Systems and methods for proton therapy treatment planning with proton energy and spatial optimization

Abstract

Embodiments of the present invention disclose methods and systems for proton therapy planning that include the discretization of proton energies and spot optimization of layers and spots using optimization algorithms to generate an optimal distribution of layer energies and spots with a relatively smooth dose distribution. The treatment planning algorithms disclosed herein can freely choose (502) the number of spots and the energy level of the spots. In this way, each spot can be considered its own layer and is not bound by the requirements of other spots / layers. Thereafter, the spots defined by the algorithm can be ordered (503) in a list according to energy level / depth and the spots can be grouped (504) into blocks according to intensity and position. The blocks can be assigned an energy level based on the corresponding spots, such as the average of all spots associated with the block. These blocks are then used as the energy layers applied by the proton therapy treatment system.

Description

Technical Field

[0001] Embodiments of the present invention generally relate to the field of radiotherapy and radiotherapy systems. More specifically, embodiments of the present invention relate to systems and methods for proton therapy treatment planning. Background Technology

[0002] Particle therapy using protons or other ions is a type of radiation therapy that uses an external beam to deliver targeted ionizing radiation to a tumor. Protons or other positively charged ions are fed to an accelerator to bring the particles to a predetermined energy level. The protons or other ions then move through a beam delivery system, where magnets are used as needed to shape, focus, and / or guide the proton or other ion beam.

[0003] Standard radiotherapy systems deposit energy in “spots” along a beam path toward the target tumor. However, the energy delivery also extends beyond the target tumor, potentially delivering radiation into healthy tissue surrounding the tumor site. This excess radiation can damage normal tissue or organs near the target area. Furthermore, the choice of specific energy and the number of spots is determined solely based on patient geometry and hardware constraints. Subsequent optimization of dosimetry standards for treatment has traditionally been performed only on spot intensity, which may yield less than optimal results. It should be understood that the term “spot intensity” as used herein is synonymous with the number of protons in a monitoring cell, for example. Intensity is a relative quantity proportional to the number of protons delivered per spot by the treatment machine.

[0004] Radiation therapy plans can be optimized based on a given dose-volume target for the target volume and the organ at risk, as well as the robustness of the plan using a commercially available treatment planning system. The dose distribution is calculated using beam characteristics and machine-specific dose calibration. However, machine or system limitations may result in machine / treatment delivery system parameters that translate the target dose distribution into machine / treatment delivery system parameters that could produce unacceptable treatment plans. Furthermore, the resulting treatment plan may not utilize the full system / machine capabilities to leverage the system most efficiently and reliably. Treatment plans can be optimized for efficiency and can be modified through trial and error using several complex, interrelated planning parameters (e.g., energy layer distance, spot size, or spot spacing) required for multi-directional optimization. Even if the optimized treatment plan eventually passes standards for plan quality and treatment delivery time, the manual trial-and-error process is time-consuming and may not achieve optimal delivery efficiency.

[0005] More specifically, particle therapy plans using existing technologies are constrained by the delivery of doses in discrete, predetermined increments. For example, to deliver a dose to a 3D volume, multiple discrete beam energies are required, and furthermore, the dose with those energies must be delivered in discrete spots. Traditionally, discretization involves the selection of specific energies, and the discretization scheme for the number and location of spots is determined based on patient geometry and hardware constraints, with treatment plan optimization limited by these constraints. Conversely, subsequent optimization to achieve dosimetry standards for treatment has traditionally been performed only on spot intensity. Because there is a lower limit to the intensity of each spot, the layer used to deliver the dose will consist of only a relatively small number of spots. This often adversely results in a non-uniform dose distribution, which is considered suboptimal clinically.

[0006] Because layer energies are predetermined by existing treatment planning solutions, optimization algorithms cannot address these constraints. Therefore, a particle therapy approach is needed that uses optimization algorithms to discretize layers and spots without existing constraints. This generates optimal distributions of layer energies and spots with a smoother (e.g., more uniform) dose distribution and can advantageously generate fewer layers and potentially fewer spots, thereby reducing the time spent treating patients. Thus, a particle therapy approach that addresses these issues is needed. Summary of the Invention

[0007] More specifically, what is needed is a method for particle therapy that uses an optimization algorithm to discretize layers and spots without existing constraints, generating an optimal distribution of layer energy and spots with a smoother (e.g., more uniform) dose distribution, and advantageously generating fewer layers and potentially fewer spots, thereby reducing the time required to treat patients. Therefore, this document discloses a method and system for proton therapy planning that includes proton energy and spot optimization using an optimization algorithm to discretize layers and spots to generate an optimal distribution of layer energy and spots with a relatively smooth dose distribution. Thus, embodiments of the invention can generate fewer layers and potentially fewer spots, thereby advantageously reducing the time required to treat patients.

[0008] According to one embodiment, a system for proton therapy is disclosed. The system includes: a gantry including nozzles for emitting a controllable proton beam; a proton therapy treatment system that controls the gantry according to a treatment plan; a treatment planning system including a memory; and a processor operable to perform a method for generating a treatment plan. The method includes receiving treatment plan parameters, determining the number of spots and the energy level of the spots based on the treatment plan parameters, calculating the intensity of the spots based on the energy levels, discretizing the spots into a plurality of blocks based on the location and intensity of the spots, wherein the treatment plan includes these blocks, and wherein the blocks represent an energy layer applied by the gantry, and outputting the treatment plan.

[0009] According to some embodiments, the method includes treating a patient using a gantry according to a treatment plan.

[0010] According to some embodiments, the discretization of spots into multiple blocks is performed iteratively until the clinical goal is achieved.

[0011] According to some embodiments, the method includes determining multiple angles for performing proton therapy treatment, and wherein the determination of multiple spots and the energy levels of the spots are also based on the multiple angles.

[0012] According to some embodiments, the method includes the number of receiving layers as user input, wherein the number of spots and the energy level of the spots are also determined based on the number of layers.

[0013] According to some embodiments, the method includes sorting the spots according to depth before discretizing them.

[0014] According to some embodiments, the method includes sorting the spots according to their energy levels before discretizing them.

[0015] According to some embodiments, the energy layer has a fixed width.

[0016] According to some embodiments, the method includes an energy layer with a fixed strength.

[0017] According to another embodiment, a method for proton therapy is disclosed. The method includes receiving treatment plan parameters, determining the number of spots and the energy level of the spots based on the treatment plan parameters, sorting the spots based on the depth of the corresponding spots, calculating the intensity of the spots based on the energy level, discretizing the spots into multiple blocks based on the location and intensity of the spots, wherein each block represents an energy layer applied by a gantry, and outputting a treatment plan, wherein the treatment plan includes the blocks.

[0018] According to various embodiments, a non-transitory computer-readable storage medium in which program instructions are embedded, when executed by one or more processors of the device, causes the device to perform a method for proton therapy. The method includes receiving treatment plan parameters; determining the number of spots and the energy level of the spots based on the treatment plan parameters; sorting the spots based on the depth of the corresponding spots; calculating the intensity of the spots based on the energy level; discretizing the spots into a plurality of blocks based on the location and intensity of the spots, wherein each block represents an energy layer applied by a gantry; and outputting a treatment plan, wherein the treatment plan includes the blocks. Attached Figure Description

[0019] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments of the invention and, together with the specification, serve to explain the principles of the invention:

[0020] Figure 1 A block diagram is shown of an example computing system on which the embodiments described herein can be implemented.

[0021] Figure 2 This is a block diagram illustrating selected components of a radiotherapy system according to an embodiment of the present invention that can be implemented thereon.

[0022] Figure 3 The components of a radiotherapy system according to an embodiment of the invention are shown.

[0023] Figure 4 This is a block diagram illustrating the components in the process of creating an optimized proton therapy treatment plan according to an embodiment of the present invention.

[0024] Figure 5 This is a flowchart depicting exemplary sequential steps for automatically creating an optimized proton therapy treatment plan according to an embodiment of the present invention.

[0025] Figure 6 This is a diagram illustrating an example proton therapy treatment plan with a predetermined energy layer.

[0026] Figure 7 This is a diagram illustrating an example proton therapy treatment plan optimized using a speckle distribution of custom energy layers with fixed intensities for each layer. Detailed Implementation

[0027] Several embodiments will now be described in detail. While the subject matter will be described in conjunction with alternative embodiments, it should be understood that they are not intended to limit the claimed subject matter to these embodiments. Rather, the claimed subject matter is intended to cover alternatives, modifications, and equivalents that may be included within the spirit and scope of the claimed subject matter as defined by the appended claims.

[0028] Furthermore, numerous specific details are set forth in the following detailed description to provide a thorough understanding of the claimed subject matter. However, those skilled in the art will recognize that embodiments can be practiced without these specific details or their equivalents. In other instances, well-known methods, processes, components, and circuits have not been described in detail to avoid unnecessarily obscuring various aspects and features of the subject matter.

[0029] The following detailed description is presented and discussed in terms of method. Although the steps and sequence of the method are disclosed in the diagrams describing its operation herein, these steps and sequences are exemplary. The embodiments are well-suited for performing the flowcharts in the accompanying drawings in a different order than that depicted and described herein (e.g., Figure 5 Various other steps or variations thereof listed in ( ).

[0030] Some parts of the detailed description are presented based on other symbolic representations of processes, steps, logic blocks, operations, and manipulations of data bits that can be executed on computer memory. These descriptions and representations are the means by which those skilled in the art of data processing most effectively communicate the substance of their work to others skilled in the art. Processes, steps, logic blocks, operations, etc., executed by the computer, are generally considered here as self-contained sequences of steps or instructions that lead to a desired result. These steps are steps that require physical manipulation of physical quantities. Typically, although not essential, these quantities take the form of electrical or magnetic signals that can be stored, transmitted, combined, compared, and otherwise manipulated in a computer system. It has been shown that it is sometimes convenient to refer to these signals as bits, values, elements, symbols, characters, items, numbers, etc., primarily for general reasons.

[0031] However, it should be remembered that all these and similar terms will be associated with appropriate physical quantities and are merely convenient notations applied to those quantities. Unless otherwise stated, as is apparent from the following discussion, it should be understood that the discussion throughout using terms such as “generate,” “write,” “include,” “store,” “transfer,” “traverse,” “associate,” “identify,” and “optimize” refers to the actions and processes of a computer system or similar electronic computing device that manipulate and convert data represented as physical (electronic) quantities in the registers and memories of the computer system into other data similarly represented as physical quantities in the computer system’s memory or registers or other such information storage, transmission, or display devices.

[0032] Some embodiments may be described in the general context of computer-executable instructions, such as program modules, that are executed by one or more computers or other devices. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. Typically, the functionality of a program module can be combined or distributed as needed in various embodiments.

[0033] Energy and spot optimization for proton therapy

[0034] The following description is presented to enable those skilled in the art to make and use embodiments of the invention; these embodiments are presented in the context of specific applications and their requirements. Those skilled in the art will readily understand various modifications to the disclosed embodiments, and the general principles defined herein can be applied to other embodiments and applications without departing from the spirit and scope of this disclosure. Therefore, the invention is not limited to the illustrated embodiments, but is accorded the widest scope consistent with the principles and features disclosed herein.

[0035] This paper describes a method and system for proton therapy planning, including proton energy and spot optimization, which uses an optimization process to discretize layers and spots. The optimization process generates an optimal distribution of layer energy and spots with a relatively smooth dose distribution, and the number and energy levels of the spots can be freely chosen. In this way, each spot can be considered its own layer and is not constrained by requirements from other spots / layers. The spots defined by this process can then be sorted into a list according to energy level / depth, and the spots can be grouped into blocks. For example, the energy level can be assigned to a block based on the average of all spots associated with that block. These blocks are then used to define the energy levels applied by the proton therapy treatment system.

[0036] Therefore, embodiments of the present invention can generate fewer layers and possibly fewer spots, thereby advantageously reducing the time required to treat patients. The optimization processes described herein, such as algorithms, can segment individual spots between different layers to avoid generating spots below a minimum energy threshold that can be delivered by the treatment system. Spots can be divided into layers such that these layers receive substantially equal intensities. For example, these spots can be divided into layers such that each layer receives substantially equal numbers of protons delivered by the proton therapy treatment system. Generally, treatment plans optimized with fewer layers result in faster delivery times. On the other hand, embodiments of the present invention can also optimize proton therapy plans for accuracy by using more spots and / or layers to better fit the target volume. Spots can be distributed at fixed intervals (e.g., 3 mm intervals) or based on variations such as beam energy and / or beam range. In all cases, the general principle is that the intensity of a layer is the sum of the intensities of all spots on a given layer.

[0037] Figure 1 A block diagram of an example computing system 100 on which embodiments described herein may be implemented is shown. In a basic configuration, system 100 includes at least one processing unit 102 and memory 104. This most basic configuration is... Figure 1The image is shown by dashed line 106. System 100 may also have additional features and / or functions. For example, system 100 may also include additional storage devices (removable and / or non-removable), including but not limited to disks, optical discs, or magnetic tapes. Such additional storage... Figure 1 The system is illustrated by removable storage device 108 and non-removable storage device 120. System 100 may also include communication connection 122, which allows the device to communicate with other devices, such as in a networked environment using a logical connection to one or more remote computers.

[0038] Figure 1 The system 100 also includes input devices 124 (such as a keyboard, mouse, pen, voice input device, touch input device). It also includes output devices 126 (such as a display device, speaker, printer).

[0039] exist Figure 1 In the example, memory 104 includes computer-readable instructions, data structures, program modules, etc. Depending on how system 100 is used, system 100 can be used to implement a planning system by executing appropriate instructions, etc., which uses an optimization algorithm (including computer-readable instructions) to discretize layers and spots to generate an optimal distribution of layer energy and spots with a relatively smooth dose distribution. The treatment planning algorithm executed by CPU 102 can freely choose the number of spots and the energy level of the spots, such that each spot can be considered as its own layer, unconstrained by the requirements of other spots / layers. Subsequently, the spots defined by the algorithm can be sorted in a list according to energy level / depth using CPU 102, and the spots can be grouped into blocks. Energy levels can be assigned to these blocks based on the corresponding spots, for example, using the average of all spots associated with that block. More generally, system 100 can be used to generate and / or optimize proton therapy treatment plans according to the present invention.

[0040] Figure 2 This is a block diagram illustrating selected components of a radiotherapy system 200 according to an embodiment of the present invention, on which selected components may be implemented. Figure 2 In the example, system 200 includes an accelerator and beam delivery system 204 for generating and / or accelerating a beam 201. Various types of beams can be generated and delivered according to embodiments of the invention, including, for example, proton beams, electron beams, neutron beams, photon beams, ion beams, or nuclear beams (e.g., using elements such as carbon, helium, or lithium). The operation and parameters of the accelerator and beam delivery system 204 are controlled such that the beam intensity, energy, size, and / or shape are dynamically modulated or controlled during the patient's treatment according to an optimized radiotherapy plan generated by system 100 as described above.

[0041] Recent radiobiological studies have demonstrated the effectiveness of delivering a complete, relatively high therapeutic radiation dose to a target within a single, short time period. This type of treatment is generally referred to herein as FLASH radiotherapy (FLASHRT). Evidence to date suggests that FLASH RT advantageously protects normal, healthy tissue from damage when tissue is exposed to only a very short time period in a single irradiation. For FLASH RT, the accelerator and beam delivery system 204 can generate a beam that can deliver at least four (4) Gy in less than one second, and up to 20 Gy or 50 Gy or more in less than one second. The control system 210 can execute a treatment plan for FLASH RT, and this plan can be generated or optimized by the system 100 executing an optimization algorithm according to an embodiment of the invention.

[0042] Nozzle 206 is used to direct the beam at various locations (targets) within the patient supported on a patient support device 208 (e.g., a chair, recliner, or table) located in the treatment room. For example, the target may be an organ, a part of an organ (e.g., a volume or region within an organ), a tumor, diseased tissue, or the patient's outline.

[0043] Nozzle 206 can be installed on the gantry ( Figure 3 The accelerator and beam delivery system 204 may be mounted on or part of the gantry structure, and the gantry structure may be movable relative to the patient support device 208, which may also be movable. In one embodiment, the accelerator and beam delivery system 204 are also mounted on or part of the gantry structure; in another embodiment, the accelerator and beam delivery system are separate from (but connected to) the gantry structure.

[0044] Figure 2 The control system 210 receives and implements a prescribed treatment plan generated and / or optimized according to embodiments of the present invention. In an embodiment, the control system 210 includes a computing system having a processor, memory, input devices (e.g., a keyboard), and may optionally have a display; Figure 1 System 100 is an example of such a platform used for control system 210. Control system 210 can receive data regarding the operation of system 200. Control system 210 can control parameters of the accelerator and beam delivery system 204, nozzle 206, and patient support device 208 based on the data received by control system 210 and according to the radiotherapy plan, including parameters such as beam energy, intensity, size and / or shape, nozzle orientation, and the position of patient support device (and patient) relative to the nozzle.

[0045] Figure 3 The illustration shows elements of a radiotherapy system 300 for treating a patient 304 according to an embodiment of the present invention. System 300 is, for example... Figure 2 An example of an implementation of a radiotherapy system 200. In this embodiment, the gantry 302 and nozzle 306 can move up and down along the length of the patient 304 and / or around the patient, and the gantry and nozzle can move independently of each other. Although in Figure 3 In the example, patient 304 is supine, but the invention is not limited to this orientation. For example, patient 304 may be seated in a chair or standing. The gantry 302 may be controlled by a treatment system using an optimized treatment plan generated according to embodiments of the invention.

[0046] about Figure 4 An example proton therapy system 400 for imaging and treating a patient 304 is described according to embodiments of the present invention. Figure 4 In the example, patient 304 is imaged using an imaging system 402, which employs, for example, X-rays, magnetic resonance imaging (MRI), and computed tomography (CT). For instance, when imaging with CT or MRI, a series of two-dimensional (2D) images are acquired from a 3D volume. Each 2D image is an image of a cross-sectional “slice” of the 3D volume. The resulting collection of 2D cross-sectional slices can be combined to create a 3D model or reconstruction of the patient's anatomical structures, such as internal organs. The 3D model will include organs of interest, which may be referred to herein as structures of interest. These organs of interest include organs targeted by radiotherapy (targets), as well as other organs that may be at risk of radiation exposure during treatment. According to some embodiments, the imaging process is separate from the treatment planning process, and the treatment planning process may include, for example, receiving imaging data from a previous imaging phase.

[0047] One purpose of 3D models is for radiotherapy planning. To develop patient-specific radiotherapy plans, information is extracted from the 3D model to determine parameters such as organ shape, organ volume, tumor shape, tumor location within the organ, and the location or orientation of several other structures of interest associated with the affected organ and any tumor. For example, a radiotherapy plan can specify how many radiation beams will be used and from what angle each beam will be delivered.

[0048] In an embodiment of the invention, an image from an image system 402 is input to a planning system 404. In this embodiment, the planning system 404 includes a computing system having a processor, memory, input devices (e.g., a keyboard), and a display. Figure 1 System 100 is an example of the platform for planned system 404.

[0049] Continue to refer to Figure 4The treatment planning system 404 executes software capable of generating an optimized treatment plan for treating patient 304. The treatment planning system 404 may receive image data generated by the image system 402 to determine constraints regarding the patient's anatomy and treatment plan parameters (such as other patient-related data and machine parameters). The treatment plan parameters are discretized into spots with defined energy levels and these spots are sorted according to their depth / energy level. The planning system 404 can optimize the treatment plan based on an optimization algorithm that determines the optimal distribution of layers with a relatively smooth dose distribution. The treatment plan can be optimized based on various specified results. For example, the treatment plan can be optimized to use fewer layers, resulting in a faster delivery time, or it can be optimized for accuracy or 3D dose uniformity by using more layers to conform to a target volume. For example, the planning system 404 may also receive user input defining the number of layers used in the optimized plan 408.

[0050] According to an embodiment of the invention, the treatment planning system 404 outputs an optimized plan 408 based on the iterative optimization algorithm 406 described herein. Spots can be distributed at fixed intervals (e.g., 3 mm spacing) or based on variations such as beam energy and / or beam range, and spots are added to a list of spots sorted according to their energy level or depth. Intensities are assigned to spots based on their energy level and / or depth / location, where the intensity of a layer is the sum of the intensities of all spots in that layer. The spots are then discretized into blocks based on energy and intensity, where each block represents a different layer. Discretizing the spots into blocks can be an iterative process, repeated until a clinical or optimization goal is achieved. The optimized plan 408 is then used to configure the treatment system 300 for, for example, performing proton therapy on a patient 304 using a gantry 302.

[0051] about Figure 5According to embodiments of the present invention, an exemplary sequence of steps for a computer implementation of automatically generating a proton therapy treatment plan is described. In step 501, the treatment plan receives treatment plan parameters, which may include patient anatomical data and machine parameters. In step 502, the treatment plan parameters are discretized into spots with defined energy levels. At this point, each spot may have an individual energy level. In step 503, spots are added to a spot list, and the list is sorted according to the energy level or depth of the spots. In step 504, an optimization algorithm is executed to produce an optimal distribution of layer energy and spots with a relatively smooth dose distribution. The spots may be distributed at fixed intervals (e.g., 3 mm spacing) or based on variations such as beam energy and / or beam range, and specifically, the distribution may be based on the energy level of the spots and / or the depth / location of the spots, with spots assigned intensities, where the intensity of a layer is the sum of the intensities of all spots in the layer. The spots are then discretized into blocks according to energy, intensity, and spot location, with each block representing a different energy layer applied by the proton therapy system. Discretizing the spots into blocks can be an iterative process, which is repeated until a clinical or optimization objective is achieved.

[0052] In step 505, an optimized treatment plan is output, for example, as a computer-readable data file. The data file can be stored in memory and used by a proton therapy system to, for example, use a gantry to fire a controlled proton beam according to the treatment plan.

[0053] According to some embodiments, the optimization algorithm also determines the optimal beam angle for clinical or optimization purposes, and generates and discretizes the speckle based on the beam angle.

[0054] about Figure 6 This paper describes an example proton therapy treatment plan 600 applied to a target volume 602 (e.g., a tumor or organ) surrounded by normal tissue 601. The treatment plan is generated using finite optimization based on the dose-volume target of the target volume 602 and the organ at risk (e.g., normal tissue 601) and machine parameters. The dose distribution is calculated according to constraints of the beam characteristics of the proton beam 604 and machine-specific dose calibration. However, Figure 6 The treatment plan shown may not utilize the full system / machine capabilities to leverage the system in the most efficient and reliable manner. Furthermore, due to machine-specific capability limitations of the combined plan parameters not considered, applying treatment plan 600 at the machine may fail or fail to achieve the optimal delivery efficiency required by the plan objectives during the treatment plan.

[0055] like Figure 6As shown, the treatment plan is constrained because it is limited to a fixed energy layer for discretizing the spots generated by the proton beam 604 to treat the target volume 602. The energy levels of the predefined layers are defined based on limited considerations of the patient's anatomy and the characteristics of the treatment device, and a scanning pattern using layer 603 is applied by the beam 604 based on these characteristics. Furthermore, using this method, the deepest layer of the target 602 receives the highest intensity, while layers closer to the surface receive significantly lower intensities, making optimization for the surface layers difficult.

[0056] In addition, using Figure 6 The method shown allows for the application of a minimum intensity to a single spot. Therefore, after optimization, if a spot's intensity is below the minimum, it must be removed from the plan to generate a machine-deliverable plan. If all spots in an energy layer are below the minimum intensity, the entire layer may need to be removed. Simple removal of spots / layers can alter the treatment plan, making the dose distribution no longer optimal. Furthermore, failure to remove these spots or layers from the treatment plan during the planning phase can lead to treatment failure, in which case treatment must be stopped and restarted after layer removal. More efficient methods involve customizing the number of layers and positioning them as needed for clinical purposes, as follows: Figure 7 As shown.

[0057] about Figure 7 This describes an exemplary optimized proton therapy treatment plan 700 applied to a target volume 702 (e.g., a tumor or organ) surrounded by normal tissue 701 for proton therapy treatment. The treatment plan 700 is initially discretized into multiple layers, as if an infinite number of layers exist, and an iterative optimization process uses these layers to distribute spots to achieve the clinical goals of the treatment plan 700 and ensures that the plan is practically deliverable by a treatment device (e.g., a gantry 302). According to some embodiments, the number of input layers is received as user input (e.g.). The optimization algorithm then places the spots in a list sorted by range / energy level and calculates the intensity (e.g., based on energy level / depth) for each spot to determine the final (e.g., optimal) distribution of layers to achieve the clinical goals of the treatment plan 700 using a proton beam 704. Figure 7As shown, the treatment plan 700 comprises six layers 703, each applying 1 / 6 of the total intensity (number of protons) of the treatment plan 700. In this way, the layer intensity is fixed, and the layer spacing is unrestricted. The principle of equal layer intensity is used to segment the spectra between layers to avoid generating spectra and layers with intensities below the minimum deliverable by the processing system. Note that the principle of equal layer intensity is used here only as an example, and other principles can be used to distribute spectra across energy layers. For example, arbitrary energy correlation functions can be designed to distribute the intensity of energy layers non-uniformly. Generally, treatment plans optimized with fewer layers result in faster delivery times. Furthermore, treatment plans optimized for accuracy tend to use more layers to better fit the target volume. The spectra can be distributed using a proton beam 704 at fixed intervals (e.g., 3 mm spacing), or they can be distributed based on variations such as beam energy and / or beam range. In either case, the layer intensity is the sum of the intensities of all spectra on a given layer.

[0058] In some embodiments, the distribution of layers and / or their energy levels are manually defined by the user. User-defined energy levels may include layers with an intensity of zero, such that no protons are delivered at certain energies, and these layers may be automatically removed by the treatment planning system after the optimization process. For example, these layers may be defined by the user at fixed or customized distances.

[0059] Embodiments of the invention have thus been described. Although the invention has been described in particular embodiments, it should be understood that the invention should not be construed as limited to these embodiments, but rather as interpreted in accordance with the appended claims.

Claims

1. A system for proton therapy, comprising: The gantry includes nozzles configured to emit a controlled proton beam; A proton therapy treatment system capable of operating to automatically control the gantry according to a treatment plan; as well as Treatment planning system, the treatment planning system comprising: Memory; and A processor operable to perform a method for generating the treatment plan, the method comprising: Receive treatment plan parameters; The number of spots and the energy level of the spots are determined based on the treatment plan parameters; The intensity of the spot is calculated based on the energy level; The spots are discretized into multiple blocks based on their location and intensity, wherein the treatment plan includes the multiple blocks, and wherein each block represents an energy layer applied by the controlled proton beam; and Output the treatment plan.

2. The system of claim 1, wherein the method further comprises treating the patient using the gantry according to the treatment plan.

3. The system of claim 1 or 2, wherein the discretization of the spot into a plurality of blocks is performed iteratively until the clinical goal is achieved.

4. The system of claim 1 or 2, wherein the method further comprises determining a plurality of angles for performing proton therapy, and wherein the determination of the number of spots and the energy level of the spots is also based on the plurality of angles.

5. The system of claim 1 or 2, wherein the method further comprises receiving a plurality of layers as user input, wherein determining the plurality of spots and the energy level of the spots is also based on the plurality of layers.

6. The system of claim 1 or 2, wherein the method further comprises sorting the spots according to depth before discretizing the spots.

7. The system of claim 1 or 2, wherein the method further comprises sorting the spots according to energy levels before discretizing the spots.

8. The system according to claim 1 or 2, wherein the energy layer comprises a fixed spacing.

9. The system according to claim 1 or 2, wherein the energy layer has a fixed total strength.

10. A method for a proton therapy treatment plan, the method comprising: Receive treatment plan parameters; The number of spots and the energy level of the spots are determined based on the treatment plan parameters; The spots are sorted based on their depth. The intensity of the spot is calculated based on the energy level; The spots are discretized into multiple blocks based on their location and intensity. as well as Generate a treatment plan, wherein the treatment plan comprises the plurality of blocks, and wherein the blocks represent an energy layer applied by a controlled proton beam.

11. The method of claim 10, further comprising controlling the gantry structure according to the treatment plan to perform particle therapy on the patient.

12. The method of claim 10 or 11, wherein the discretization of the spot into a plurality of blocks is performed iteratively until the clinical goal is achieved.

13. The method of claim 10, 11, or 12, further comprising determining a plurality of angles for performing proton therapy, wherein the determination of the number of spots and the energy level of the spots is also based on the plurality of angles.

14. The method according to any one of claims 10 to 13, further comprising receiving a plurality of layers as user input, wherein the determination of the plurality of spots and the energy level of the spots is also based on the plurality of layers.

15. The method according to any one of claims 10 to 14, wherein the energy layer comprises a fixed spacing.

16. The method according to any one of claims 10 to 15, wherein the energy layer comprises a fixed total intensity.

17. A non-transitory computer-readable storage medium in which program instructions are embedded, the program instructions, when executed by one or more processors of a device, causing the device to perform a proton therapy treatment plan, the method comprising: Receive treatment plan parameters; The number of spots and the energy level of the spots are determined based on the treatment plan parameters; The spots are sorted based on their depth. The intensity of the spot is calculated based on its relevant energy level; The spots are discretized into multiple blocks based on their location and intensity, wherein each block represents an energy layer applied during proton therapy. as well as Output a treatment plan, wherein the treatment plan comprises the plurality of blocks, and wherein the blocks represent an energy layer applied by a controlled proton beam.

18. The non-transitory computer-readable storage medium of claim 17, wherein the method further comprises automatically controlling the gantry structure to perform particle therapy on the patient according to the treatment plan.

19. The non-transitory computer-readable storage medium of claim 17 or 18, wherein the discretization of the spot into a plurality of blocks is performed iteratively until the clinical goal is achieved.

20. The non-transitory computer-readable storage medium of claim 17 or 18, wherein the method further comprises determining a plurality of angles for performing proton therapy, and wherein the determination of the number of spots and the energy level of the spots is also based on the plurality of angles.

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