizers, transform engines, and geometry engines, and generate pixel data from rendering commands to create output images. The physical GPU can be configured as multiple virtual GPUs that can be used in parallel (e.g., simultaneously) by multiple applications or processes executing in parallel, or multiple physical GPUs can be used simultaneously. The graphics subsystem 1305 can output display data to the display device 1310, for example, to visualize DVHs and dose distributions of a modified treatment plan, and present sliders or input fields on the display device 1310 with a graphical user interface.

[0087] In radiation therapy treatment techniques such as intensity modulated radiation therapy (IMRT), intensity modulated particle therapy (IMPT), and spot scanning (e.g., pencil beam scanning), where the intensity of the particle beam is constant or modulated across the entire delivery area, the beam intensity is varied across each treatment area (volume in the treatment target) of the patient. Depending on the treatment modality, the degrees of freedom available for intensity modulation include, but are not limited to, beam shaping (collimation), beam weighting (spot scanning), number and arrangement of spots, and angle of incidence (which can be referred to as beam geometry). These degrees of freedom result in an effectively infinite number of potential treatment plans, and thus the ability to consistently and efficiently generate and evaluate high quality treatment plans is beyond the capability of humans and relies on the use of computer systems, particularly given the time constraints associated with using radiation therapy to treat diseases such as cancer, and the large number of patients undergoing or needing to undergo radiation therapy during any given time period.

[0088] Embodiments of the present disclosure are therefore described. While the present disclosure has been described in specific embodiments, the present disclosure should not be construed as limited to these embodiments, but only as defined by the appended claims.

Claims

1. A computer-implemented method for radiotherapy treatment planning, the method comprising: accessing a radiotherapy treatment plan comprising a plurality of treatment layers, each of the plurality of treatment layers comprising a plurality of points; receiving a weight for a treatment time objective of the radiotherapy treatment plan; modifying the points based on the weight and a cost of a point from a treatment layer of the plurality of treatment layers to produce a modified treatment layer; and generating a modified radiotherapy plan using the modified treatment layer.

2. The method of claim 1, further comprising modifying a plurality of points of the plurality of treatment layers to produce a plurality of modified treatment layers, wherein the generating the modified radiofrequency treatment plan is performed using the plurality of modified treatment layers.

3. The method of claim 1, wherein modifying the points comprises an operation selected from the group consisting of: removing the point; modifying the point to reduce the cost of the point; and reassigning a dose contribution of the point to one or more neighboring points.

4. The method of claim 1, further comprising receiving a weight for a dose metric objective of the radiotherapy treatment plan.

5. The method of claim 4, wherein the dose metric objective is selected from the group consisting of: a dose volume histogram (DVH) objective; an equivalent uniform dose (EUD) objective; a minimum dose objective; a maximum dose objective; and a dose fall-off objective. dynamically presenting a dose volume histogram on a graphical user interface of a treatment planning system based on the weight for the treatment time objective of the modified radiotherapy treatment plan and the weight for a dose metric objective of the radiotherapy treatment plan.

6. The method of claim 4, further comprising:

7. The method of claim 6, wherein the weight for the treatment time objective and the weight for the dose metric objective are defined according to positions of respective sliders presented on the graphical user interface of the treatment planning system.

8. The method of claim 1, further comprising:

8. The method of claim 1, further comprising: simulating a radiotherapy treatment according to the modified radiotherapy treatment plan to determine whether an actual dose would meet a predefined treatment quality standard when applied according to the modified radiotherapy treatment plan.

9. The method of claim 1, wherein modifying the points comprises: calculating, for each point of the plurality of points, a cost of the point based on a dose associated with the point and a delivery duration of the point; and modifying at least one point of the plurality of points having a highest cost.

10. An electronic system for radiotherapy treatment planning, the system comprising: a display device; a memory coupled to the display device; and a processor in communication with the memory, wherein the processor is operable to execute instructions for performing a method for performing radiotherapy treatment planning, the method comprising: accessing a radiotherapy treatment plan comprising a plurality of treatment layers, each of the plurality of treatment layers comprising a plurality of points; assigning a weight for a treatment time objective of the radiotherapy treatment plan using input received from a graphical user interface presented on the display device; ​ modify the point based on the weight and a cost of the point from a treatment layer of the plurality of treatment layers to produce a modified treatment layer; and generate a modified radiotherapy treatment plan using the modified treatment layer, wherein the modified radiotherapy treatment plan is operable to be executed by a delivery machine to apply radiotherapy treatment to a target according to the modified radiotherapy treatment plan.

11. The electronic system of claim 10, wherein the method further comprises modifying a plurality of points of the plurality of treatment layers to produce a plurality of modified treatment layers, wherein the generating the modified radiofrequency treatment plan is performed using the plurality of modified treatment layers.

12. The electronic system of claim 10, wherein modifying the point comprises an operation selected from the group consisting of: removing the point; modifying the point to reduce the cost of the point; and reassigning a dose contribution of the point to one or more adjacent points.

13. The electronic system of claim 10, wherein the method further comprises assigning a weight to a dose metric objective of the radiotherapy treatment plan.

14. The electronic system of claim 13, wherein the dose metric objective is selected from the group consisting of: a dose volume histogram (DVH) objective; an equivalent uniform dose (EUD) objective; a minimum dose objective; a maximum dose objective; and a dose fall-off objective.

15. The electronic system of claim 13, wherein the method further comprises: dynamically present a dose volume histogram on the graphical user interface based on the weight of the treatment time objective for the modified radiotherapy treatment plan and the weight of a dose metric objective for the modified radiotherapy treatment plan.

16. The electronic system of claim 13, wherein the weight for the treatment time objective and the weight for the dose metric objective are defined according to a position of a respective slider presented on the graphical user interface.

17. The electronic system of claim 10, wherein the method further comprises: simulate radiotherapy treatment according to the modified radiotherapy treatment plan to determine whether an actual dose would meet a predefined treatment quality standard when applied according to the modified radiotherapy treatment plan.

18. The electronic system of claim 10, wherein modifying the point comprises: calculating a cost of the point based on a dose associated with the point and a delivery duration of the point for each point of the plurality of points; and modifying at least one point of the plurality of points having a highest cost.

19. A non-transitory computer-readable storage medium containing instructions that, when executed by a processor, cause the processor to perform a method of radiotherapy treatment planning, the method comprising: accessing a radiotherapy treatment plan comprising a plurality of treatment layers, each treatment layer of the plurality of treatment layers comprising a plurality of points; assigning a weight to a treatment time objective of the radiotherapy treatment plan based on received input; modifying the points based on the weight and a cost of the points from a treatment layer of the plurality of treatment layers to produce a modified layer; and and generating a modified radiation therapy plan using the modified treatment layers, wherein the modified radiation therapy treatment plan is operable to be executed by a delivery machine to apply radiation therapy treatment to a target in accordance with the modified treatment plan.

20. The non-transitory computer readable storage medium of claim 19, wherein the method further comprises modifying a plurality of points of the plurality of treatment layers to produce a plurality of modified treatment layers, wherein the generating the modified radio frequency treatment plan is performed using the plurality of modified treatment layers.

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