Delivery machine restriction guided radiation therapy treatment planning

Abstract

The invention relates to delivery machine restriction guided radiation therapy treatment planning. A system for planning a radiation therapy treatment to be performed by a radiation therapy machine includes at least one processor and a memory storing computer executable instructions. The at least one processor is configured to execute the computer executable instructions to cause the system to generate a radiation therapy treatment plan specifying a plurality of energy layers associated with a plurality of spots in a treatment target. The radiation therapy treatment plan is based on a plurality of minimum monitoring unit values, each minimum monitoring unit value of the plurality of minimum monitoring unit values for a respective energy layer of the plurality of energy layers. Each minimum monitoring unit value of the plurality of minimum monitoring unit values is based on a machine parameter of the radiation therapy machine and / or based on a minimum monitoring unit objective function of the radiation therapy machine.

Description

Technical Field

[0001] One or more example embodiments relate to radiation therapy treatment planning and radiation therapy treatment. Background Art

[0002] Radiation therapy involves directing beams of high-energy proton, photon, ion, or electron radiation into a target volume in the treatment target of unhealthy tissue (eg, a tumor or lesion).

[0003] Before radiation therapy is performed on a patient, a treatment plan specific to that patient is developed. The treatment plan defines various aspects of the radiation therapy using simulations and optimizations that may be based on past experience. Typically, the goal of a treatment plan is to deliver sufficient radiation to unhealthy tissue while minimizing exposure of surrounding healthy tissue to that radiation. Summary of the invention

[0004] The scope of protection sought for the various example embodiments is set out by the independent claims. Example embodiments and / or features described in this specification that do not fall within the scope of the independent claims, if any, are to be construed as examples useful for understanding the various embodiments.

[0005] At least one example embodiment provides a system for planning a radiation therapy treatment to be performed by a radiation therapy machine. The system includes at least one processor and a memory storing computer executable instructions. The at least one processor is configured to execute the computer executable instructions so that the system generates a radiation therapy treatment plan, the radiation therapy treatment plan indicating a plurality of energy layers associated with a plurality of spots in a treatment target, the radiation therapy treatment plan being based on a plurality of minimum monitoring unit values, each of the plurality of minimum monitoring unit values ​​being for a corresponding energy layer among the plurality of energy layers, and each of the plurality of minimum monitoring unit values ​​being based on a machine parameter of the radiation therapy machine.

[0007] At least one other example embodiment provides a radiation therapy treatment system, comprising: a system for planning a radiation therapy treatment; and a radiation therapy machine configured to provide the radiation therapy treatment according to the radiation therapy treatment plan. The system for planning a radiation therapy treatment comprises at least one processor and a memory storing computer executable instructions. The at least one processor is configured to execute the computer executable instructions so that the system generates a radiation therapy treatment plan, the radiation therapy treatment plan indicating a plurality of energy layers associated with a plurality of spots in a treatment target, the radiation therapy treatment plan being based on a plurality of minimum monitoring unit values, each of the plurality of minimum monitoring unit values ​​being for a corresponding energy layer among the plurality of energy layers, and each of the plurality of minimum monitoring unit values ​​being based on a machine parameter of the radiation therapy machine.

[0008] At least one other example embodiment provides a system for planning a radiation therapy treatment to be performed by a radiation therapy machine. The system includes a component for generating a radiation therapy treatment plan, the radiation therapy treatment plan indicating a plurality of energy layers associated with a plurality of spots in a treatment target, the radiation therapy treatment plan being based on a plurality of minimum monitoring unit values, each of the plurality of minimum monitoring unit values ​​being for a respective energy layer among the plurality of energy layers, and each of the plurality of minimum monitoring unit values ​​being based on a machine parameter of the radiation therapy machine.

[0009] At least one other example embodiment provides a method for planning a radiation therapy treatment to be performed by a radiation therapy machine, the method comprising: generating a radiation therapy treatment plan indicating multiple energy layers associated with multiple spots in a treatment target, the radiation therapy treatment plan being based on multiple minimum monitoring unit values, each of the multiple minimum monitoring unit values ​​being for a corresponding energy layer among the multiple energy layers, and each of the multiple minimum monitoring unit values ​​being based on a machine parameter of the radiation therapy machine.

[0010] At least one other example embodiment provides a non-transitory computer-readable medium storing computer-executable instructions which, when executed by at least one processor, cause the at least one processor to perform a method for planning a radiation therapy treatment to be performed by a radiation therapy machine, the method comprising: generating a radiation therapy treatment plan indicating a plurality of energy layers associated with a plurality of spots in a treatment target, the radiation therapy treatment plan being based on a plurality of minimum monitoring unit values, each of the plurality of minimum monitoring unit values ​​being for a corresponding energy layer among the plurality of energy layers, and each of the plurality of minimum monitoring unit values ​​being based on a machine parameter of the radiation therapy machine.

[0011] According to one or more example embodiments, the machine parameters may include at least one of: a monitoring unit rate range of the radiation therapy machine, a minimum spot duration of the radiation therapy machine, or a transmission parameter of the radiation therapy machine.

[0012] The at least one processor can be configured to execute computer-executable instructions so that the system: calculates a minimum deliverable monitoring unit value for a first energy layer among multiple energy layers based on machine parameters of the radiation therapy machine; calculates a monitoring unit rate saturation point for the first energy layer based on the machine parameters of the radiation therapy machine; and determines a minimum monitoring unit value for the first energy layer based on the minimum deliverable monitoring unit value for the first energy layer and the monitoring unit rate saturation point.

[0013] The at least one processor may be configured to execute computer-executable instructions to cause the system to determine a plurality of minimum monitoring unit values ​​based on a minimum monitoring unit saturation curve of the radiation therapy machine, the minimum monitoring unit saturation curve being derived based on machine parameters of the radiation therapy machine.

[0014] The minimum monitoring unit saturation curve may indicate a minimum deliverable monitoring unit value and a monitoring unit rate saturation point for each of a plurality of energy tiers.

[0015] The minimum deliverable monitoring unit value and the monitoring unit rate saturation point for each energy layer in the plurality of energy layers may be based on machine parameters of the radiation therapy machine.

[0016] At least one example embodiment provides a system for planning a radiation therapy treatment to be performed by a radiation therapy machine. The system includes at least one processor and a memory storing computer executable instructions. The at least one processor is configured to execute the computer executable instructions so that the system generates a radiation therapy treatment plan, the radiation therapy treatment plan indicating a plurality of energy layers associated with a plurality of spots in a treatment target, the radiation therapy treatment plan having a plurality of minimum monitoring unit values, the plurality of minimum monitoring unit values ​​being generated based on a minimum monitoring unit objective function of the radiation therapy machine.

[0017] At least one other example embodiment provides a radiation therapy treatment system, the radiation therapy treatment system comprising: a system for planning a radiation therapy treatment; and a radiation therapy machine configured to provide the radiation therapy treatment according to the radiation therapy treatment plan. The system for planning a radiation therapy treatment comprises at least one processor and a memory storing computer executable instructions. The at least one processor is configured to execute the computer executable instructions so that the system generates a radiation therapy treatment plan indicating a plurality of energy layers associated with a plurality of spots in a treatment target, the radiation therapy treatment plan having a plurality of minimum monitoring unit values, the plurality of minimum monitoring unit values ​​being generated based on a minimum monitoring unit objective function of the radiation therapy machine.

[0018] At least one example embodiment provides a system for planning a radiation therapy treatment to be performed by a radiation therapy machine. The system includes a component for generating a radiation therapy treatment plan, the radiation therapy treatment plan indicating a plurality of energy layers associated with a plurality of spots in a treatment target, the radiation therapy treatment plan having a plurality of minimum monitoring unit values ​​generated based on a minimum monitoring unit objective function of the radiation therapy machine.

[0019] At least one example embodiment provides a method for planning a radiation therapy treatment to be performed by a radiation therapy machine, the method comprising: generating a radiation therapy treatment plan indicating a plurality of energy layers associated with a plurality of spots in a treatment target, the radiation therapy treatment plan having a plurality of minimum monitoring unit values ​​generated based on a minimum monitoring unit objective function of the radiation therapy machine.

[0020] At least one example embodiment provides a non-transitory computer-readable medium storing computer-executable instructions that, when executed by at least one processor, cause the at least one processor to perform a method for planning a radiation therapy treatment to be performed by a radiation therapy machine, the method comprising: generating a radiation therapy treatment plan indicating a plurality of energy layers associated with a plurality of spots in a treatment target, the radiation therapy treatment plan having a plurality of minimum monitoring unit values ​​generated based on a minimum monitoring unit objective function of the radiation therapy machine.

[0021] According to one or more example embodiments, the at least one processor may be configured to execute computer-executable instructions to cause the system to derive a minimum monitoring unit objective function based on machine parameters of the radiation therapy machine.

[0022] Each minimum monitoring unit value of the plurality of minimum monitoring unit values ​​may be associated with a corresponding energy tier among the plurality of energy tiers.

[0023] The at least one processor may be configured to execute computer-executable instructions to cause the system to: generate a radiation therapy treatment plan based on at least a minimum monitoring unit objective function, a dosimetry objective function, and a weighting factor.

[0024] The minimum monitoring unit objective function can be the sum of piecewise linear energy layer and spot cost functions.

[0025] At least one example embodiment provides a system for planning a radiation therapy treatment to be performed by a radiation therapy machine. The system includes at least one processor and a memory storing computer executable instructions. The at least one processor is configured to execute the computer executable instructions so that the system: generates a radiation therapy treatment plan for a treatment target based on a minimum monitoring unit value calculated for each of a plurality of energy layers specified by the radiation therapy treatment plan, each minimum monitoring unit value being based on a machine parameter of the radiation therapy machine.

[0026] At least one other example embodiment provides a system for radiation therapy treatment, the system comprising: a system for planning radiation therapy treatment; and a radiation therapy machine configured to apply the radiation therapy treatment according to the radiation therapy treatment plan. The system for planning radiation therapy treatment comprises at least one processor and a memory storing computer executable instructions. The at least one processor is configured to execute the computer executable instructions so that the system: generates a radiation therapy treatment plan for a treatment target based on a minimum monitoring unit value calculated for each of a plurality of energy layers specified by the radiation therapy treatment plan, each minimum monitoring unit value being based on a machine parameter of the radiation therapy machine.

[0027] At least one other example embodiment provides a system for planning a radiation therapy treatment to be performed by a radiation therapy machine. The system includes a component for generating a radiation therapy treatment plan for a treatment target based on a minimum monitoring unit value calculated for each of a plurality of energy layers specified by the radiation therapy treatment plan, each minimum monitoring unit value being based on a machine parameter of the radiation therapy machine.

[0028] At least one other example embodiment provides a method for planning a radiation therapy treatment to be performed by a radiation therapy machine, the method comprising: generating a radiation therapy treatment plan for a treatment target based on minimum monitoring unit values ​​calculated for each of a plurality of energy layers specified by the radiation therapy treatment plan, each minimum monitoring unit value being based on a machine parameter of the radiation therapy machine.

[0029] At least one other example embodiment provides a non-transitory computer-readable medium storing computer-executable instructions which, when executed by at least one processor, cause the at least one processor to perform a method for planning a radiation therapy treatment to be performed by a radiation therapy machine, the method comprising: generating a radiation therapy treatment plan for a treatment target based on minimum monitoring unit values ​​calculated for each of a plurality of energy layers specified by the radiation therapy treatment plan, each minimum monitoring unit value being based on a machine parameter of the radiation therapy machine.

[0030] According to one or more example embodiments, the at least one processor may be configured to execute computer executable instructions to cause the system to: generate a radiation therapy treatment plan by performing optimization based on a minimum monitoring unit value for each of a plurality of energy layers.

[0031] The machine parameters may include at least one of: a monitoring unit rate range of the radiation therapy machine, a minimum spot duration of the radiation therapy machine, or a transmission parameter of the radiation therapy machine.

[0032] The at least one processor can be configured to execute computer-executable instructions so that the system: calculates a minimum deliverable monitoring unit value for a first energy layer among multiple energy layers based on machine parameters of the radiation therapy machine; calculates a monitoring unit rate saturation point for the first energy layer based on the machine parameters of the radiation therapy machine; and determines a minimum monitoring unit value for the first energy layer based on the minimum deliverable monitoring unit value for the first energy layer and the monitoring unit rate saturation point.

[0033] The at least one processor can be configured to execute computer-executable instructions to cause the system to: calculate a minimum monitoring unit value for each of a plurality of energy layers based on a minimum monitoring unit saturation curve of the radiation therapy machine, wherein the minimum monitoring unit saturation curve is derived based on machine parameters of the radiation therapy machine. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Example embodiments will be more fully understood from the detailed description and drawings given below, in which like elements are represented by like reference numerals, which are given by way of illustration only and thus do not limit the present disclosure.

[0035] Figure 1 is a block diagram of an example of a system upon which one or more example embodiments may be implemented.

[0036] Figure 2A and Figure 2B An example of a beam viewing angle for treating a target is shown according to an example embodiment.

[0037] Figure 3 and Figure 4 is a block diagram illustrating an example of an automated radiation therapy treatment planning process according to an example embodiment.

[0038] Figure 5 is a functional block diagram illustrating a simplified example intensity modulated particle therapy (IMPT) optimization workflow according to an example embodiment.

[0039] Figure 6 is a flow chart illustrating a method for radiation therapy treatment planning and treatment according to an example embodiment.

[0040] Figure 7 is a flow chart illustrating an example embodiment of a method for determining a minimum monitoring unit (MU) for an energy layer according to an example embodiment.

[0041] Figure 8 is a flow chart illustrating an example embodiment of a method for generating a deliverable radiation plan according to an example embodiment.

[0042] Fig. 9is a flow chart illustrating another method for radiation therapy treatment planning and treatment according to an example embodiment.

[0043] Fig.10 is a graph showing an example saturation curve and minimum deliverable MU for a delivery machine according to an example embodiment.

[0044] It should be noted that these figures are intended to illustrate the general characteristics of methods, structures, and / or materials utilized in certain example embodiments and to supplement the written description provided below. However, these drawings are not to scale and may not accurately reflect the precise structural or performance characteristics of any given embodiment, and should not be interpreted as defining or limiting the range of values ​​or properties encompassed by the example embodiments. The use of similar or identical reference numerals in the various drawings is intended to indicate the presence of similar or identical elements or features. DETAILED DESCRIPTION

[0045] Various example embodiments will now be described more fully with reference to the accompanying drawings, in which some example embodiments are shown.

[0046] Detailed illustrative embodiments are disclosed herein. However, the specific structural and functional details disclosed herein are representative only for the purpose of describing the exemplary embodiments. However, the exemplary embodiments may be embodied in many alternative forms and should not be construed as being limited to the embodiments set forth herein.

[0047] It should be understood that the exemplary embodiments are not intended to be limited to the specific forms disclosed. On the contrary, the exemplary embodiments will cover all modifications, equivalents and substitutions falling within the scope of the present disclosure. Throughout the description of the drawings, similar reference numerals refer to similar elements.

[0048] As discussed herein, the terms "one or more" and "at least one" may be used interchangeably.

[0049] As discussed herein, a radiation therapy treatment plan may also be referred to as a radiation treatment plan, a treatment plan, or a plan. Furthermore, the terms "proposed" and "candidate" may be used interchangeably in the context of radiation therapy treatment plans.

[0050] It will be appreciated that various example embodiments may be used in combination.

[0051] Unless specifically stated otherwise, as will be apparent from the following discussion, it should be recognized that throughout this disclosure, discussions utilizing terms such as "access," "determine," "store," "assign," "adjust," "combine," "sum," "add," "optimize," "minimize," "produce," "generate," "identify," "set," "increase," "evaluate," "compute," etc., may refer to actions and processes of a computer system or similar electronic computing device or processor. A computer system or similar electronic computing device manipulates and transforms data, which is represented as physical (electronic) quantities within a computer system memory, registers, or other such information storage, transmission, or display device.

[0052] The following discussion may include terms such as "weight," "metric," "intensity," "monitoring unit," etc. Unless otherwise noted, a value is associated with each such term. For example, a weight (e.g., a weight of a spot or a beamlet) has a value, and a metric has a value. For simplicity, the term "weight" or "metric" or "intensity" or "monitoring unit" may refer to the value of the weight or metric or intensity or monitoring unit itself, unless otherwise noted or apparent from the discussion.

[0053] Although example embodiments may be discussed herein with respect to intensity modulated particle therapy (IMPT) (spot or pencil beam scanning), example embodiments should not be limited to this example. Rather, example embodiments may also be applicable to IMRT.

[0054] Figure 1 is a block diagram of an example of a system on which one or more example embodiments may be implemented. The system includes a computer system 100 and a radiation therapy machine 1000 in bidirectional communication with each other.

[0055] The radiation therapy machine 1000 may be a treatment modality for providing radiation therapy treatments, such as intensity modulated radiation therapy (IMRT) or intensity modulated particle therapy (IMPT). These radiation therapy treatments will be discussed in more detail later.

[0056] Computer system 100 includes at least one central processing unit (or other processing circuitry) 102, memory 104, removable storage devices 108, non-removable storage devices 120, and communication connection(s) 122 to enable the system to communicate with other devices (e.g., in a networked environment using logical connections to one or more remote computers).

[0057] The system 100 also includes one or more input devices 124 (e.g., a keyboard, a mouse, a pen, a voice input device, a touch screen or other input device, etc.) and one or more output devices 126, such as a display device, a speaker, a printer, etc. The display device can be, for example, a cathode ray tube display, a light emitting diode display, a liquid crystal display, a touch screen display, a combination thereof, etc.

[0058] exist Figure 1 , the memory 104 includes computer-readable instructions, data structures, program modules, etc. associated with a treatment planning system (TPS) 150, which may also be referred to as an optimizer. However, the TPS 150 may alternatively reside in any of the computer storage media used by the system 100, may be distributed on some combination of computer storage media, may be distributed on some combination of networked computers, or may exist in the cloud. As discussed later, the TPS 150 is configured to generate, optimize, and evaluate radiation treatment plans (e.g., candidate or proposed treatment plans), and produce a final (optimized and deliverable) treatment plan. The final treatment plan may be used to apply a radiation therapy treatment to a treatment target of a patient via the radiation therapy machine 1000.

[0059] With respect to treatment modalities, in IMRT, a photon beam comprises a plurality of beam segments or beamlets as specified by a treatment plan. A multi-leaf collimator (MLC) is used to shape the beam before or while the beam is directed into a treatment target. In one or more such embodiments, a maximum energy of the beam is specified (e.g., 80 MeV), and the energy of each of the beamlets is determined as a percentage (100% or less) or an equivalent fraction of the maximum beam energy. Thus, each of the beamlets can be weighted based on its energy layer. By weighting based on the energy of each beamlet, each beamlet is actually also weighted based on its intensity. The weight of each beamlet can be expressed as a monitoring unit (MU).

[0060] In IMPT (e.g., spot or pencil beam scanning), a proton or ion beam is directed to a spot in a treatment target as specified by a treatment plan. For each energy slice of the beam, the specified spot locations are typically arranged in a fixed (grid) pattern, and the beam is delivered on a fixed scan path within the energy slice. Each spot can be weighted based on, for example, the number of protons received at that spot when irradiated by the beam. The weight of each spot can be expressed as a value of a monitoring unit (e.g., number of protons) or MU.

[0061] Radiation therapy treatment plans (e.g., optimized, deliverable, and / or candidate) include parameters that can affect dose and / or dose rate, as well as values ​​for other parameters. Depending on the treatment modality, the parameters may include, but are not limited to: beam shape (collimation); the number and arrangement of spots for spot (pencil beam) scanning, and spot weights; beamlet weights; beamlet intensity or energy; beam / beamlet direction; specified dose and specified dose rate; the number of irradiations of the target volume; the duration of each irradiation in the irradiation (irradiation time); and the dose deposited in each irradiation in the irradiation. Parameters may also include time periods during which irradiations are applied (e.g., multiple irradiations are applied in a time period such as one hour, where each irradiation in the time period is separated from the next irradiation by another time period) and the time interval between each period of irradiation (e.g., each one-hour long period is separated from the next one-hour long period by one day).

[0062] The relatively large number of parameters and the range of their values ​​may result in a virtually unlimited number of potential treatment plans, and thus consistently and efficiently generating and evaluating high quality treatment plans is far beyond the capabilities of the human mind and relies on the use of computing systems.

[0063] To deliver a specified radiation dose / dose rate, the radiation treatment plan may be converted (e.g., by TPS 150) into radiation therapy application parameters of a radiation therapy machine (e.g., radiation therapy machine 1000). The radiation therapy application parameters may include, for example, the beam current of a proton, ion, or photon beam, the number of protons, ions, or photons per time period to be emitted by the accelerator, the magnet current, settings for achieving a specified energy of protons, ions, or photons at a target volume, and / or a measurement range of a dose monitoring system.

[0064] During treatment, the beam enters a nozzle of the radiation therapy machine 1000, which may include one or more components that affect (e.g., reduce, modulate, etc.) the energy of the beam to control the dose / dose rate delivered by the beam and / or control the dose-to-depth curve of the beam, depending on the type of beam. For example, for a proton beam or ion beam having a Bragg peak, the nozzle may control the position of the Bragg peak in the treatment target laterally relative to the beam axis. In other examples, energy modulation is performed external to the nozzle (e.g., upstream of the nozzle).

[0065] The nozzle is mounted on a movable gantry so that the beam can be delivered from different directions (angles) relative to the patient (treatment target) on the patient support device, and the position of the patient support device relative to the beam can also be changed.

[0066] Figure 2AExamples of beam viewing angles of a treatment target 208 in some (e.g., IMPT) example embodiments are shown. The treatment target 208 may conform to the shape of the treated volume (e.g., the contour of the treatment target may conform to the contour of a tumor), the treatment target may be larger than the treated volume, or the treatment target may correspond to a portion of the treated volume (e.g., a sub-volume).

[0067] In these example embodiments, an arrangement of spots (e.g., spots 204 and 206) is mapped onto a treatment target 208. Each spot corresponds to a specific location in the treatment target 208. The spots in the treatment target 208 can be irradiated with a raster scan (two-dimensional emission) of a spot scanning beam (pencil beam). In general, a first pencil beam is aimed at a first spot 204 in the treatment target 208, and a dose rate is delivered to the spot, then a second pencil beam is aimed at a second spot 206 in the treatment target, and a dose rate is delivered to the second spot 206, and so on. Spots with a weight or MU below a minimum MU (e.g., spots with a zero weight or MU) are not irradiated.

[0068] Each spot scanning beam can deliver a relatively high dose rate (relatively high dose in a relatively short period of time) to each spot. For example, if necessary, the spot scanning beam can deliver more than 40 Gray (Gy) to each spot in less than a second.

[0069] Figure 2B Examples of beam viewing angles of a treatment target 208 in other (e.g., IMRT) example embodiments are shown. In these example embodiments, a beam 220 for irradiating the treatment target 208 includes an array of beamlets (e.g., beamlets 214 and 216) mapped onto the treatment target 208. Each beamlet corresponds to a specific location in the treatment target 208. A maximum energy of the beam 220 is specified, and the energy of each of the beamlets 214, 216, etc. is determined as a percentage or fraction of the maximum beam energy.

[0070] As with spot scanning, each beamlet is capable of delivering a relatively high dose rate (relatively high dose in a relatively short period of time). For example, if desired, each beamlet can deliver more than 40 grays (Gy) in less than a second. Beamlets with weights or MUs below a minimum MU (e.g., beamlets with zero weights or MUs) are not used during treatment.

[0071] Figure 3 is a block diagram illustrating an example of an automated radiation therapy treatment planning and treatment process 300 according to an example embodiment. The process 300 may be implemented in whole or in part as Figure 1 Computer system 100 and radiation therapy machine 1000 in / using Figure 1The computer system 100 and the radiation therapy machine 1000 may be implemented by software programs, hardware logic, or a combination thereof, or in combination thereof.

[0072] refer to Figure 3 In step 302, the computer system 100 obtains a three-dimensional (3D) image of the patient and segments and contours organs and other structures in the patient (patient geometry). In steps 304 and 306, as will be described below with respect to Figure 4 As discussed in greater detail, the system 100 develops and evaluates a radiation therapy treatment plan based on the information obtained in step 302 and other information.

[0073] In step 308, if the treatment plan developed by the system 100 is satisfactory (e.g., meets the specified clinical goals), the radiation therapy treatment plan can be used for treatment of the patient (e.g., using the radiation therapy machine 1000). If not, the system 100 can iteratively modify aspects of the treatment plan and / or clinical goals until a satisfactory plan is generated, and the satisfactory radiation therapy treatment plan can then be utilized for treatment of the patient (e.g., using the radiation therapy machine 1000). The clinical goals can be expressed in terms of, for example, a set of quality metrics, such as target uniformity, fitness with treatment targets, critical organ sparing, etc., with corresponding target values ​​for the quality metrics.

[0074] Figure 4 4 is a block diagram illustrating an example of an automated radiation therapy treatment planning process 400 according to an example embodiment. The process 400 may be implemented in whole or in part as Figure 1 System 100 on / using Figure 1 The process 400 may be performed by a software program, hardware logic, or a combination thereof of the system 100. For example, the process 400 may be performed at the TPS 150. The process 400 generally corresponds to Figure 3 Steps 304 and 306 in .

[0075] refer to Figure 4 , TPS150 (for example, from Figure 1 The TPS 150 may also access or receive information specific to the patient to be treated (e.g., the patient geometry discussed above), including information describing the treatment target (region of interest (ROI)), which may include a planned target volume (PTV), a gross tumor volume (GTV), a clinical target volume (CTV), and / or organs at risk (OARs).

[0076] The TPS 150 also accesses or receives an objective function defined for the treatment of the patient. An objective function is a mathematical formula of variables (such as parameters of the above parameters) that may have an impact on achieving specified clinical goals. The objective function is used to evaluate a proposed radiation therapy treatment plan to determine whether the clinical goals specified for the treatment of the patient are met.

[0077] An example of a dose objective function f(d) is: f(d)=∑(w i )(d i –d p ) 2 ), where w i is the weight of each voxel in the treatment target, d i is the dose per voxel planned to receive according to the proposed treatment plan, d p is the specified dose for each voxel, and the sum ∑ is over all voxels i in the treatment target. A voxel may be a spot in the treatment target irradiated by a spot scanning beam, or may correspond to a location in the treatment target to which a beamlet is directed. In this example, the goal is to minimize the value of a dose objective function (in this example, as the value of the function decreases, the dose across the treatment target becomes more uniform). In practice, there may be several objective functions (in addition to the dose objective function) to be minimized in order to achieve a final (e.g., optimal final) treatment plan. Some other objective functions according to example embodiments will be discussed in more detail later. Objective functions may conflict with each other; that is, minimizing one objective function may be detrimental to another objective function, and therefore minimizing all objective functions may not be achievable. Therefore, in an example embodiment, the objective functions may be weighted and summed to provide a sum of all objective functions (F Tot ), and then this sum can be minimized.

[0078] Still reference Figure 4 For IMPT, for example, the information accessed or received by TPS 150 may include, but is not limited to, the number and location (pattern or arrangement) of spots, the value (e.g., initial value) of the weight of each spot in the treatment target, and a dosimetry objective function that takes into account the dose targets of the PTV and OARs. The weight of each spot may be expressed as a value of MU corresponding to, for example, the number of particles (e.g., protons or ions) per spot. As described above with respect to Figure 2A As noted, each blob corresponds to a location in the treatment target. As such, each blob weight may be referred to as a "positional" weight or a position-based weight: a blob corresponds to a location, a weight corresponds to a blob, and thus a blob weight corresponds to a location. In essence, according to example embodiments, a blob weight is assigned to or associated with a corresponding location within the treatment target.

[0079] In another example, for IMRT, the information accessed or received by TPS 150 may include, but is not limited to, the number of beamlets, the value (e.g., initial value) of the weight of each beamlet (where the weight corresponds to a fraction or percentage of the beam energy), and a dosimetry objective function that takes into account the dose targets for the PTV and OARs. The weight of each beamlet may also be expressed as a value of MU corresponding to the intensity or energy of the beamlet, for example, as a fraction or percentage of the beam intensity or energy. As described above with respect to Figure 2B As noted, each beamlet corresponds to a location in the treatment target. Similar to the speckle weights, each beamlet weight may be referred to as a weight on location or a location-based weight: a beamlet corresponds to a location, a weight corresponds to a beamlet, and thus a beamlet weight corresponds to a location. Essentially, according to these example embodiments, beamlet weights are assigned to or associated with corresponding locations inside the treatment target.

[0080] When generating and optimizing radiation treatment plans involving modulated scan plans, the quality of the treatment is affected, among other things, by the minimum MU (minMU) of the treatment plan. Traditionally, in the context of IMPT plan optimization, for example, the minimum MU is considered a system-level parameter that specifies the minimum amount of dose that a single spot is allowed to deliver. The minimum MU for a treatment plan is selected to suit the radiation therapy treatment system (also called the delivery system) and the treatment planning requirements, where the minimum amount of radiation that can be delivered by the delivery system (minimum allowable or minimum deliverable MU) specifies the lowest minimum MU that can be selected for the treatment plan. In addition to the minimum allowable MU constraint, the minimum MU can be selected to balance the dosimetric quality of the treatment plan with the time it takes per plan to deliver the treatment (treatment or delivery time).

[0081] Conventional system-level (or global) minimum MU requires identifying a universal value that is deliverable at all beam energies and is an appropriate compromise between delivery speed and target dose quality. However, in cases where the selected minimum MU is a function of beam energy and a normal IMPT plan includes multiple energy slices, any global minimum MU may not provide an optimal compromise across all energy slices. That is, for example, there may be cases where, for an energy slice, a minimum MU different from the global minimum MU can improve delivery time without sacrificing plan quality, or vice versa.

[0082] For example, the global minimum MU may lead to a situation where the upper limit of the delivery speed of the delivery machine is exceeded at the lower energy layer and / or the upper limit of the delivery speed is not reached at the higher energy layer. This may result in lower plan quality without delivery time improvement and / or slower delivery time without plan quality improvement.

[0083] One or more example embodiments address at least the above situation by utilizing a per-layer minimum MU guided by delivery machine parameters rather than a global minimum MU. Machine parameters may also be referred to as machine limitations, machine parameter limitations, delivery limitations, physical delivery limitations, etc. In at least one example embodiment, the TPS may determine the minimum MU on a per-energy layer basis rather than globally. The minimum MU may be based on machine parameters of the radiation therapy machine.

[0084] According to one or more example embodiments, machine limits may be used as one of the boundary conditions of MU. However, example embodiments may also be applicable to instances where boundary conditions are set based on, for example, user-preferred, user-defined, or user-selected maximum / minimum MU.

[0085] Figure 5 is a functional block diagram illustrating an example of a simplified IMPT optimization workflow according to one or more example embodiments.

[0086] Conventionally, as similarly discussed above, machine beam data and treatment plans are used to generate energy layers and spots within each energy layer for the treatment plan. The spot weights are then optimized, and any spots with a weight (MU) below a global minimum MU (MU between zero and the global minimum MU) are eliminated to generate a deliverable treatment plan.

[0087] like Figure 5 As shown in , according to one or more example embodiments, machine beam data and treatment plans are used to generate energy layers and spots therein (502), and then the spot weights are optimized (506). However, instead of utilizing a global minimum MU, the TPS 150 derives a minimum MU for each energy layer (504), and the minimum MU for each energy layer is used instead of the global minimum MU to eliminate any spots having a weight or MU (MU between zero and the minimum MU) lower than the minimum MU for the corresponding energy layer to obtain a deliverable treatment plan.

[0088] Figure 6 is a flow chart illustrating a method for radiation therapy treatment planning and treatment according to an example embodiment. Figure 6 The method shown in will be discussed as Figure 1 However, example embodiments should not be limited to this example.

[0089] according to Figure 6 method, Figure 1The system shown in (e.g., TPS 150) can generate a radiation therapy treatment plan based on a plurality of minimum monitoring unit values, wherein each of the plurality of minimum monitoring unit values ​​is for a corresponding energy layer among a plurality of energy layers specified by the radiation therapy treatment plan, and wherein each of the plurality of minimum monitoring unit values ​​is based on a machine parameter (or machine limitation) of the radiation therapy machine 1000. The plurality of energy layers can be associated with a plurality of spots in a treatment target.

[0090] More specifically refer to Figure 6 At S604, TPS150 determines a minimum MU for each energy layer specified by a radiation therapy treatment plan based on machine parameters of a radiation therapy machine 1000 that is used to deliver the radiation therapy treatment. In one example, the radiation therapy treatment plan may specify a plurality of energy layers associated with a plurality of spots in a treatment target, and TPS150 may determine a minimum MU for each of the plurality of energy layers based on the machine parameters of the radiation therapy machine 1000. The minimum MU for each respective energy layer may be the same as or different from the minimum MU for the other energy layers; that is, one or more of the minimum MUs for the plurality of energy layers may be different from other minimum MUs for other energy layers in the plurality of energy layers. This will be discussed later. Figure 7 Example embodiments of methods for determining a minimum MU for a respective energy tier are discussed in more detail.

[0091] The TPS 150 may generate a radiation therapy treatment plan, for example, as described above with respect to Figure 3 and 4 Alternatively, the TPS 150 may obtain a previously generated radiation therapy treatment plan stored in, for example, the memory 108 and / or 120 .

[0092] Once the minimum MU value for each energy layer has been determined, at S606, the TPS 150 generates a deliverable radiation therapy treatment plan by performing an optimization based on the minimum MU for each of the plurality of energy layers. Figure 8 Example embodiments of methods for determining a deliverable radiation therapy treatment plan are discussed in further detail.

[0093] Once determined, the radiation therapy treatment plan output by the TPS 150 may be delivered for treating the patient at S608 (eg, via the radiation therapy machine 1000 ). Figure 6 Step S608 in Figure 3 The process is the same as step 308 in , and therefore, the detailed description will not be repeated here.

[0094] Figure 7 is shown for Figure 6Flow chart of an example embodiment of a method for determining a minimum MU for an energy layer at S604 in FIG. Figure 7 The methods shown in will be discussed as being used by Figure 1 The computer system 100 (and more specifically the TPS 150) in FIG. 1 is executed. However, the example embodiments should not be limited to this example. Although not shown, for each of the plurality of energy layers specified by the radiation therapy treatment plan, (e.g., iteratively, serially, or in parallel) Figure 7 However, for the sake of brevity, only a single iteration in which the minimum MU is determined for the e-th energy layer among a plurality of energy layers specified by a radiation therapy treatment plan will be described in detail. In at least this example, the radiation therapy treatment plan may specify N energy layers, and the index e may take values ​​from 1 to N.

[0095] refer to Figure 7 At S704, the TPS 150 calculates the minimum deliverable MU (also referred to as the delivery capability limit) min_del_MU and the MU rate saturation point MU_Rate_Sat_e for the e-th energy layer based on the machine parameters of the radiation therapy machine. The MU rate saturation point may also be referred to as the MU saturation point. The minimum deliverable MU and the MU rate saturation point may be related to (e.g., may be a direct result of) the physical limitations of the delivery machine when performing the radiation therapy treatment. As a result, the minimum deliverable MU and the MU rate saturation point may vary (e.g., slightly) between different machines.

[0096] According to at least one example embodiment, the machine parameters may include one or more of: a MU rate range of the radiation therapy machine, a minimum spot duration of the radiation therapy machine, or a delivery parameter of the radiation therapy machine. The MU rate range may define a minimum and maximum number of protons that can be produced by the delivery machine per second. The MU rate range may be set for each energy layer specified by the radiation therapy treatment plan, depending on the minimum MU of the energy layer. The MU rate range may be expressed in MU per second (MU / s).

[0097] The minimum spot duration is the minimum beam duration (in seconds) that can be emitted by the delivery machine. In practice, the beam duration is limited by the speed with which the hardware can reliably turn the beam off after it has been turned on, and the accuracy with which the system can determine the number of MUs emitted during beam delivery. For example, the system may require several milliseconds for the hardware to turn the beam off after it has been turned on. In another example, the measurement accuracy of the system's emitted monitoring unit may be limited to 0.1 MU, and the MU rate may be 10 MU / s, which would result in the shortest amount of time the beam can be on such that an emitted MU is counted as 10 ms.

[0098] The transmission parameters of the radiation therapy machine include, for example, a coefficient of transmission, which represents the fraction of protons from the accelerator that reach the patient. The transmission parameters depend on the beam energy, and therefore, for lower beam energies, the transmission parameters may be lower. The transmission parameters of the radiation therapy machine may be known a priori.

[0099] The minimum deliverable MU min_del_MU is the minimum amount of radiation that the radiation therapy machine can physically produce at one time. In one example, the minimum deliverable MU min_del_MU is the product of the minimum transmitted MU rate Tx_MU_Rate_min in MU / s and the minimum spot duration t_min_spot in, for example, milliseconds (min_del_MU=Tx_MU_Rate_min*t_min_spot). The minimum transmitted MU rate Tx_MU_Rate_min_e for an energy layer is the product of the transmission coefficient Transmission_e for that energy layer and the minimum MU rate MU_Rate_min of the delivery machine; that is, Tx_MU_Rate_min_e=Transmission_e*MU_Rate_min. The minimum transmitted MU rate Tx_MU_Rate_min of the delivery machine is the minimum transmitted MU rate Tx_MU_Rate_min_e from among the minimum transmitted MU rates for multiple energy layers. The delivery machine cannot deliver spots with MUs lower than the lowest deliverable MU, because doing so would require MU rates and spot durations below the minimum thresholds for these values. Spots with higher MUs can be delivered using the same MU rate by extending the spot duration (how long the beam is on at that spot).

[0100] The MU rate saturation point is the MU value at which the delivery speed at a given energy layer no longer improves. The MU rate saturation point MU_Rate_Sat_e for an energy layer is reached when the minimum MU min_MU_e of the energy layer is equal to the product of the MU rate Tx_MU_Rate_max_e for the maximum transmission of the energy layer and the minimum spot duration (min_MU_e=MU_Rate_Sat_e=Tx_MU_Rate_max_e*t_min_spot). As mentioned above, spots with higher MU can be delivered by increasing the duration of irradiation.

[0101] As an example, if the MU rate range for the e-th energy layer is [100, 6000] MU / s (i.e., a minimum MU rate of 100 MU / s and a maximum MU rate of 6000 MU / s), the minimum spot duration is 2 ms (t_min_spot = 2 ms), and the transmission coefficient for the e-th energy layer is 0.5, then the minimum deliverable MU min_del_MU for the e-th energy layer will be min_del_MU_e = 100 MU / s * 0.002s * 0.5 = 0.1 MU. The MU rate saturation point MU_Rate_Sat_e for the e-th energy layer will be MU_Rate_Sat_e = 6000 MU / s * 0.002s * 0.5 = 6 MU.

[0102] In at least some example embodiments, each energy tier may have a different transmission coefficient and MU rate range, and as a result, a different minimum deliverable MU and MU rate saturation point.

[0103] Still reference Figure 7 Once the minimum deliverable MU and the MU saturation point for the e-th energy layer have been calculated, at S706 , the TPS 150 determines the minimum MU min_MU_e for the e-th energy layer based on the minimum deliverable MU min_del_MU_e and / or the MU rate saturation point MU_Rate_Sat_e.

[0104] In one example, TPS150 sets the minimum MU for the e-th energy layer to the MU rate saturation point for the e-th energy layer (min_MU_e=MU_Rate_Sat_e). As discussed above, during planning, the MU rate saturation point can be calculated / calculated by TPS150. In another example, TPS150 can set the minimum MU for the energy layer to the MU rate saturation point, where the MU rate saturation point is obtained from a saturation curve of the delivery machine or selected from a lookup table. In the case of a saturation curve and / or a lookup table, the saturation curve and / or the stored value can be determined, for example, in advance (e.g., before optimization) or during optimization.

[0105] In yet another example, the TPS 150 may select a value between the minimum deliverable MU min_del_MU_e and the MU rate saturation point MU_Rate_Sat_e as the minimum MU (min_del_MU_e) for the e-th energy layer. <min_MU_e<MU_Rate_Sat_e)。

[0106] In this case, the minimum MU may be selected by considering the dose distribution, plan quality, etc. For example, if the minimum deliverable MU is considered to be "0%" and the MU rate saturation point is considered to be "100%", setting the minimum MU for the energy layer to the MU rate saturation point may provide "100%" or the maximum delivery rate without exceeding the saturation limit. However, in some cases, a radiation treatment plan utilizing the maximum delivery rate (100%) does not provide an acceptable dose distribution, and as a result, some delivery rate must be traded off to improve plan quality. In this case, depending on the dose distribution and / or other factors that affect plan quality, the TPS 150 may select a minimum MU that is, for example, 75% or other percentage of the MU rate saturation value.

[0107] Fig.10 is a graph showing an example saturation curve and minimum deliverable MU for a delivery machine according to an example embodiment. Fig.10 In FIG. 1 , the y-axis represents the minimum MU and the x-axis represents the slice energy in MeV. As shown, the limiting factor for the minimum MU of a treatment plan is the minimum deliverable MU 1020 ( Fig.10 0.5) and the saturation point of the MU rate for a given energy layer on curve 1060. By setting the minimum MU for an energy layer to a value on the saturation curve, the delivery rate for a given energy layer (or radiation treatment) can be increased and / or maximized, and as a result, the treatment time can be reduced and / or minimized.

[0108] Figure 8 is shown for Figure 6 Flowchart of an example embodiment of a method of generating a deliverable radiation plan at S606 in FIG. Figure 8 The methods shown in will be discussed as being used by Figure 1 The computer system 100 (and more specifically the TPS 150) in FIG. 1 is executed. However, example embodiments should not be limited to this example.

[0109] refer to Figure 8 At S804, TPS150 executes the above Figure 4The optimization process discussed to obtain a radiation treatment plan. In one example, the optimization process at S804 can be performed in any known manner. In another example, TPS150 can consider the minimum MU for each energy during optimization. In this example, the optimization process can be similar to those known in the art, but instead of considering a single global minimum MU as in conventional techniques (e.g., using constraints in the optimization, such as described by Wenhua Cao et al. in “Incorporating deliverable monitor unit constraints into spot intensity optimization in intensity-modulated protontherapy treatment planning” (2013 Phys. Med. Biol. 58 5113) (the entire contents of which are incorporated herein by reference), or additional terms in the objective function), the optimization process can consider separate minimum MU values ​​for each energy layer. In one example, the separate minimum MU value for each energy layer can be as described herein with respect to Figure 7 to be obtained and / or determined as discussed.

[0110] Since the optimization process considering a single global minimum MU is generally known, further detailed discussion is omitted.

[0111] At S806, for each energy layer, the TPS 150 removes and / or eliminates all spots having MU lower than the minimum MU for the energy layer to obtain a deliverable radiation therapy treatment plan. That is, for example, for each energy layer e among the specified N energy layers from the radiation treatment plan, the TPS 150 removes all spots having MU lower than the minimum MU min_MU_e for the energy layer e.

[0112] In at least one other example embodiment, the TPS 150 may be based on a minimum MU objective function F derived from the above-mentioned machine parameters (machine constraints). MU To determine the minimum MU of each energy layer, the minimum MU objective function F MU The optimization results may be directed toward a higher minimum MU for each energy layer. For example, TPS 150 may (eg, during or prior to optimization) set the minimum MU objective function F MU The piecewise linear per-energy-layer and per-blob cost functions F are determined as shown below: MU The sum of (e,j).

[0113] When MU(j) reaches its delivery capacity limit (e), FMU(e,j)=0,

[0114] When MU(j)≤saturation limit(e),

[0115] When MU(j)>saturation limit (e), FFMu(e,j)=1

[0116] In the above example, MU(j) is the MU of the jth spot in energy layer e, and the delivery capability limit (minimum deliverable MU) and saturation limit (MU rate saturation point) are calculated for each energy layer according to the machine parameters, for example, as described above for Figure 7 From the minimum MU objective function F shown above MU It can be seen that the minimum MU objective function F MU It reaches its maximum value at the MU rate saturation limit.

[0117] As illustrated below in equation (1), for example, if the cost of the dosimetry objective of a radiation therapy treatment plan is given by the objective function F D Defined, then the total cost function F for the optimization of radiation therapy treatment planning is Tot Based on the objective function F D , minimum MU objective function F MU And the balance objective function F D and the minimum MU objective function F MU In one example, the function F D It may be similar or identical to the dose objective function f(d) discussed above.

[0118] F Tot = F D -w*F MU (1)

[0119] By minimizing the MU objective function F MU Maximizing can reduce the total cost function F Tot and / or let the total cost function F Tot minimize.

[0120] By aiming to make the total cost function F Tot Minimization, the weighting factor w controls the trade-off between the dosimetry objective and the minimum MU objective, where w = 0 produces only the (given by the function F D The optimal result for the dosimetry objective is defined as w>>1, and w>>1 produces a result that essentially ignores the dosimetry objective function F D By changing the weighting factor w, the TPS 150 can obtain an appropriate (or optimal) balance between the minimum Mu per energy layer and the dosimetric quality of the radiation treatment plan.

[0121] Fig. 9 is a flow chart illustrating a method for radiation therapy treatment planning and treatment utilizing a minimum MU objective function according to an example embodiment. Figures 6 to 8 Same, Fig. 9 The method shown in will be discussed as Figure 1 However, example embodiments should not be limited to this example.

[0122] according to Fig. 9 The TPS 150 can generate a radiation therapy treatment plan indicating multiple energy layers associated with multiple spots in a treatment target, the radiation therapy treatment plan having multiple minimum MUs (minimum monitoring unit values), wherein the multiple minimum MUs are generated based on a minimum MU objective function of the radiation therapy machine 1000.

[0123] More specifically refer to Fig. 9 At S904, the TPS 150 derives the minimum MU objective function F based on the machine parameters (or constraints) of the radiation therapy machine 1000. MU , the radiation therapy machine 1000 is used to deliver radiation therapy treatment. In one example, the TPS 150 may minimize the MU objective function F MU The layer-by-layer and spot-by-spot cost functions F are derived as discussed above. MU The sum of (e,j).

[0124] At S906, the TPS 150 determines the dose based on at least the dose measurement objective function F D , minimum MU objective function F MU and the balanced dosimetry objective function F D and the minimum MU objective function F MU The optimization is performed with a weighting factor w of t to generate a deliverable radiation therapy treatment plan, as discussed earlier.

[0125] Once determined, a deliverable radiation therapy treatment plan is output by the TPS 150 for treating the patient at S908 (eg, via the radiation therapy machine 1000 ). Fig. 9 Step S908 in Figure 3 Step 308 and Figure 6 The process is the same as step S608 in , and therefore, the detailed description will not be repeated here.

[0126] By utilizing a per-energy-slice minimum MU based on machine limitations of a radiation therapy machine in accordance with one or more example embodiments, field delivery time may be significantly improved (eg, about 5 seconds or more in actual scan time per field) with little impact on dose quality.

[0127] The following is a list of non-limiting illustrative embodiments disclosed herein.

[0128] Illustrative embodiments 1. A system for planning a radiation therapy treatment, the radiation therapy treatment to be performed by a radiation therapy machine, the system comprising: a memory storing computer-executable instructions; and at least one processor configured to execute the computer-executable instructions so that the system generates a radiation therapy treatment plan, the radiation therapy treatment plan indicating a plurality of energy layers associated with a plurality of spots in a treatment target, the radiation therapy treatment plan being based on a plurality of minimum monitoring unit values, each of the plurality of minimum monitoring unit values ​​being for a corresponding energy layer among the plurality of energy layers, and each of the plurality of minimum monitoring unit values ​​being based on a machine parameter of the radiation therapy machine.

[0129] Illustrative embodiment 2. The system of illustrative embodiment 1, wherein the machine parameters include at least one of: a monitoring unit rate range of the radiation therapy machine, a minimum spot duration of the radiation therapy machine, or a transmission parameter of the radiation therapy machine.

[0130] Illustrative embodiment 3. A system according to any one of the aforementioned illustrative embodiments, wherein the at least one processor is configured to execute the computer-executable instructions so that the system: calculates a minimum deliverable monitoring unit value for a first energy layer among the multiple energy layers based on the machine parameters of the radiation therapy machine, calculates a monitoring unit rate saturation point for the first energy layer based on the machine parameters of the radiation therapy machine, and determines a minimum monitoring unit value for the first energy layer based on the minimum deliverable monitoring unit value for the first energy layer and the monitoring unit rate saturation point.

[0131] Illustrative embodiment 4. A system according to any one of the preceding illustrative embodiments, wherein the at least one processor is configured to execute the computer-executable instructions so that the system: determines the multiple minimum monitoring unit values ​​based on a minimum monitoring unit saturation curve of the radiation therapy machine, wherein the minimum monitoring unit saturation curve is derived based on the machine parameters of the radiation therapy machine.

[0132] Illustrative embodiment 5. The system of any of the preceding illustrative embodiments, wherein the minimum monitoring unit saturation curve indicates a minimum deliverable monitoring unit value and a monitoring unit rate saturation point for each energy tier of the plurality of energy tiers.

[0133] Illustrative embodiment 6. The system of any of the preceding illustrative embodiments, wherein the minimum deliverable monitoring unit value and the monitoring unit rate saturation point for each of the plurality of energy layers are based on the machine parameters of the radiation therapy machine.

[0134] Illustrative embodiment 7. A radiation therapy treatment system comprising: a system for planning a radiation therapy treatment according to any of the preceding illustrative embodiments; and the radiation therapy machine configured to provide radiation therapy treatment according to the radiation therapy treatment plan.

[0135] Illustrative embodiment 8. A system for planning a radiation therapy treatment, the radiation therapy treatment to be performed by a radiation therapy machine, the system comprising: a memory storing computer-executable instructions; and at least one processor configured to execute the computer-executable instructions so that the system generates a radiation therapy treatment plan, the radiation therapy treatment plan indicating a plurality of energy layers associated with a plurality of spots in a treatment target, the radiation therapy treatment plan having a plurality of minimum monitoring unit values, the plurality of minimum monitoring unit values ​​being generated based on a minimum monitoring unit objective function of the radiation therapy machine.

[0136] Illustrative embodiment 9. The system according to illustrative embodiment 8, wherein the at least one processor is configured to execute the computer executable instructions so that the system: derives the minimum monitoring unit objective function based on machine parameters of the radiation therapy machine.

[0137] Illustrative embodiment 10. A system according to any one of illustrative embodiments 8 to 9, wherein the machine parameters include at least one of the following: a monitoring unit rate range of the radiation therapy machine, a minimum spot duration of the radiation therapy machine, or a transmission parameter of the radiation therapy machine.

[0138] Illustrative embodiment 11. The system of any one of illustrative embodiments 8 to 10, wherein each minimum monitoring unit value of the plurality of minimum monitoring unit values ​​is associated with a corresponding energy stratum among the plurality of energy strata.

[0139] Illustrative embodiment 12. A system according to any one of illustrative embodiments 8 to 11, wherein the at least one processor is configured to execute the computer-executable instructions so that the system: generates the radiation therapy treatment plan based on at least the minimum monitoring unit objective function, the dose measurement objective function and the weight factor.

[0140] Illustrative embodiment 13. The system of any one of illustrative embodiments 8 to 12, wherein the minimum monitoring unit objective function is a sum of piecewise linear energy layer-by-energy and spot cost functions.

[0141] Illustrative embodiment 14. A radiation therapy treatment system comprising: a system for planning a radiation therapy treatment according to any one of illustrative embodiments 8 to 13; and the radiation therapy machine configured to provide radiation therapy treatment according to the radiation therapy treatment plan.

[0142] Illustrative embodiment 15. A system for planning a radiation therapy treatment, the radiation therapy treatment to be performed by a radiation therapy machine, the system comprising: a memory storing computer-executable instructions; and at least one processor configured to execute the computer-executable instructions so that the system generates a radiation therapy treatment plan for a treatment target, the radiation therapy treatment plan being generated based on a minimum monitoring unit value for each of a plurality of energy layers specified by the radiation therapy treatment plan, each minimum monitoring unit value being based on a machine parameter of the radiation therapy machine.

[0143] Illustrative embodiment 16. A system according to illustrative embodiment 15, wherein the at least one processor is configured to execute the computer-executable instructions so that the system: generates the radiation therapy treatment plan by performing optimization based on the minimum monitoring unit value for each of the multiple energy layers.

[0144] Illustrative embodiment 17. A system according to any one of illustrative embodiments 15 to 16, wherein the machine parameters include at least one of the following: a monitoring unit rate range of the radiation therapy machine, a minimum spot duration of the radiation therapy machine, or a transmission parameter of the radiation therapy machine.

[0145] Illustrative embodiment 18. A system according to any one of illustrative embodiments 15 to 17, wherein the at least one processor is configured to execute the computer-executable instructions so that the system: calculates a minimum deliverable monitoring unit value for a first energy layer among the multiple energy layers based on the machine parameters of the radiation therapy machine, calculates a monitoring unit rate saturation point for the first energy layer based on the machine parameters of the radiation therapy machine, and determines a minimum monitoring unit value for the first energy layer based on the minimum deliverable monitoring unit value for the first energy layer and the monitoring unit rate saturation point.

[0146] Illustrative embodiment 19. A system according to any one of illustrative embodiments 15 to 18, wherein the at least one processor is configured to execute the computer-executable instructions so that the system: determines the minimum monitoring unit value for each of the multiple energy layers based on a minimum monitoring unit saturation curve of the radiation therapy machine, and the minimum monitoring unit saturation curve is derived based on the machine parameters of the radiation therapy machine.

[0147] Illustrative embodiment 20. A system for radiation therapy treatment, the system comprising: a system for planning radiation therapy treatment according to any one of illustrative embodiments 15 to 19; and the radiation therapy machine configured to apply radiation therapy treatment according to the radiation therapy treatment plan.

[0148] Although the terms first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another element. For example, a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element without departing from the scope of this disclosure. As used herein, the term "and / or" includes any and all combinations of one or more items in the associated listed items.

[0149] When an element is referred to as being "connected" or "coupled" to another element, it may be directly connected or coupled to the other element or there may be intervening elements. In contrast, when an element is referred to as being "directly connected" or "directly coupled" to another element, there are no intervening elements. Other words used to describe the relationship between elements should be interpreted in a similar manner (e.g., "between" versus "directly between," "adjacent" versus "directly adjacent," etc.).

[0150] The terms used herein are only used for the purpose of describing specific embodiments and are not intended to be limiting. As used herein, the singular forms "a", "an", and "the" are also intended to include the plural forms unless the context clearly indicates otherwise. It will also be understood that the terms "comprises", "comprising", "containing", and / or "having" when used herein specify the presence of stated features, wholes, steps, operations, elements, and / or parts, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, parts, and / or groups thereof.

[0151] It should also be noted that in some alternative implementations, the functions / actions noted may not occur in the order noted in the figures. For example, depending on the functions / actions involved, two figures shown in succession may actually be performed substantially simultaneously, or may sometimes be performed in reverse order.

[0152] Specific details are provided in the following description to provide a thorough understanding of the example embodiments. However, one of ordinary skill in the art will appreciate that the example embodiments may be practiced without these specific details. For example, the system may be shown in a block diagram so as not to obscure the example embodiments with unnecessary detail. In other instances, well-known processes, structures, and techniques may be shown without unnecessary detail in order to avoid obscuring the example embodiments.

[0153] As discussed herein, the illustrative embodiments will be described with reference to symbolic representations of acts and operations (e.g., in the form of flowcharts, flow diagrams, data flow diagrams, structure diagrams, block diagrams, etc.) that may be implemented as program modules or functional processes, including routines, programs, objects, components, data structures, etc., that perform particular tasks or implement particular abstract data types, and may be implemented using existing hardware, such as processing or control circuitry, such as, but not limited to, one or more processors, one or more central processing units (CPUs), one or more controllers, one or more arithmetic logic units (ALUs), one or more digital signal processors (DSPs), one or more microcomputers, one or more field programmable gate arrays (FPGAs), one or more systems on chips (SOCs), one or more programmable logic units (PLUs), one or more microprocessors, one or more application specific integrated circuits (ASICs), or any other device or devices capable of responding to and executing instructions in a defined manner.

[0154] Although a flowchart may describe operations as a sequential process, many of the operations may be performed in parallel, concurrently, or simultaneously. In addition, the order of the operations may be rearranged. A process may terminate when its operations are completed, but may also have additional steps not included in the diagram. A process may correspond to a method, function, flow, subroutine, subprogram, etc. When a process corresponds to a function, its termination may correspond to the function returning to the calling function or the main function.

[0155] As disclosed herein, the terms "memory", "storage medium", "processor-readable medium", "computer-readable storage medium" or "non-transitory computer-readable storage medium" may refer to one or more devices for storing data, including read-only memory (ROM), random access memory (RAM), magnetic RAM, core memory, magnetic disk storage media, optical storage media, flash memory devices and / or other tangible machine-readable media for storing information. The term "computer-readable medium" may include, but is not limited to, portable or fixed storage devices, optical storage devices, and various other media capable of storing, containing or carrying (one or more) instructions and / or data.

[0156] In addition, the example embodiments may be implemented by hardware, software, firmware, middleware, microcode, hardware description language or any combination thereof. When implemented in software, firmware, middleware or microcode, the program code or code segment for performing the necessary tasks may be stored in a machine such as a computer-readable storage medium or a computer-readable medium. When implemented in software, one or more processors will perform the necessary tasks. For example, as mentioned above, according to one or more example embodiments, at least one memory may include or store a computer program code, and at least one memory and the computer program code may be configured to enable a network element or network device to perform the necessary tasks together with at least one processor. In addition, the processor, memory and example algorithm encoded as a computer program code are used as components for providing or causing the execution of the operations discussed herein.

[0157] As used herein, the terms "comprising" and / or "having" are defined as including (i.e., open language). As used herein, the term "coupled" is defined as connected, but not necessarily directly and not necessarily mechanically. Terms derived from the word "indicating" (e.g., "indicates" and "indication") are intended to cover all the various techniques that can be used to convey or reference the object / information being indicated. Some but not all examples of techniques that can be used to transmit or reference the object / information being indicated include transmission of the object / information being indicated, transmission of an identifier of the object / information being indicated, transmission of information used to generate the object / information being indicated, transmission of some parts or portions of the object / information being indicated, transmission of some derivative of the object / information being indicated, and transmission of some symbol representing the object / information being indicated.

[0158] According to example embodiments, the medical system may be (or include) hardware, firmware, hardware executing software, or any combination thereof. Such hardware may include processing or control circuitry such as, but not limited to, one or more processors, one or more CPUs, one or more controllers, one or more ALUs, one or more DSPs, one or more microcomputers, one or more FPGAs, one or more SoCs, one or more PLUs, one or more microprocessors, one or more ASICs, or any other device or devices capable of responding to and executing instructions in a defined manner.

[0159] The benefits, other advantages and solutions to problems have been described above with reference to specific embodiments. However, the benefits, advantages, solutions to problems and any (one or more) elements that may cause or lead to such benefits, advantages or solutions or make such benefits, advantages or solutions more significant should not be interpreted as key, essential or basic features or elements of any or all claims.

Claims

1. A system for planning a radiation therapy treatment to be performed by a radiation therapy machine, the system comprising: a memory storing computer executable instructions; as well as at least one processor configured to execute the computer-executable instructions so that the system generates a radiation therapy treatment plan, the radiation therapy treatment plan indicating a plurality of energy layers associated with a plurality of spots in a treatment target, the radiation therapy treatment plan being based on a plurality of minimum monitoring unit values, each of the plurality of minimum monitoring unit values ​​being for a corresponding energy layer among the plurality of energy layers, and each of the plurality of minimum monitoring unit values ​​being based on a machine parameter of the radiation therapy machine.

2. The system of claim 1, wherein the machine parameters include at least one of: a monitoring unit rate range of the radiation therapy machine, a minimum spot duration of the radiation therapy machine, or a transmission parameter of the radiation therapy machine.

3. The system of claim 1 , wherein the at least one processor is configured to execute the computer executable instructions so that the system: calculating a minimum deliverable monitoring unit value for a first energy layer among the plurality of energy layers based on the machine parameters of the radiation therapy machine, calculating a monitoring unit rate saturation point for the first energy layer based on the machine parameters of the radiation therapy machine, and Based on the minimum deliverable monitoring unit value and the monitoring unit rate saturation point for the first energy tier, a minimum monitoring unit value for the first energy tier is determined.

4. The system of claim 1 , wherein the at least one processor is configured to execute the computer executable instructions so that the system: determines the plurality of minimum monitoring unit values ​​based on a minimum monitoring unit saturation curve of the radiation therapy machine, the minimum monitoring unit saturation curve being derived based on the machine parameters of the radiation therapy machine. 5 . The system of claim 4 , wherein the minimum monitoring unit saturation curve indicates a minimum deliverable monitoring unit value and a monitoring unit rate saturation point for each of the plurality of energy tiers.

6. The system of claim 5, wherein the minimum deliverable monitoring unit value and the monitoring unit rate saturation point for each of the plurality of energy layers are based on the machine parameters of the radiation therapy machine.

7. A radiation therapy treatment system comprising: The system for planning radiation therapy treatment according to claim 1; as well as The radiation therapy machine is configured to provide radiation therapy treatment according to the radiation therapy treatment plan.

8. A system for planning a radiation therapy treatment to be performed by a radiation therapy machine, the system comprising: a memory storing computer executable instructions; as well as and at least one processor configured to execute the computer-executable instructions to cause the system to generate a radiation therapy treatment plan, the radiation therapy treatment plan specifying a plurality of energy layers associated with a plurality of spots in a treatment target, the radiation therapy treatment plan having a plurality of minimum monitoring unit values ​​generated based on a minimum monitoring unit objective function of the radiation therapy machine.

9. The system of claim 8, wherein the at least one processor is configured to execute the computer executable instructions such that the system: derives the minimum monitoring unit objective function based on machine parameters of the radiation therapy machine.

10. The system of claim 9, wherein the machine parameters include at least one of: a monitoring unit rate range of the radiation therapy machine, a minimum spot duration of the radiation therapy machine, or a transmission parameter of the radiation therapy machine. 11 . The system of claim 8 , wherein each minimum monitoring unit value of the plurality of minimum monitoring unit values ​​is associated with a corresponding energy tier among the plurality of energy tiers.

12. The system of claim 8, wherein the at least one processor is configured to execute the computer executable instructions so that the system generates the radiation therapy treatment plan based on at least the minimum monitoring unit objective function, the dosimetry objective function, and a weighting factor.

13. The system of claim 8, wherein the minimum monitoring unit objective function is a sum of piecewise linear energy layer-by-energy and spot cost functions.

14. A radiation therapy treatment system comprising: The system for planning radiation therapy treatment according to claim 8; as well as The radiation therapy machine is configured to provide radiation therapy treatment according to the radiation therapy treatment plan.

15. A system for planning a radiation therapy treatment to be performed by a radiation therapy machine, the system comprising: a memory storing computer executable instructions; as well as at least one processor configured to execute the computer-executable instructions to cause the system to generate a radiation therapy treatment plan for a treatment target, the radiation therapy treatment plan being generated based on a minimum monitoring unit value for each of a plurality of energy layers specified by the radiation therapy treatment plan, each minimum monitoring unit value being based on a machine parameter of the radiation therapy machine.

16. The system of claim 15, wherein the at least one processor is configured to execute the computer executable instructions such that the system generates the radiation therapy treatment plan by performing optimization based on the minimum monitoring unit value for each of the plurality of energy layers.

17. The system of claim 15, wherein the machine parameters include at least one of: a monitoring unit rate range of the radiation therapy machine, a minimum spot duration of the radiation therapy machine, or a transmission parameter of the radiation therapy machine.

18. The system of claim 15, wherein the at least one processor is configured to execute the computer executable instructions so that the system: calculating a minimum deliverable monitoring unit value for a first energy layer among the plurality of energy layers based on the machine parameters of the radiation therapy machine, calculating a monitoring unit rate saturation point for the first energy layer based on the machine parameters of the radiation therapy machine, and Based on the minimum deliverable monitoring unit value and the monitoring unit rate saturation point for the first energy tier, a minimum monitoring unit value for the first energy tier is determined.

19. The system of claim 15, wherein the at least one processor is configured to execute the computer executable instructions so that the system: determines the minimum monitoring unit value for each of the plurality of energy layers based on a minimum monitoring unit saturation curve of the radiation therapy machine, the minimum monitoring unit saturation curve being derived based on the machine parameters of the radiation therapy machine.

20. A system for radiation therapy treatment, the system comprising: The system for planning radiation therapy treatment according to claim 15; as well as The radiation therapy machine is configured to apply radiation therapy treatment according to the radiation therapy treatment plan.

Images