A radiotherapy plan optimization method and device based on equivalent uniform dose

Abstract

The application discloses a radiotherapy plan optimization method and equipment based on equivalent uniform dose, comprising the following steps: performing pre-treatment on a case; generating individualized radiotherapy plan scoring rules according to anatomical structure information of the case; selecting a suitable biological objective function according to a target region and a normal tissue type, and setting a constraint parameter for the selected biological objective function according to the individualized radiotherapy plan scoring rules; performing flux map optimization according to the biological objective function, evaluating an optimization result, and obtaining a final dose distribution. The EUD biological objective function can fully reflect the control probability of the target region or the complication probability of the normal tissue when subjected to uneven dose distribution, and meanwhile, the situation of mutual intersection of DVH and difficulty in selecting a better plan due to dose-volume constraints can be avoided. The initial EUD value of the biological constraint is calculated through extraction of the individualized radiotherapy plan scoring rules, so that the plan quality problem caused by experience difference of a physicist can be avoided.

Description

Technical Field

[0001] This invention belongs to the field of radiotherapy technology, specifically relating to a method and equipment for optimizing radiotherapy plans based on equivalent uniform dose. Background Technology

[0002] The design process for intensity-modulated radiation therapy (IMRT) plans is highly complex. After delineating the planning target volume (PTV) and organs at risk (OARs) on the patient's CT images and determining the physical and geometric parameters related to the irradiation field, key steps include: defining optimization criteria, including the objective function and constraint parameters; using optimization algorithms; and clinical evaluation. The objective function is a crucial tool for optimizing and evaluating a treatment plan; it not only serves as a link between the output dose and input radiation parameters but also reflects the quality of the treatment plan.

[0003] Objective functions are categorized into physical objective functions and biological objective functions. Physical objective functions optimize the treatment by limiting the physical dose distribution to the target area and organs at risk; this is currently the most commonly used and mature approach. Biological objective functions, on the other hand, optimize the treatment by limiting the desired therapeutic effects, such as the probability of tumor control (TCP), the probability of normal tissue complication (NTCP), and the equivalent uniform dose (EUD). These are quantitative indicators describing the patient's quality of life after treatment and represent the highest principle and fundamental goal of treatment. TCP and NTCP can be used to convert the three-dimensional dose distribution to the biological effects on tumors and normal tissues, thereby optimizing and evaluating IMRT plans. However, these dose-effect-based objective functions are less frequently used in plan optimization, primarily due to the scarcity of radiobiological data required for radiobiological models, especially radiobiological data related to human tumor treatment.

[0004] EUD (Equivalent Dose) is a bioequivalent dose proposed by Niemierko. For anatomical structures subjected to non-uniform irradiation, the resulting radiobiological effects can be equivalent to a uniform dose distribution, which is called the EUD of the non-uniform dose distribution. EUD optimization is a method that can improve the uniformity of the dose in the tumor target area while controlling the irradiation dose to normal tissues. It has significant improvements in reducing the dose cold spot in the tumor target area and the irradiation dose to normal tissues.

[0005] However, both existing physical and biological objective functions have the following drawbacks:

[0006] 1. When using the physical objective function, for a certain tissue, there may be multiple dose-volume histograms (DVHs) that satisfy its dose-volume constraints. These DVHs often intersect each other. For a specific tissue, their values ​​may all be satisfied, but only one of them is definitely the solution that makes the plan globally optimal, so the selection is relatively difficult.

[0007] 2. The physical objective function cannot fully reflect the nonlinear effects of dose on tumors and normal tissues, especially under irregular and non-uniform dose distributions. For example, if a single or multiple volumetric matrix units within a tumor are irradiated with a very low dose, this will not have a significant impact on the IMRT plan score, but the TCP will decrease significantly due to dose cold spots.

[0008] 3. Biological objective functions based on dose-effect, such as TCP and NTCP, are rarely used in planning optimization, mainly because of the scarcity of radiobiological data required for radiobiological models, especially radiobiological data related to human tumor treatment.

[0009] 4. For EUD-based biological objective functions, the initial EUD value before optimization is generally difficult to set. It can only be roughly estimated based on the physicist's experience, or optimized once using the traditional dose-volume method, and then the EUD value is set to a reasonable level based on the optimization results. Summary of the Invention

[0010] To address the aforementioned technical problems, this invention proposes a method and device for optimizing radiotherapy plans based on equivalent uniform dose.

[0011] To achieve the above objectives, the technical solution of the present invention is as follows:

[0012] On one hand, this invention discloses a method for optimizing radiotherapy planning based on equivalent uniform dose, comprising the following steps:

[0013] Optimize the pretreatment of cases;

[0014] Based on the anatomical information of the case, generate individualized radiotherapy plan scoring rules;

[0015] Select appropriate biological objective functions based on the target area and normal tissue type, and set constraint parameters for the selected biological objective functions according to the individualized radiotherapy planning scoring rules;

[0016] Based on the above biological objective function, the flux map is optimized, the optimization results are evaluated, and the final dose distribution is obtained.

[0017] Based on the above technical solution, the following improvements can be made:

[0018] As a preferred approach, the cases undergo one or more of the following optimized pretreatments:

[0019] Automatically or manually delineate the target area and normal tissue;

[0020] Add prescriptions, set the number and direction of the radiation fields, select the dose calculation method and grid size;

[0021] Add details to auxiliary organs.

[0022] As a preferred approach, the individualized radiotherapy plan scoring rules, which "generate individualized radiotherapy plan scoring rules based on the anatomical information of the case", include one or more of the following evaluation indicators: dose to the target area, dose to organs at risk and other normal tissues, dose-volume ratio, conformity, homogeneity, and dose drop index.

[0023] As a preferred approach, "selecting an appropriate biological objective function based on the target area and normal tissue type, and setting constraint parameters for the selected biological objective function according to the individualized radiotherapy planning scoring rules" specifically includes the following steps:

[0024] Select an appropriate biological objective function based on the target area and normal tissue type;

[0025] Extract the target area and normal tissue assessment items that require additional constraints from the individualized radiotherapy planning scoring rules;

[0026] Assume that the dose distribution in the target area and normal tissues meets all the full score requirements, and that the volume within the equally spaced dose difference of each region of interest that needs to be constrained is the same;

[0027] According to Equation (1), set the characteristic parameter a for different constraints of the target area and normal tissue, and calculate the target EUD value for different characteristic parameters a;

[0028]

[0029] Where: N is the number of voxels in the region of interest, and D... i Let be the dose of the i-th individual element, and a be a characteristic parameter of the tumor or normal tissue used to describe the dose-volume effect.

[0030] As a preferred approach, appropriate biological objective functions are selected for the target region and normal tissue types based on the following methods.

[0031] The target area can be selected from one or more of Lower-gEUD, Window-gEUD, and Upper-gEUD;

[0032] For normal tissues, select Upper-gEUD;

[0033] Among them: Lower-gEUD is used to constrain low doses, Upper-gEUD is used to constrain high doses, and Window-gEUD is used to achieve the target dose-volume ratio and improve the dose uniformity of the target area.

[0034] As a preferred approach, "optimizing the flux map based on the aforementioned biological objective function, evaluating the optimization results, and obtaining the final dose distribution" specifically includes the following:

[0035] An optimization algorithm was used to optimize the intensity map of each firing field based on the added constraint parameters, and the optimization results were evaluated.

[0036] If the optimized dose distribution meets clinical requirements, proceed to the next step.

[0037] Otherwise, the field of fire and constraint parameters are adjusted based on the optimization results until the optimized dose distribution meets clinical requirements.

[0038] With the goal of optimizing the obtained flux map, a segmentation algorithm was selected for subfield segmentation and dose calculation, and the final dose distribution was evaluated.

[0039] If the final dose distribution meets clinical requirements, a radiotherapy plan is generated.

[0040] Otherwise, the field and constraint parameters are adjusted based on the assessment results until the final dose distribution meets clinical requirements.

[0041] On the other hand, the present invention also discloses a radiotherapy planning optimization device based on equivalent uniform dose, comprising:

[0042] One or more processors;

[0043] Memory;

[0044] And one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by one or more processors, the one or more programs including instructions for any of the above-described radiotherapy planning optimization methods.

[0045] This invention discloses a method and device for optimizing radiotherapy plans based on equivalent uniform dose, which has the following beneficial effects:

[0046] First, the EUD biological objective function can fully reflect the control probability of the target area or the complication probability of normal tissues when subjected to uneven dose distribution.

[0047] Second, using biological constraints can avoid the situation where DVH crossover occurs during dose-volume constraints, making it difficult to select a better plan.

[0048] Third, by extracting the dose or dose-volume reference range from the scoring items in the individualized radiotherapy planning scoring rules to calculate the initial EUD value of biological constraints, planning quality problems caused by differences in physicist experience can be avoided.

[0049] Fourth, when optimizing the physical objective function, for some normal tissues, it is usually necessary to limit multiple doses or dose-volume, and the constraint parameters are complex. In the end, the DVH may only meet the requirements on the constrained dose-volume, but the overall DVH curve is poor. However, EUD-based biological optimization can constrain the overall DVH curve, with fewer constraint parameters, and can improve the optimization efficiency and quality of radiotherapy planning. Attached Figure Description

[0050] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0051] Figure 1 A flowchart of a radiotherapy planning optimization method provided in an embodiment of the present invention.

[0052] Figure 2 The flowchart for S3 provided in the embodiment of the present invention.

[0053] Figure 3 A comparison chart of the DVH results of the optimization of biological objective function for cervical cancer cases and physical objective function provided in the embodiments of the invention.

[0054] Figure 4 A comparison chart showing the score of the optimization results of the biological objective function for cervical cancer cases and the physical objective function provided in the embodiments of the present invention. Detailed Implementation

[0055] The preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0056] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0057] Using ordinal numbers such as “first,” “second,” “third,” etc. to describe ordinary objects merely indicates different instances of similar objects and is not intended to imply that the objects being described must have a given order in time, space, sequence, or any other way.

[0058] Furthermore, the expression "includes" is an "open-ended" expression, which only means that the corresponding component exists and should not be interpreted as excluding additional components.

[0059] To achieve the objectives of this invention, some embodiments of a radiotherapy planning optimization method and apparatus based on equivalent uniform dose are provided, such as... Figure 1 As shown, the radiotherapy planning optimization method includes the following steps:

[0060] S1: Import cases into TPS and perform preprocessing optimization on the cases;

[0061] S2: Generate individualized radiotherapy planning scoring rules based on the anatomical information of the case;

[0062] S3: Select an appropriate biological objective function based on the target area and normal tissue type, and set constraint parameters for the selected biological objective function according to the individualized radiotherapy planning scoring rules;

[0063] S4: Optimize the flux map based on the above biological objective function, evaluate the optimization results, and obtain the final dose distribution.

[0064] Furthermore, in S1, the cases undergo one or more of the following optimized pretreatments:

[0065] Automatically or manually delineate the target area and normal tissue;

[0066] Add prescriptions, set the number and direction of the radiation fields, select the dose calculation method and grid size;

[0067] Add details to auxiliary organs.

[0068] Furthermore, in S2, the scoring rules for individualized radiotherapy planning include, but are not limited to, one or more of the following assessment indicators: dose to the target area, organs at risk and other normal tissues, dose-volume, conformity (CI), uniformity (HI), and dose drop index (GI).

[0069] Furthermore, such as Figure 2 As shown, S3 specifically includes the following steps:

[0070] Select an appropriate biological objective function based on the target area and normal tissue type;

[0071] The target area and normal tissue assessment items that require additional constraints are extracted from the individualized radiotherapy planning scoring rules, such as target area D95%≥100%Rx, D98%≥98%Rx, D2%≤110%Rx, Dmin≥90%Rx, etc., where Rx represents the prescription dose;

[0072] Assume that the dose distribution in the target area and normal tissues meets all the full score requirements, and that the volume within the equally spaced dose difference of each region of interest that needs to be constrained is the same;

[0073] According to Equation (1), set the characteristic parameter a for different constraints of the target area and normal tissue, and calculate the target EUD value for different characteristic parameters a;

[0074]

[0075] Where: N is the number of voxels in the region of interest, and D... i Let be the dose of the i-th individual element, and a be a characteristic parameter of the tumor or normal tissue used to describe the dose-volume effect.

[0076] EUD is a continuous function, so in a treatment plan, if 'a' takes a large positive value, the "hot spot" dose of the voxel can be reflected by the EUD value; when 'a' takes a small negative value, the EUD reflects the "cold spot" dose in the voxel; when 'a' is 1, the EUD is the arithmetic mean of the voxels.

[0077] The appropriate biological objective function for the target area and normal tissue type is selected according to the following method.

[0078] The target area can be selected from one or more of Lower-gEUD, Window-gEUD, and Upper-gEUD;

[0079] For normal tissues, select Upper-gEUD;

[0080] Among them: Lower-gEUD is used to constrain low doses, Upper-gEUD is used to constrain high doses, and Window-gEUD is used to achieve the target dose-volume ratio and improve the dose uniformity of the target area.

[0081] This invention uses a quadratic objective function based on a generalized EUD, categorized into three types: Upper-gEUD, Lower-gEUD, and Window-gEUD. Lower-gEUD and Window-gEUD are suitable for target area optimization, while Upper-gEUD is suitable for dose limiting in normal tissues. Using the EUD biological objective function effectively reflects the control probability of the target area or the complication probability of normal tissues under non-uniform dose distribution, while avoiding the difficulty in selecting a better plan due to the overlap of DVH (dose-volume-harm) interactions that occurs under dose-volume constraints.

[0082] Furthermore, S4 specifically includes the following:

[0083] An optimization algorithm was used to optimize the intensity map of each firing field based on the added constraint parameters, and the optimization results were evaluated.

[0084] If the optimized dose distribution meets clinical requirements, proceed to the next step.

[0085] Otherwise, the field of fire and constraint parameters are adjusted based on the optimization results until the optimized dose distribution meets clinical requirements.

[0086] With the goal of optimizing the obtained flux map, a segmentation algorithm was selected for subfield segmentation and dose calculation, and the final dose distribution was evaluated.

[0087] If the final dose distribution meets clinical requirements, a radiotherapy plan is generated.

[0088] Otherwise, the field and constraint parameters are adjusted based on the assessment results until the final dose distribution meets clinical requirements.

[0089] On the other hand, the present invention also discloses a radiotherapy planning optimization device based on equivalent uniform dose, comprising:

[0090] One or more processors;

[0091] Memory;

[0092] And one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by one or more processors, the one or more programs including instructions for the radiotherapy planning optimization method disclosed in any of the above embodiments.

[0093] To better understand the present invention and verify its effectiveness, a specific embodiment is described below. This embodiment uses cervical cancer cases to test the biological optimization effect, and the optimization process selects the Conjugate Gradient (CG) algorithm.

[0094] S1: Randomly select a clinically treated cervical cancer case and perform optimization preprocessing on the case. In this embodiment, the prescription dose is 45Gy / 25F. The original clinical plan was an IMRT plan with 7 fields equally divided. The dose was calculated using the Monte Carlo (MC) algorithm.

[0095] S2: Based on the anatomical information of the case, generate individualized radiotherapy plan scoring rules using the "A method and device for evaluating radiotherapy plans based on unsupervised learning" disclosed in CN 114566251 A;

[0096] S3: Select an appropriate biological objective function based on the target area and normal tissue type, and set constraint parameters for the selected biological objective function according to the individualized radiotherapy planning scoring rules;

[0097] S4: Optimize the flux map based on the above biological objective function, evaluate the optimization results, and obtain the final dose distribution.

[0098] Furthermore, in S3, a physical objective function is appropriately added to the target area to optimize the hybrid objective function, resulting in better optimization performance.

[0099] For organs and other normal tissues, Upper-gEUD is used for optimization. For serial organs or tissues that need to limit the maximum dose, the characteristic parameter 'a' is taken as a large positive integer, such as 30 to 50. For parallel organs or tissues that need to limit the average dose or the overall DVH curve, the characteristic parameter 'a' is taken as a small positive integer, such as 1 or 2.

[0100] For the target area, Lower-gEUD is used to constrain the cold point of the dose, in which case the characteristic parameter 'a' takes a small negative integer, such as -50 to -30. Window-gEUD is used to constrain the average dose, with the characteristic parameter 'a' taking a small positive integer, such as 1. Alternatively, Upper-gEUD can be used to appropriately constrain the high dose in the target area.

[0101] Extract the region of interest assessment items that need to be constrained from the individualized radiotherapy planning scoring rules, such as: target area D95%≥100%Rx, D98%≥98%Rx, D2%≤110%Rx, Dmin≥90%Rx, etc. Assuming that the dose distribution of the target area and normal tissue meets the full score requirements of each item, and that the volume within the equally spaced dose difference of each region of interest that needs to be constrained is the same, calculate the target EUD value for different characteristic parameters a.

[0102] Furthermore, in S4, the CG algorithm is used to optimize the intensity map of each firing field based on the added constraints, and the optimization results are evaluated.

[0103] If the optimized dose distribution meets clinical requirements, proceed to the next step.

[0104] Otherwise, the firing field and constraints are adjusted based on the optimization results until the optimized dose distribution meets clinical requirements.

[0105] With the goal of optimizing the obtained flux map, a segmentation algorithm was selected for subfield segmentation and dose calculation, and the final dose distribution was evaluated.

[0106] If the final dose distribution meets clinical requirements, a radiotherapy plan is generated.

[0107] Otherwise, the firing field and constraint conditions are adjusted based on the assessment results until the final dose distribution meets clinical requirements.

[0108] The differences in the final program quality between biological objective function optimization and physical objective function optimization are compared, and the results are as follows: Figure 3 , 4 As shown. For parallel organs, such as the rectum and bladder, optimization using biological objective functions can achieve better constraint effects with fewer constraint terms. Target area biological objective function optimization can improve the dose cold point and dose uniformity within the target area, but without physical constraints, the conformity of the target area will be worse than when using physical objective functions for optimization. Overall, combining biological and physical objective functions can significantly improve the planning optimization effect.

[0109] In summary, the radiotherapy planning optimization method and equipment based on equivalent uniform dose disclosed in this invention have the following beneficial effects:

[0110] First, the EUD biological objective function can fully reflect the control probability of the target area or the complication probability of normal tissues when subjected to uneven dose distribution.

[0111] Second, using biological constraints can avoid the situation where DVH crossover occurs and it is difficult to select a better plan, which is the case with dose-volume constraints.

[0112] Third, by extracting the dose or dose-volume reference range from the scoring items in the individualized radiotherapy planning scoring rules to calculate the initial EUD value of biological constraints, planning quality problems caused by differences in physicist experience can be avoided.

[0113] Fourth, when optimizing the physical objective function, for some normal tissues, it is usually necessary to limit multiple doses or dose-volume, which is a complex constraint. The final DVH may only meet the requirements on the constrained dose-volume, but the overall DVH curve is poor. However, EUD-based biological optimization can constrain the overall DVH curve with fewer constraints and can improve the optimization efficiency and quality of radiotherapy planning.

[0114] It should be understood that the various techniques described herein can be implemented in combination with hardware or software, or a combination thereof. Thus, the methods and apparatus of the present invention, or certain aspects or portions thereof, can take the form of program code (i.e., instructions) embedded in a tangible medium, such as a floppy disk, CD-ROM, hard disk, or any other machine-readable storage medium, wherein when the program is loaded into and executed by a machine such as a computer, that machine becomes an apparatus for practicing the present invention.

[0115] The above embodiments are only for illustrating the technical concept and features of the present invention, and are intended to enable those skilled in the art to understand the content of the present invention and implement it. They should not be used to limit the scope of protection of the present invention. All equivalent changes or modifications made in accordance with the spirit and essence of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A method for optimizing radiotherapy planning based on equivalent uniform dose, characterized in that, Includes the following steps: Optimize the pretreatment of cases; Based on the anatomical information of the case, generate individualized radiotherapy plan scoring rules; Based on the target area and normal tissue type, a suitable biological objective function is selected, and constraint parameters are set for the selected biological objective function according to the individualized radiotherapy planning scoring rules. This specifically includes the following steps: Select an appropriate biological objective function based on the target area and normal tissue type; Extract the target area and normal tissue assessment items that require additional constraints from the individualized radiotherapy planning scoring rules; Assume that the dose distribution in the target area and normal tissues meets all the full score requirements, and that the volume within the equally spaced dose difference of each region of interest that needs to be constrained is the same; According to Equation (1), set the characteristic parameter a of different constraints on the target area and normal tissue, and calculate the target EUD value corresponding to different characteristic parameters a; （1） Where: N is the number of voxels in the region of interest. Let be the dose of the i-th individual element, and a be a characteristic parameter of the tumor or normal tissue used to describe the dose-volume effect; The appropriate biological objective function for the target area and normal tissue type is selected according to the following method. The target area can be selected from one or more of Lower-gEUD, Window-gEUD, and Upper-gEUD; For normal tissues, select Upper-gEUD; Among them: Lower-gEUD is used to constrain low doses, Upper-gEUD is used to constrain high doses, and Window-gEUD is used to achieve the target dose-volume ratio and improve the dose uniformity of the target area. Based on the above biological objective function, the flux map is optimized, the optimization results are evaluated, and the final dose distribution is obtained.

2. The radiotherapy planning optimization method according to claim 1, characterized in that, Perform one or more of the following optimized pretreatments on the cases: Automatically or manually delineate the target area and normal tissue; Add prescriptions, set the number and direction of the radiation fields, select the dose calculation method and grid size; Add details to auxiliary organs.

3. The radiotherapy planning optimization method according to claim 1, characterized in that, The individualized radiotherapy planning scoring rules, which generate individualized radiotherapy planning scoring rules based on the anatomical information of the case, include one or more of the following assessment indicators: dose to the target area, organs at risk and other normal tissues, dose-volume, conformity, homogeneity, and dose drop index.

4. The radiotherapy planning optimization method according to claim 1, characterized in that, "Optimize the flux map based on the above biological objective function, evaluate the optimization results, and obtain the final dose distribution" specifically includes the following: An optimization algorithm was used to optimize the intensity map of each firing field based on the added constraint parameters, and the optimization results were evaluated. If the optimized dose distribution meets clinical requirements, proceed to the next step. Otherwise, the field of fire and constraint parameters are adjusted based on the optimization results until the optimized dose distribution meets clinical requirements. With the goal of optimizing the obtained flux map, a segmentation algorithm was selected for subfield segmentation and dose calculation, and the final dose distribution was evaluated. If the final dose distribution meets clinical requirements, a radiotherapy plan is generated. Otherwise, the field and constraint parameters are adjusted based on the assessment results until the final dose distribution meets clinical requirements.

5. A radiotherapy planning optimization device based on equivalent uniform dose, characterized in that, include: One or more processors; Memory; And one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by one or more processors, the one or more programs including instructions for the radiotherapy planning optimization method according to any one of claims 1-4.

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