Radiation therapy treatment plan and radiation therapy treatment including MU distribution visualization

Abstract

Embodiments of the present disclosure relate to radiation therapy treatment plans and radiation therapy treatments including MU distribution visualization. A system includes at least one processor configured to execute computer executable instructions to cause the system to: generate or obtain a first radiation therapy plan for a therapy target in a patient, the first radiation therapy plan specifying beam characteristics of a plurality of beamlets or spots in the therapy target, the beam characteristic comprises a monitoring unit value associated with each of a plurality of beamlets or spots in at least the first field; and displaying, via a graphical user interface, at least one representation of a first distribution of monitoring units for the first radiotherapy plan, the at least one representation of the first distribution of monitoring units indicating, for each respective monitoring unit value, a number of beamlets or spots in at least the first field having the respective monitoring unit value.

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 high-energy proton, photon, ion, or electron radiation beams to a target volume in the treatment target of unhealthy tissue, such as a tumor or lesion.

[0003] Before radiation therapy is performed on a patient, a treatment plan is developed for that patient. The treatment plan defines various aspects of the radiation therapy using simulations and optimizations that may be based on past experience. In general, 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 independent claims define the scope of protection sought for the various example embodiments. 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 comprising: 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 or obtains a first radiation therapy plan for a treatment target in a patient, the first radiation therapy plan specifying beam characteristics of a plurality of beamlets or spots in the treatment target, the beam characteristics including a monitoring unit value associated with each of the plurality of beamlets or spots in at least a first field; and displays at least one representation of a first distribution of monitoring units for the first radiation therapy plan via a graphical user interface, the at least one representation of the first distribution of monitoring units indicating, for each corresponding monitoring unit value, the number of beamlets or spots in at least the first field having the corresponding monitoring unit value.

[0006] At least one other example embodiment provides a system comprising: a device for generating a first radiation therapy plan for a treatment target in a patient and / or a device for obtaining a first radiation therapy plan for a treatment target in a patient, the first radiation therapy plan specifying beam characteristics of a plurality of beamlets or spots in the treatment target, the beam characteristics comprising a monitoring unit value associated with each of the plurality of beamlets or spots in at least a first field; and a device for displaying at least one representation of a first distribution of monitoring units for the first radiation therapy plan via a graphical user interface, the at least one representation of the first distribution of monitoring units indicating, for each corresponding monitoring unit value, the number of beamlets or spots in at least the first field having the corresponding monitoring unit value.

[0007] At least one other example embodiment provides a method comprising: generating or obtaining a first radiation therapy plan for a treatment target in a patient, the first radiation therapy plan specifying beam characteristics of a plurality of beamlets or spots in the treatment target, the beam characteristics comprising a monitoring unit value associated with each of the plurality of beamlets or spots in at least a first field; and displaying at least one representation of a first distribution of monitoring units for the first radiation therapy plan via a graphical user interface, the at least one representation of the first distribution of monitoring units indicating, for each corresponding monitoring unit value, the number of beamlets or spots in at least the first field having the corresponding monitoring unit value.

[0008] At least one other exemplary embodiment provides a non-transitory computer-readable storage medium storing computer-executable instructions that, when executed by at least one processor at a system, cause the system to perform a method comprising: generating or obtaining a first radiation therapy plan for a treatment target in a patient, the first radiation therapy plan specifying beam characteristics of a plurality of beamlets or spots in the treatment target, the beam characteristics comprising a monitoring unit value associated with each of the plurality of beamlets or spots in at least a first field; and displaying at least one representation of a first distribution of monitoring units for the first radiation therapy plan via a graphical user interface, the at least one representation of the first distribution of monitoring units indicating, for each corresponding monitoring unit value, the number of beamlets or spots in at least the first field having the corresponding monitoring unit value.

[0009] At least one example embodiment provides a system comprising at least one processor and a memory storing computer executable instructions. At least one processor is configured to execute computer-executable instructions to cause the system to: generate a first candidate radiation therapy plan for a treatment target in a patient, the first candidate radiation therapy plan specifying beam characteristics of a plurality of beamlets or spots in the treatment target, the beam characteristics including a first monitoring unit value associated with each of the plurality of beamlets or spots; generate a second candidate radiation therapy plan for the treatment target in the patient, the second candidate radiation therapy plan specifying second beam characteristics of the plurality of beamlets or spots in the treatment target, the second beam characteristics including a second monitoring unit value associated with each of the plurality of beamlets or spots; display via a graphical user interface at least one representation of a first distribution of monitoring units for the first candidate radiation therapy plan, the at least one representation of the first distribution of monitoring units indicating, for each respective first monitoring value, a first number of beamlets or spots having a respective first monitoring unit value; and display via the graphical user interface at least one representation of a second distribution of monitoring units for the second candidate radiation therapy plan, the at least one representation of the second distribution of monitoring units indicating, for each respective second monitoring value, a second number of beamlets or spots having a respective second monitoring unit value.

[0010] At least one example embodiment provides a system comprising: means for generating (or obtaining) a first candidate radiation therapy plan for a treatment target in a patient, the first candidate radiation therapy plan specifying first beam characteristics of a plurality of beamlets or spots in the treatment target, the first beam characteristics comprising first monitoring unit values ​​associated with each of the plurality of beamlets or spots; means for generating (or obtaining) a second candidate radiation therapy plan for the treatment target in the patient, the second candidate radiation therapy plan specifying second beam characteristics of the plurality of beamlets or spots in the treatment target, the second beam characteristics comprising first monitoring unit values ​​associated with each of the plurality of beamlets or spots; means for displaying, via a graphical user interface, at least one representation of a first distribution of monitoring units for a first candidate radiotherapy plan, the at least one representation of the first distribution of monitoring units indicating, for each corresponding first monitoring value, a first number of beamlets or spots having a corresponding first monitoring unit value; and means for displaying, via a graphical user interface, at least one representation of a second distribution of monitoring units for a second candidate radiotherapy plan, the at least one representation of the second distribution of monitoring units indicating, for each corresponding second monitoring value, a second number of beamlets or spots having a corresponding second monitoring unit value.

[0011] At least one example embodiment provides a method comprising: generating (or obtaining) a first candidate radiation therapy plan for a treatment target in a patient, the first candidate radiation therapy plan specifying first beam characteristics of a plurality of beamlets or spots in the treatment target, the first beam characteristics including a first monitoring unit value associated with each of the plurality of beamlets or spots; generating (or obtaining) a second candidate radiation therapy plan for the treatment target in the patient, the second candidate radiation therapy plan specifying second beam characteristics of the plurality of beamlets or spots in the treatment target, the second beam characteristics including a second monitoring unit value associated with each of the plurality of beamlets or spots; displaying, via a graphical user interface, at least one representation of a first distribution of monitoring units for the first candidate radiation therapy plan, the at least one representation of the first distribution of monitoring units indicating, for each respective first monitoring value, a first number of beamlets or spots having a respective first monitoring unit value; and displaying, via a graphical user interface, at least one representation of a second distribution of monitoring units for the second candidate radiation therapy plan, the at least one representation of the second distribution of monitoring units indicating, for each respective second monitoring value, a second number of beamlets or spots having a respective second monitoring unit value.

[0012] At least one other example embodiment provides a non-transitory computer-readable storage medium storing computer-executable instructions that, when executed by at least one processor at a system, cause the system to perform a method, the method comprising: generating (or obtaining) a first candidate radiation therapy plan for a treatment target in a patient, the first candidate radiation therapy plan specifying first beam characteristics of a plurality of beamlets or spots in the treatment target, the first beam characteristics comprising a first monitoring unit value associated with each of the plurality of beamlets or spots; generating (or obtaining) a second candidate radiation therapy plan for the treatment target in the patient, the second candidate radiation therapy plan specifying first beam characteristics of the plurality of beamlets or spots in the treatment target; a second beam characteristic comprising a second monitoring unit value associated with each of a plurality of beamlets or spots; displaying, via a graphical user interface, at least one representation of a first distribution of monitoring units for a first candidate radiotherapy treatment plan, the at least one representation of the first distribution of monitoring units indicating, for each respective first monitoring value, a first number of beamlets or spots having a respective first monitoring unit value; and displaying, via a graphical user interface, at least one representation of a second distribution of monitoring units for a second candidate radiotherapy treatment plan, the at least one representation of the second distribution of monitoring units indicating, for each respective second monitoring value, a second number of beamlets or spots having a respective second monitoring unit value. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Example embodiments will become more fully understood from the detailed description and accompanying drawings given hereinafter, wherein like elements are denoted by like reference numerals, which are given by way of illustration only and thus do not limit the present disclosure.

[0014] Figure 1 is a block diagram of an example of a system upon which an example embodiment may be implemented.

[0015] Figure 2A and Figure 2B An example of a beam view of a treatment target is shown according to an example embodiment.

[0016] 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.

[0017] Figure 5 is a flow chart illustrating a method according to an example embodiment.

[0018] Figure 6 is a flow chart illustrating another method according to an example embodiment.

[0019] Figure 7 is a flow chart illustrating yet another method according to an example embodiment.

[0020] Figure 8 is a flow chart illustrating yet another method according to an example embodiment.

[0021] Fig.9A , Fig. 9B , Fig. 9C and Fig.9D An example graphical user interface (GUI) rendering of a representation of monitoring unit (MU) distribution for radiation therapy treatment planning is shown in accordance with an example embodiment.

[0022] Fig.10 An example GUI rendering of a representation of MU distribution for radiation therapy treatment planning is shown in accordance with an example embodiment.

[0023] Fig.11 Another example GUI rendering of a representation of MU distribution for radiation therapy treatment planning is shown in accordance with an example embodiment.

[0024] Fig.12 An example GUI rendering of a representation of MU distribution for radiation therapy treatment planning is shown in accordance with an example embodiment.

[0025] Fig.13 An example GUI rendering of a representation of a MU distribution including a minimum MU target for radiation therapy treatment planning is shown in accordance with an example embodiment.

[0026] Fig.14 An example GUI rendering of a representation of MU distribution for radiation therapy treatment planning is shown in accordance with an example embodiment.

[0027] Fig.15 An example GUI rendering of a representation of MU distributions for two candidate radiation therapy treatment plans is shown in accordance with an example embodiment.

[0028] It should be noted that these figures are intended to illustrate the general characteristics of methods, structures, and / or materials used in certain example embodiments and to supplement the written description provided below. However, these drawings are not drawn to scale and may not accurately reflect the precise structural or performance characteristics of any given embodiment, nor should they 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

[0029] Various example embodiments will now be described more fully with reference to the accompanying drawings, in which some example embodiments are shown.

[0030] 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.

[0031] 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, equivalent forms and alternatives that fall within the scope of the present disclosure. Throughout the description of the drawings, like numbers refer to like elements.

[0032] As discussed herein, the terms "one or more" and "at least one" can be used interchangeably.

[0033] As discussed herein, a radiation therapy treatment plan may also be referred to as a radiation therapy plan, a treatment plan, or a plan. Furthermore, in the context of radiation therapy treatment plans, the terms "proposed" and "candidate" may be used interchangeably.

[0034] It should be understood that various example embodiments may be used in combination.

[0035] Unless clearly indicated from the following discussion, it should be understood that throughout this disclosure, discussions utilizing terms such as "access," "determine," "store," "allocate," "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 represented as physical (electronic) quantities within a computer system memory, registers, or other such information storage, transmission, or display device.

[0036] The discussion that follows may include terms such as "weight," "metric," "intensity," "monitoring unit," and the like. Unless otherwise noted, a value is associated with each such term. For example, a weight (e.g., a weight of a spot or beamlet) has a value, and an indicator has a value. For simplicity, the term "weight" or "metric" or "intensity" or "monitoring unit" may refer to the value of the weight or indicator or intensity or MU itself, unless otherwise noted or apparent from the discussion.

[0037] As discussed herein, a "representation" may refer to a graphical or visual representation, such as a histogram, a density map, and / or a color density map. Although example embodiments may be discussed herein with respect to a histogram or a density map, example embodiments should not be limited to these example representations.

[0038] Figure 1 A block diagram of an example of a system upon which one or more example embodiments may be implemented is shown. The system includes a computer system 100 and a radiation therapy machine 1000 in bidirectional communication with each other.

[0039] 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 are discussed in more detail below.

[0040] Computer system 100 includes at least one processing unit 102, memory 104, removable storage 108, non-removable storage 120, and communication connections 122 that enable the system to communicate with other devices (e.g., in a networked environment using logical connections to one or more remote computers).

[0041] The system 100 further 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. As will be discussed more later, according to one or more example embodiments, the output device 126 can include a display device configured to display a graphical user interface (GUI) rendering of one or more representations of one or more distributions of MUs (also referred to as MU distributions) for one or more radiation therapy treatment plans.

[0042] exist Figure 1 In the embodiment of the present invention, 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 instead reside in any of the computer storage media used by the system 100, or may be distributed on a combination of computer storage media, or may be distributed on a combination of networked computers. The TPS 150 is configured to generate, optimize and evaluate candidate (suggested) treatment plans and produce a final (optimized) treatment plan. The final treatment plan can be used to perform radiotherapy treatment on the patient's treatment targets via the radiotherapy machine 1000.

[0043] More specifically, for example, TPS 150 defines a proposed radiation therapy plan that is stored in and accessed from a computer system memory. As described above, the treatment modalities of the treatment plan include intensity modulated radiation therapy (IMRT) and intensity modulated particle therapy (IMPT).

[0044] In IMRT embodiments, the photon beam includes multiple beam segments or beamlets. A multi-leaf collimator (MLC) is used to shape the beam before or while directing the beam into the treatment target. In one or more such embodiments, the maximum energy of the beam (e.g., 80 MeV) is specified, and the energy of each beamlet in the beamlets is determined as a percentage (100% or less) or an equivalent fraction of the maximum beam energy. Therefore, each beamlet in the beamlets can be weighted based on its energy level. By weighting each beamlet based on its energy, each beamlet is actually also weighted based on its intensity.

[0045] In IMPT (e.g., spot or pencil beam scanning) embodiments, a proton or ion beam is directed to a spot in a treatment target as specified in the treatment plan. For each energy slice of the beam, the specified spot locations are typically arranged in a fixed (raster) pattern, and the beam is delivered on a fixed scan path within the energy slice. For example, each spot can be weighted based on the number of protons received when the beam is irradiated. The weight of each spot can be expressed as a value of monitoring units (e.g., proton number) or MU.

[0046] Candidate radiation therapy treatment plans include values ​​of parameters that may affect dose and / or dose rate, as well as other parameters. Depending on the treatment modality, the parameters may include, but are not limited to: beam shape (collimation); number and arrangement of spots for spot (pencil beam) scanning, and spot weights; beamlet weights; beamlet intensity or energy; beam / beamlet direction; prescribed dose and prescribed dose rate; number of irradiations of the target volume; duration of each irradiation in the irradiation (irradiation time); and dose deposited in each irradiation in the irradiation. Parameters may also include the time period over which the irradiation is applied (e.g., the number of times the irradiation is applied in a time period such as one hour, where each irradiation is separated from the next irradiation in the time period by another time period) and the time interval between each irradiation period (e.g., each hour-long period is separated from the next period by one day).

[0047] The large number of parameters and their value ranges may result in an effectively infinite number of potential treatment plans. Therefore, consistently and efficiently generating and evaluating high-quality treatment plans is beyond human capabilities and relies on and / or requires the use of computing systems.

[0048] To deliver a prescribed radiation dose / dose rate, the radiotherapy plan can be converted (e.g., by TPS 150) into machine parameters of a radiotherapy machine (e.g., radiotherapy machine 1000). The machine parameters may include, for example, the beam current of the proton, ion, or photon beam, the number of protons, ions, photons emitted by the accelerator in each time segment, the magnet current, the settings to achieve the prescribed energy of the protons, ions, or photons at the target volume, and the measurement range of the dose monitoring system. This conversion therefore takes into account the limitations of the processor equipment that generates the beam and delivers and monitors the radiotherapy.

[0049] During treatment, the beam enters the nozzle of the radiotherapy 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 transverse to the beam axis in the treatment target. In other examples, energy modulation is performed outside the nozzle (e.g., upstream of the nozzle).

[0050] The nozzle is mounted on a movable gantry so that the beam can be delivered from different directions (angles) relative to the patient (or the patient's treatment target) on the patient support device, and the position of the patient support device relative to the beam can also be changed.

[0051] Figure 2A An example of a beam view of a treatment target 208 in some (e.g., IMPT) example embodiments is shown. The treatment target 208 can conform to the shape of the treated volume (e.g., the contour of the treatment target can conform to the contour of the tumor), the treatment target can be larger than the treated volume, or the treatment target can correspond to a portion of the treated volume (e.g., a sub-volume).

[0052] 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 may be irradiated with a raster scan (two-dimensional emission) of a spot scanning beam (pencil beam). Generally, a first pencil beam is directed at a first spot 204 in the treatment target 208, a dose rate is delivered to that spot, then a second pencil beam is directed at a second spot 206 in the treatment target, a dose rate is delivered to the second spot 206, and so on. Spots with a weight or MU value of zero are not irradiated.

[0053] Each spot scanning beam can deliver a relatively high dose rate to each spot (provide a relatively high dose in a relatively short period of time). For example, if necessary, the spot scanning beam can deliver more than 40 grays (Gy) of energy to each spot in less than a second.

[0054] Figure 2B An example of a beam view of a treatment target 208 in other (e.g., IMRT) example embodiments is shown. In these example embodiments, a beam 220 used to irradiate 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 is specified for the beam 220, and the energy of each of the beamlets 214, 216, etc. is determined as a percentage or fraction of the maximum beam energy.

[0055] Each beamlet can deliver a relatively high dose rate (a relatively high dose in a relatively short period of time). For example, if necessary, each beamlet can deliver more than 40 grays (Gy) of radiation in less than a second. No beamlets with a weight or MU of zero are used during treatment.

[0056] Figure 3is a block diagram illustrating an example of an automated radiation therapy treatment planning process 300 according to an example embodiment. The process 300 may be performed in whole or in part in Figure 1 The computer system 100 in the embodiment is implemented as a software program, hardware logic or a combination thereof.

[0057] refer to Figure 3 In step 302, the computer system 100 obtains a three-dimensional (3D) image of the patient and segments and contours the organs and other structures (patient geometry) in the patient. In steps 304 and 306, as will be described below, Figure 4 Discussed in more detail, the system 100 develops and evaluates a radiation therapy treatment plan based on the information obtained in step 302 and other information.

[0058] In step 308, if the treatment plan developed by the system 100 is satisfactory (e.g., meets the clinical goals), the radiation therapy treatment plan can be used to treat the patient's treatment targets (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 then use the satisfactory radiation therapy treatment plan to treat the patient (e.g., using the radiation therapy machine 1000). The clinical goals can be expressed in terms of a set of quality indicators, such as target homogeneity, consistency with treatment targets, critical organ sparing, etc., which have corresponding target values ​​for the quality indicators.

[0059] 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 performed in whole or in part in Figure 1 The process 400 may be implemented as a software program, hardware logic, or a combination thereof on / using 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 .

[0060] refer to Figure 4 , TPS150 accesses or receives (for example, from Figure 1 The memory 104 of the TPS 150 includes information of parameters such as those described above. The TPS 150 may also access or receive information specific to the patient to be treated (e.g., patient geometry), including information describing treatment targets (regions of interest, ROIs), which may include planning target volumes (PTVs), gross tumor volumes (GTVs), clinical target volumes (CTVs), and / or organs at risk (OARs).

[0061] The TPS 150 also accesses or receives an objective function defined for treating a patient. An objective function is a mathematical formula of variables (parameters such as those described above) that may have an impact on achieving a specified clinical goal. More specifically, the objective function is used to evaluate a proposed radiation therapy treatment plan to determine whether the clinical goals specified for treating a patient are met.

[0062] 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 expected to receive according to the proposed treatment plan, d p is the prescribed dose for each voxel, and the sum ∑ is for 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 the dose objective function (in this example, as the value of the function decreases, the dose across the treatment target becomes more uniform). In practice, in order to achieve the best final treatment plan, several objective functions (in addition to the dose objective function) may need to be minimized. Objective functions may conflict with each other; that is, minimizing one objective function may penalize 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, and the sum may then be minimized.

[0063] Still refer to Figure 4 In some (e.g., IMPT) example embodiments, the information accessed or received by TPS 150 may include, but is not limited to, the number and location (pattern or arrangement) of spots, a weight value (e.g., initial value) 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 monitoring units (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 described, each spot corresponds to a location in the treatment target. As such, each spot weight may be referred to as a "position" weight or a position-based weight: a spot corresponds to a location, a weight corresponds to a spot, and thus a spot weight corresponds to a location. Essentially, in example embodiments, a spot weight is assigned to or associated with a corresponding location within the treatment target.

[0064] In other (e.g., IMRT) example embodiments, the information accessed or received by TPS 150 may include, but is not limited to, the number of beamlets, a weight value (e.g., an initial value) for each beamlet (where the weight corresponds to a fraction or percentage of the beam energy), and a dosimetry objective function that takes into account dose targets for the PTV and OARs. The weight of each beamlet may be expressed as a value of MU, for example, which corresponds to the intensity or energy of the beamlet as a fraction or percentage of the beam intensity or energy. As described above with respect to Figure 2B As described, each beamlet corresponds to a location in the treatment target. Similar to the spot weights, each beamlet weight can be referred to as a location weight 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, in these example embodiments, the beamlet weights are assigned to or associated with corresponding locations within the treatment target.

[0065] When generating and optimizing a treatment plan, the TPS 150 can adjust the weights of the spots or beamlets relative to, for example, a dosimetry objective function. In addition to the objectives already mentioned herein, another objective is to determine and output a set of final weights such that during treatment, the treatment target will receive a uniform dose (uniform dose across the treatment target) and the delivered dose will be closer to the edge of the treatment target.

[0066] For various reasons (e.g., overcoming machine hardware constraints, increasing dose rate, reducing delivery time, etc.), clinicians may desire and / or require that the weights or MUs of the corresponding spots and / or beamlets of the treatment plan be above or below a certain threshold (referred to as minimum MU, minimum MU number, or minimum MU value).

[0067] However, conventional radiation therapy planning systems do not provide mechanisms to fully assess and control the goals of treatment planning in real time, resulting in delays in radiation therapy, potentially harming the patient. Such delays also result in additional (and unnecessary) optimization iterations, which unnecessarily utilize increased processing resources and power.

[0068] One or more example embodiments provide solutions to at least these shortcomings of conventional radiation therapy treatment planning systems. More specifically, for example, one or more example embodiments provide mechanisms to provide and / or display renderings of representations of one or more MU distributions (also referred to as MU distributions) for one or more (e.g., candidate) radiation therapy treatment plans to a clinician during treatment planning. The distributions of MUs for one or more candidate radiation therapy treatment plans can be displayed in various ways and / or at one or more different stages of the planning process (e.g., during plan optimization, beam planning, and / or plan evaluation). In at least one example, the one or more MU distributions can be displayed as one or more renderings on a graphical user interface (GUI) displayed by an output device 126. Reference will be made later to the embodiments of the present invention. FIG. 9A to FIG. 15 An example representation of a MU distribution is discussed, wherein a rendering of the representation is shown displayed on an output device (eg, display device) 126 .

[0069] By displaying a representation of the MU distribution of one or more radiation therapy treatment plans, the objectives of the treatment plans can be evaluated and / or controlled in real time, thereby increasing the speed with which a satisfactory treatment plan is determined and the treatment is performed on a patient. Thus, treatment of the patient can be expedited, or in other words, the patient can be given an expedited radiation therapy treatment, thereby increasing the patient's chance of survival. The display of representations of the MU distribution of one or more radiation therapy treatment plans also enables improved control and / or interaction with an optimizer to increase the speed with which a satisfactory treatment plan is determined and the treatment is performed on a patient. In one example, a treatment plan can be tuned and the optimizer can be directed to produce results more quickly than with conventional techniques. By reducing the time required to obtain a satisfactory treatment plan, the number of optimizer iterations is reduced, which reduces the processing power and resources required to generate a treatment plan for a patient.

[0070] In addition, radiation therapy plans typically include hundreds of thousands of spots or beamlets. As a result, traditionally, it has been impossible for humans to properly evaluate and control the goals of a treatment plan in real time by analyzing the MU of a treatment plan or a field (beam) of a treatment plan. According to an example embodiment, the display of the representation not only allows the clinician to evaluate and / or control the goals of the treatment plan, which was not previously possible, but can also be done relatively quickly. For example, the clinician can verify (e.g., at a glance) whether the treatment plan is delivered above the minimum MU, verify (e.g., at a glance) whether the plan is sufficiently robust, evaluate whether the field has a MU distribution sufficient to be delivered in a relatively short period of time, evaluate whether the field is delivered in a sufficiently robust manner, determine whether the field contributes less dose than other fields (e.g., due to OAR constraints), and so on. Although described as an example of clinician evaluation, other mechanisms for rendering of representations for evaluating MU distributions, such as machine learning, may also be used.

[0071] According to one or more example embodiments, without rendering and displaying of a representation of a MU distribution, the above advantages would not be achieved.

[0072] The following will be about Figures 5 to 15 More detailed example embodiments are discussed.

[0073] Figure 5 is a flow chart illustrating a method for rendering and displaying one or more representations of MU distributions for a treatment plan according to an example embodiment. Figure 5 The method shown will be discussed as Figure 1304. The computer system 100 in FIG. 304 and more specifically the TPS 150 during the planning / evaluation / optimization 304 may be implemented. However, example embodiments should not be limited to this example.

[0074] refer to Figure 5 In step S502, TPS 150 generates a radiation therapy treatment plan for the patient. In one example, the generated radiation therapy treatment plan may be as described above with respect to Figure 3 and Figure 4 Alternatively, the TPS 150 may obtain a previously generated radiation therapy treatment plan stored in, for example, the memory 108 and / or 120. The radiation therapy treatment plan specifies beam characteristics for a plurality of spots or beamlets in a treatment target. The beam characteristics include at least an MU associated with each of the plurality of spots or beamlets in the treatment plan.

[0075] In step S504, TPS150 generates one or more MU distributions for the radiotherapy treatment plan generated (or obtained) in step S502. TPS150 can generate one or more MU distributions in any suitable known manner. In one example, a MU distribution can be generated for the entire radiotherapy treatment plan. In another example, individual or separate MU distributions can be generated on a per-field (per-beam) basis; that is, for example, a MU distribution can be generated for each field (beam) of the radiotherapy treatment plan. In this case, for each corresponding MU, the MU distribution can indicate a small beam or spot in the field with the corresponding MU. TPS150 can generate a MU distribution for one or more (e.g., each) field of the radiotherapy treatment plan.

[0076] return Figure 5 At step S506, the TPS 150 generates and displays via the GUI on the output device 126 a rendering of one or more (visual) representations of one or more MU distributions (e.g., each MU distribution) for the radiation therapy treatment plan generated (or obtained) at step S502. In one example, the representation of the MU distribution may be a histogram in which the horizontal (x) axis represents the MU and the vertical (y) axis represents the number of times a beamlet or spot with a given MU appears in the radiation therapy treatment plan.

[0077] In some instances, the absolute number of beamlets or spots with a given MU may not be particularly important to the treatment planner or plan user. In such cases, the full histogram representation of the MU distribution can be simplified to a density map, where areas where the bars are more tightly grouped indicate that there are more beamlets or spots in that area and have MUs that are similar or relatively close to the particular MU. In this case, the representation of the MU distribution can take the form of a density map or a color density map.

[0078] In another example, the MU distribution may be visually represented in the form of a combination of a histogram and a corresponding density map. The histogram and density map may be displayed together in a single rendering in the GUI, or may be displayed in separate renderings.

[0079] According to one or more example embodiments, for representations of individual fields of a radiation therapy treatment plan, histograms and / or density maps of the respective fields may be displayed one above the other, side by side, or overlapping as desired. A clinician may configure the display of the representations as desired.

[0080] Fig.9A , Fig. 9B , Fig. 9C and Fig.9D An example rendering of a histogram representing MU distribution for a radiation therapy treatment plan is shown in accordance with an example embodiment. 9A to 9D In the example shown, the MU of a radiation therapy treatment plan is displayed as a histogram for the entire plan. The horizontal (x) axis represents the MU, and the vertical (y) axis represents the number of times a beamlet or spot with a given MU appears in the plan. Although not shown, the scale of the y-axis can alternatively be set to logarithmic.

[0081] As shown in the figure, Fig.9A Shown is a histogram representation of the MU distribution for a radiation therapy treatment plan with relatively balanced MUs among the beamlets or spots.

[0082] Fig. 9B Shows something like Fig.9A A histogram representation of the MU distribution for a radiation therapy treatment plan, but one of the beamlets or spots has a higher MU (e.g., significantly or substantially) than the other beamlets or spots.

[0083] Fig. 9C A histogram representation of the MU distribution for a radiotherapy treatment plan is shown for spots or beamlets with MU above a threshold. In this example, the threshold is the minimum MU, which is Fig. 9C is designated as the “minimum MU”.

[0084] Fig.9D A histogram representation of the MU distribution for radiotherapy treatment planning is shown, where Fig. 9C It is shown that a threshold (eg, minimum MU) constraint is applied, but one spot or beamlet is below the threshold, thereby violating the constraint.

[0085] Fig.10 An example rendering of a combination of representations of MU distributions is shown, where a full histogram (a) is shown together with (e.g., above) a corresponding density map (B) and a corresponding color density map (C). The color density map shows the density map and histogram. Figure 1 It should be noted that the gradient scale can be linear or logarithmic as desired.

[0086] As described above, for each field of the radiation therapy treatment plan, the TPS 150 can display one or more individual or separate MU distributions. Displaying a representation of the MU distribution for each field may be desirable and / or useful, for example, when: one of the fields needs to be specifically delivered in a relatively short period of time, one of the fields needs to be specifically delivered in a more robust manner, the dose contribution of one of the fields is significantly or much lower than that of the other fields (e.g., due to OAR constraints), etc.

[0087] Fig.11 An example rendering of a representation of the MU distribution for each field used in a radiation therapy treatment plan is shown. Fig.11 , the MU distribution for two fields (field 1 and field 2) is displayed on the same histogram. In this example, the histograms for the individual fields are stacked vertically so that the histogram shows the MU distribution for the entire radiotherapy treatment plan. As shown, different colors (or grayscales) can be used for each field to depict the MU distribution.

[0088] Fig.12 An example rendering of a combination of representations of individual MU distributions for respective fields of a radiotherapy treatment plan, and a representation of the MU distribution for the entire radiotherapy treatment plan is shown. In this example, the MU distributions are represented as different color density maps for each respective field. The MU distributions for the treatment plans are shown on a separate axis (total number of plans), with the density maps of the respective fields overlaid on each other.

[0089] Fig.13 Shows Fig.12 1 shows an example rendering of a combination of color density maps, and a minimum MU value indicator on each density map. During optimization, the visual representation of the MU distribution at each iteration provides direct feedback to indicate and / or provide an understanding of whether MU-related goals are being achieved. The simplest goal a user may want to set is a minimum and maximum value between which the MU distribution must be constrained. According to one or more example embodiments, the MU distribution can be constrained to be within the range of the minimum and maximum values ​​​​between. Fig.13The GUI presented as shown is used to set at least a minimum MU value. For example, if implemented as a GUI on a touch screen display, a user can touch a portion of one or more of the color density maps to establish and / or adjust the minimum and / or maximum MU for a field or radiation therapy treatment plan.

[0090] Figure 6 is a flow chart illustrating a method for radiation therapy treatment according to an example embodiment. Figure 6 The method shown includes Figure 5 Therefore, for the sake of brevity, these steps will not be described in detail here. Figure 1 System Description Shown Figure 6 However, the example embodiments should not be limited to this example.

[0091] refer to Figure 6 , after displaying one or more representations of the MU distribution for the candidate radiation therapy treatment plans in step S506, the treatment plans may be evaluated based on the rendered representation(s) in step S608. In one example, the treatment plans may be evaluated based on a preferred treatment plan or desired characteristics of a preferred treatment plan. More specifically, for example, a treatment planner or TPS may desire, prefer, and / or require that there be no plans with MU values ​​below a certain threshold (e.g., a certain minimum MU value), and evaluate the treatment plans based on this desire, preference, and / or requirement. In this case, if the treatment plan does not include any MU values ​​below the threshold (all MU values ​​are above the threshold), the treatment plan may be considered satisfactory. On the other hand, if the treatment plan includes one or more MU values ​​below the threshold, the treatment plan may be considered unsatisfactory. Although discussed with respect to this example, example embodiments should not be limited to this example case.

[0092] If it is determined at S610 that the radiation therapy treatment plan is satisfactory, then at 308 , the TPS 150 may further optimize and / or output the radiation therapy treatment plan for use in treating the patient (eg, via the radiation therapy machine 1000 ). Figure 3 Step 308 in Figure 3 The process is the same as step 308 in , and therefore a detailed description will be omitted for brevity.

[0093] Returning to step S610 , if it is determined that the radiation therapy treatment plan is not satisfactory, the TPS 150 may modify the radiation therapy treatment plan and / or the clinical goals at step S614 .

[0094] After modifying the radiation therapy treatment plan and / or clinical goals at step S614, the process returns to step S504 where the TPS 150 generates a MU distribution for the updated radiation therapy treatment plan. The process then proceeds to step S506 and continues as discussed herein.

[0095] As discussed below, one or more example embodiments also provide a mechanism for the clinician to adjust and / or define a cost (objective) function for optimizing a radiation therapy plan via interaction with a GUI.

[0096] Figure 7 is a flow chart illustrating a method for radiation therapy treatment according to an example embodiment. Figure 6 Same method as shown, Figure 7 The method shown includes Figure 5 Therefore, for the sake of brevity, these steps will not be described in detail here. Figure 1 System Description Shown Figure 7 However, the example embodiments should not be limited to this example.

[0097] refer to Figure 7 , after displaying a rendered GUI (e.g., on display device 126) that includes a representation of the MU distribution for a candidate radiation therapy treatment plan, TPS 150 receives a defined MU distribution for the radiation therapy treatment plan. In at least one example embodiment, a clinician may manually define a desired MU distribution by defining a cost (objective) function for the radiation therapy treatment plan or its field via an interface of TPS 150. In one example, the GUI may be a touch screen or other input device that enables a clinician to interact with TPS 150 to define the cost function. In another example, a clinician may interact with TPS 150 via a mouse, keyboard, or other input device.

[0098] In one example, the GUI for defining the cost function can be similar to an audio equalizer interface. A clinician can draw a spline curve on top of a displayed histogram representation of the MU distribution (e.g., via a touch screen or other input device) to define a cost function for a radiation therapy treatment plan or field thereof, and then adjust the cost function by manipulating the displayed histogram at adjustment points.

[0099] Fig.14An example GUI rendering of a user-adjustable representation of a MU distribution for a radiation therapy treatment plan is shown. As shown, a spline curve 1402 can be drawn on top of a histogram to define a cost function. Similar to an audio equalizer interface, an adjustment point 1404 can be moved up and down via interaction with the GUI (e.g., via a touch screen or other input device) to adjust the cost function of the corresponding radiation therapy treatment plan.

[0100] Return to Figure 7 At step S710, the TPS 150 adjusts the MU distribution and the displayed representation of the MU distribution (as needed) based on the input provided at step S708. In at least one example embodiment, a histogram or other representation of the MU distribution may be updated in real time based on adjustments to the cost function via the GUI (e.g., as described above with respect to Figure 3 to Figure 4 discussed).

[0101] Once adjusted, at step 308, the radiation therapy plan may be output and the radiation therapy performed (eg, via the radiation therapy machine 1000), as described above with respect to Figure 3 discussed, with or without further evaluation and optimization.

[0102] One or more example embodiments may also provide a mechanism for evaluating and / or comparing two or more candidate radiation therapy treatment plans.

[0103] Figure 8 is a flow chart illustrating a method for radiation therapy treatment including comparison of two or more radiation therapy treatment plans according to an example embodiment. Figure 8 The example embodiment shown. However, the example embodiment should not be limited to this example. Instead, any number of radiation therapy treatment plans may be used. In addition, the first MU distribution and corresponding representation and the second MU distribution and corresponding representation will be discussed. Figure 8 However, it should be understood that the example embodiments are not limited to a single MU distribution and corresponding representation. Instead, one or more MU distributions and corresponding representations may be generated for each of the first radiation therapy treatment plan and the second radiation therapy treatment plan.

[0104] About Figure 1 System Description Shown Figure 8 However, the example embodiments should not be limited to this example.

[0105] refer to Figure 8 In step S802, TPS 150 generates or obtains a first radiation therapy treatment plan and a second radiation therapy treatment plan. Each of the first radiation therapy treatment plan and the second radiation therapy treatment plan can be similar to the above description of Figure 5The method is generated or obtained in the same or substantially the same manner as discussed in step S502 in the above description.

[0106] In step S804, the TPS 150 generates a first MU distribution for the first radiation therapy treatment plan generated (or obtained) in step S802, and generates a second MU distribution for the second radiation therapy treatment plan generated (or obtained) in step S802. Each of the first MU distribution and the second MU distribution can be in the same manner as described above with respect to Figure 5 The method is generated or obtained in the same or substantially the same manner as discussed in step S504 in the above description.

[0107] In step S806, TPS150 displays a GUI that includes renderings of at least one representation of a first MU distribution for a first candidate radiation therapy treatment plan and at least one representation of a second MU distribution for a second candidate radiation therapy treatment plan. The representations of the first MU distribution and the second MU distribution can be displayed concurrently and / or simultaneously in a single rendering of the GUI. In one example, each MU distribution can be presented as a histogram and / or density map as described herein. The histograms (or other representations, such as density maps) of each plan in the first candidate radiation therapy treatment plan and the second candidate radiation therapy treatment plan can be overlapped with each other for comparison. Alternatively or in combination, the histograms (or other representations, such as density maps) of the first candidate radiation therapy treatment plan and the second candidate radiation therapy treatment plan can be arranged side by side. In one example, the MU distribution can be represented as, for example, a semi-transparent histogram overlapped on the same figure and / or two different color density maps arranged one above the other or side by side.

[0108] Fig.15 An example GUI rendering of a representation of the MU distribution for two candidate radiation therapy treatment plans is shown. Fig.15 In the example shown, the MU distribution is represented as, for example, semi-transparent histograms partially overlapping each other on the same graph, and is also represented as two different color density graphs arranged one above the other.

[0109] Return to Figure 8 At step S808, the TPS 150 may select one of the first candidate radiation therapy treatment plan and the second candidate radiation therapy treatment plan based on the displayed representation of the MU distribution for the treatment plan. In one example, the clinician may select one of the two radiation therapy plans via the TPS interface.

[0110] At 308, radiation therapy (with or without further evaluation and optimization) may be performed on the patient according to the selected radiation therapy treatment plan as discussed above (e.g., via radiation therapy machine 1000). The following is a list of non-limiting illustrative embodiments disclosed herein:

[0111] Illustrative embodiment 1. A system 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 or obtains a first radiation therapy plan for a treatment target in a patient, the first radiation therapy plan specifies beam characteristics of a plurality of beamlets or spots in the treatment target, the beam characteristics comprising a monitoring unit value associated with each of the plurality of beamlets or spots in at least a first field; and displays at least one representation of a first distribution of monitoring units for the first radiation therapy plan via a graphical user interface, the at least one representation of the first distribution of monitoring units indicating, for each corresponding monitoring unit value, the number of beamlets or spots in at least the first field having the corresponding monitoring unit value.

[0112] Illustrative embodiment 2. The system of illustrative embodiment 1, wherein the at least one processor is configured to execute the computer executable instructions to cause the system to display the at least one representation during radiation therapy plan optimization.

[0113] Illustrative embodiment 3. The system of any of the preceding illustrative embodiments, wherein the at least one processor is configured to execute the computer executable instructions to cause the system to display, via the graphical user interface, a plurality of representations of the first distribution of monitoring units.

[0114] Illustrative embodiment 4. The system of any of the preceding illustrative embodiments, wherein the plurality of representations of the first distribution of monitoring units comprises at least one histogram and at least one density map.

[0115] Illustrative embodiment 5. The system of any of the preceding illustrative embodiments, wherein the plurality of representations of the first distribution of monitoring units are displayed simultaneously via the graphical user interface.

[0116] Illustrative embodiment 6. The system of any of the preceding illustrative embodiments, wherein the plurality of representations of the first distribution of monitoring units comprises at least one histogram and at least one density map.

[0117] Illustrative embodiment 7. The system according to any of the preceding illustrative embodiments, further comprising: a radiation therapy machine configured to apply a radiation therapy treatment to the treatment target based on the first radiation therapy plan after displaying the at least one representation.

[0118] Illustrative embodiment 8. The system of any of the preceding illustrative embodiments, wherein the at least one representation of the first distribution of monitoring units comprises at least one of a histogram or a density map.

[0119] Illustrative embodiment 9. The system of any of the preceding illustrative embodiments, wherein the at least one representation of the first distribution of monitoring units comprises a density map, and the at least one processor is configured to execute the computer executable instructions to cause the system to display a marker on the density map, the marker being used to indicate a minimum monitoring unit of at least one of the first radiation treatment plan or the first field.

[0120] Illustrative embodiment 10. The system of any of the preceding illustrative embodiments, wherein the at least one processor is configured to execute the computer executable instructions to cause the system to display, via the graphical user interface, at least one representation of a second distribution of monitoring units for a second field of the first radiation therapy plan, the at least one representation of the second distribution of monitoring units indicating, for each respective monitoring value, a number of beamlets or spots in the second field having the respective monitoring unit value.

[0121] Illustrative Embodiment 11. The system of any of the preceding illustrative embodiments, wherein the at least one representation of the first distribution and the at least one representation of the second distribution overlap each other.

[0122] Illustrative embodiment 12. The system of any of the preceding illustrative embodiments, wherein the at least one processor is configured to execute the computer executable instructions to cause the system to receive a defined distribution of monitoring units for the first radiation therapy plan, and to adjust the first distribution of monitoring units based on the defined distribution of monitoring units.

[0123] Illustrative Embodiment 13. The system of any one of the preceding illustrative embodiments, wherein the at least one representation of the first distribution is a color density map.

[0124] Illustrative Embodiment 14. A 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 to cause the system to: generate a first candidate radiation therapy plan for a treatment target in a patient, the first candidate radiation therapy plan specifying a first beam characteristic of a plurality of beamlets or spots in the treatment target, the first beam characteristic including a first monitoring unit value associated with each of the plurality of beamlets or spots; generate a second candidate radiation therapy plan for the treatment target in the patient, the second candidate radiation therapy plan specifying a second beam characteristic of the plurality of beamlets or spots in the treatment target, the second beam characteristic including a second monitoring unit value associated with each of the plurality of beamlets or spots; display via a graphical user interface at least one representation of a first distribution of monitoring units for the first candidate radiation therapy plan, the at least one representation of the first distribution of monitoring units indicating, for each respective first monitoring value, a first number of beamlets or spots having the respective first monitoring unit value; and display via the graphical user interface at least one representation of a second distribution of monitoring units for the second candidate radiation therapy plan, the at least one representation of the second distribution of second monitoring units indicating, for each respective second monitoring value, a second number of beamlets or spots having the respective second monitoring unit value.

[0125] Illustrative embodiment 15. The system of illustrative embodiment 14, wherein the at least one representation of the first distribution and the at least one representation of the second distribution comprise at least one of a histogram or a density map.

[0126] Illustrative Embodiment 16. The system of any of Illustrative Embodiments 14 to 15, wherein the at least one representation of the first distribution and the at least one representation of the second distribution overlap each other.

[0127] Illustrative Embodiment 17. The system of any one of Illustrative Embodiments 14 to 16, wherein the at least one processor is configured to execute the computer executable instructions to cause the system to select one of the first candidate radiation treatment plan or the second candidate radiation treatment plan as the radiation treatment plan for the patient based on the first distribution and the second distribution.

[0128] Illustrative Embodiment 18. The system of any one of Illustrative Embodiments 14 to 17, further comprising: a radiation therapy machine configured to apply radiation therapy treatment to the patient based on the radiation therapy plan for the patient.

[0129] Illustrative Embodiment 19. The system of any one of Illustrative Embodiments 14 to 18, wherein at least one of the at least one representation of the first distribution or the at least one representation of the second distribution comprises a color density map.

[0130] Illustrative embodiment 20. The system of any one of illustrative embodiments 14 to 19, wherein the at least one processor is configured to execute the computer executable instructions to cause the system to display the at least one representation of the first distribution of monitoring cells and the at least one representation of the second distribution of monitoring cells during radiation therapy plan optimization.

[0131] 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, without departing from the scope of the present disclosure, the first element may be referred to as the second element, and similarly, the second element may be referred to as the first element. As used herein, the term "and / or" includes any and all combinations of one or more items in the associated listed items.

[0132] 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. Conversely, 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.).

[0133] The terms used herein are for the purpose of describing specific embodiments only 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 be further understood that the terms "comprises", "comprising", "includes" and / or "including" when used herein specify the presence of stated features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements and / or components and / or groups thereof.

[0134] 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.

[0135] Specific details are provided in the following description to provide a thorough understanding of the example embodiments. However, those skilled 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 examples, well-known processes, structures, and techniques may be shown without unnecessary detail so as to avoid obscuring the example embodiments.

[0136] As discussed herein, the illustrative embodiments will be described with reference to acts and symbolic representations of operations (e.g., in the form of flowcharts, flow diagrams, data flow diagrams, structure diagrams, block diagrams, etc.), which 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, for example, 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 capable of responding to and executing instructions in a defined manner.

[0137] Although a flowchart may describe operations as a sequential process, many 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, procedure, 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.

[0138] 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 instructions and / or data.

[0139] 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 segments for performing the necessary tasks may be stored in a machine or computer readable medium such as a computer readable storage medium. When implemented in software, one or more processors will perform the necessary tasks. For example, as described above, according to one or more example embodiments, at least one memory may include or store computer program code, and at least one memory and 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, processors, memories, and example algorithms encoded as computer program codes are used as means for providing or causing the execution of the operations discussed herein.

[0140] As used herein, the terms "including" and / or "having" are defined as including (i.e., open language). As used herein, the term "coupled" is defined as connected, although not necessarily directly connected, and not necessarily mechanically connected. Terms derived from the word "indicating" (e.g., "indicates" and "indication") are intended to cover all various techniques that can be used to convey or reference the indicated object / information. Some, but not all, examples of techniques that can be used to convey or reference the indicated object / information include transmission of the indicated object / information, transmission of an indicator of the indicated object / information, transmission of information used to generate the indicated object / information, transmission of some portion or part of the indicated object / information, transmission of some derivative of the indicated object / information, and transmission of some symbol representing the indicated object / information.

[0141] 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 capable of responding to and executing instructions in a defined manner.

[0142] Benefits, other advantages, and solutions to problems have been described above with respect to specific embodiments. However, benefits, advantages, solutions to problems, and any elements that may cause or derive such benefits, advantages, or solutions, or make such benefits, advantages, or solutions more significant, should not be construed as key, required, or essential features or elements of any or all of the claims.

Claims

1. A 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: generating or obtaining a first radiation therapy plan for a treatment target in a patient, the first radiation therapy plan specifying beam characteristics of a plurality of beamlets or spots in the treatment target, the beam characteristics including monitoring unit values ​​associated with each of the plurality of beamlets or spots in at least a first field, and At least one representation of a first distribution of monitoring units for the first radiotherapy plan is displayed via a graphical user interface, the at least one representation of the first distribution of monitoring units indicating, for each respective monitoring unit value, a number of beamlets or spots in at least the first field having the respective monitoring unit value.

2. The system of claim 1, wherein the at least one processor is configured to execute the computer executable instructions to cause the system to display the at least one representation during radiation therapy plan optimization. 3 . The system of claim 1 , wherein the at least one processor is configured to execute the computer-executable instructions to cause the system to display, via the graphical user interface, a plurality of representations of the first distribution of monitoring units. 4 . The system of claim 3 , wherein the plurality of representations of the first distribution of monitoring units comprises at least one histogram and at least one density plot. 5 . The system of claim 3 , wherein the plurality of representations of the first distribution of monitoring units are displayed simultaneously via the graphical user interface. 6 . The system of claim 5 , wherein the plurality of representations of the first distribution of monitoring units comprises at least one histogram and at least one density plot.

7. The system of claim 1, further comprising: A radiation therapy machine is configured to apply a radiation therapy treatment to the treatment target based on the first radiation therapy plan after displaying the at least one representation.

8. The system of claim 1, wherein the at least one representation of the first distribution of monitoring units comprises at least one of a histogram or a density map.

9. The system of claim 1, wherein: The at least one representation of the first distribution of monitoring units comprises a density map, and The at least one processor is configured to execute the computer-executable instructions to cause the system to display a marker on the density map, the marker indicating a minimum monitoring unit for at least one of the first radiation therapy plan or the first field.

10. The system of claim 1 , wherein the at least one processor is configured to execute the computer-executable instructions to cause the system to display, via the graphical user interface, at least one representation of a second distribution of monitoring cells for a second field of the first radiation treatment plan, the at least one representation of the second distribution of monitoring cells indicating, for each respective monitoring value, a number of beamlets or spots in the second field having the respective monitoring cell value.

11. The system of claim 10, wherein the at least one representation of the first distribution and the at least one representation of the second distribution overlap each other.

12. The system of claim 1, wherein the at least one processor is configured to execute the computer executable instructions so that the system: receiving a defined profile of monitoring units for the first radiation therapy plan, and The first distribution of monitoring units is adjusted based on the defined distribution of monitoring units.

13. The system of claim 1, wherein the at least one representation of the first distribution is a color density map.

14. A 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: generating or obtaining a first candidate radiation therapy plan for a treatment target in a patient, the first candidate radiation therapy plan specifying first beam characteristics of a plurality of beamlets or spots in the treatment target, the first beam characteristics comprising first monitoring unit values ​​associated with each of the plurality of beamlets or spots, generating or obtaining a second candidate radiation therapy plan for the treatment target in the patient, the second candidate radiation therapy plan specifying second beam characteristics of the plurality of beamlets or spots in the treatment target, the second beam characteristics comprising second monitoring unit values ​​associated with each of the plurality of beamlets or spots, displaying, via a graphical user interface, at least one representation of a first distribution of monitoring units for the first candidate radiation treatment plan, the at least one representation of the first distribution of monitoring units indicating, for each respective first monitoring value, a first number of beamlets or spots having the respective first monitoring unit value, and At least one representation of a second distribution of monitoring units for the second candidate radiation treatment plan is displayed via the graphical user interface, the at least one representation of the second distribution of monitoring units indicating, for each respective second monitoring value, a second number of beamlets or spots having the respective second monitoring unit value.

15. The system of claim 14, wherein the at least one representation of the first distribution and the at least one representation of the second distribution comprise at least one of a histogram or a density map.

16. The system of claim 14, wherein the at least one representation of the first distribution and the at least one representation of the second distribution overlap each other.

17. The system of claim 14, wherein the at least one processor is configured to execute the computer-executable instructions to cause the system to select one of the first candidate radiation treatment plan or the second candidate radiation treatment plan as the radiation treatment plan for the patient based on the first distribution and the second distribution.

18. The system of claim 17, further comprising: A radiation therapy machine is configured to apply radiation therapy treatment to the patient based on the radiation therapy plan for the patient.

19. The system of claim 14, wherein at least one of the at least one representation of the first distribution or the at least one representation of the second distribution comprises a color density map.

20. The system of claim 14, wherein the at least one processor is configured to execute the computer executable instructions to cause the system to display the at least one representation of the first distribution of monitoring cells and the at least one representation of the second distribution of monitoring cells during radiation therapy plan optimization.

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