A BNCT treatment planning inverse planning system

Abstract

The present application relates to the technical field of radiotherapy planning, in particular to a BNCT treatment plan reverse planning system, the system comprises selecting calibration conditions, target region and region of interest definition, boron concentration initialization, reference dose calculation and normalization, objective function construction and iteration initialization, boron concentration optimization iteration, parameter update and cycle and convergence judgment and cycle termination; the present application creatively proposes a BNCT reverse treatment plan method with biological effective dose uniformity as the target, which has significant advantages in optimization effect and clear feasibility in operation process, and shows its great prospects in reshaping the existing treatment plan paradigm and developing into a future BNCT standardized, individualized and precise treatment plan development method.

Description

Technical Field

[0001] This invention relates to the field of radiotherapy planning technology, and specifically to a BNCT treatment planning inverse planning system. Background Technology

[0002] The concept of using neutrons for radiotherapy was reported in the early 1940s. With continuous development and extensive radiobiological experiments, interest in neutron therapy has gradually increased. Neutron therapy has two branches: fast neutron therapy (FNT) and neutron capture therapy (NCT). NCT is a binary therapy that injects an isotope with a large thermal neutron absorption cross-section into the patient, some of which accumulates in the tumor area. A commonly used isotope is boron-10, so it is often referred to as boron neutron capture therapy (BNCT).

[0003] Unlike traditional radiotherapy, BNCT involves the localized deposition of high-LET particles, produced by the nuclear reaction of neutrons with matter, into the target tumor volume. These high-LET particles, such as alpha particles and Li ions, are produced by... 10 B(n,α) 7 The Li reaction is produced by a nuclear reaction in which boron atoms capture thermal neutrons. In addition to alpha particles and Li ions, there are protons from nitrogen neutron capture reactions, recoil protons from thermal neutron absorption of hydrogen in the tissue, and gamma rays from neutrons interacting with surrounding materials.

[0004] Radiotherapy typically adheres to general requirements for radiotherapy planning, such as ensuring the prescribed dose to the target area is not lower than the minimum limit and that the dose to normal tissues or organs at risk (OARs) does not exceed the maximum limit. It also requires the output of relevant irradiation parameters. Radiotherapy planning methods include forward and backward strategies. Early clinical radiotherapy practice commonly used forward planning, which calculates the dose distribution starting from the radiation source, obtains the calculation results by simulating irradiation parameter settings, and confirms the irradiation parameters by evaluating the calculation results. With technological advancements and increasingly sophisticated equipment, irradiation parameters can be flexibly adjusted to meet treatment requirements. This involves optimizing irradiation conditions backward from the lesion end; given a prescription target, the calculated parameters (irradiation parameters) are optimized and adjusted to meet the target. This approach is commonly referred to as backward planning. From a radiotherapy perspective, the core characteristic of backward planning is: using target area dose requirements and organ at risk limitations as input conditions, it automatically solves for the optimal irradiation parameters in reverse.

[0005] In current real-world BNCT clinical treatment, treatment plans are primarily developed using forward programming. Traditional BNCT treatment planning systems (such as BNCT_Rtpe, SERA, and NCTPlan) mostly employ forward programming, which calculates the dose distribution from the radiation source and then optimizes the parameters. The forward treatment planning strategy for BNCT is a trial-and-error optimization method driven by human experience. The process begins with the physicist pre-setting a set of irradiation parameters (such as beam direction, energy, flux, target size, tissue material, and boron concentration) based on experience. These parameters are input into the treatment planning system as initial conditions to calculate the corresponding physical and biological dose distribution. Subsequently, the physicist manually evaluates whether the dose result meets clinical requirements. If not, the irradiation parameters must be manually adjusted and recalculated, repeating this process until an acceptable plan is obtained. This strategy heavily relies on the physicist's experience and intuition; the resulting treatment plan is often only a locally feasible solution and cannot guarantee that it is the optimal solution among many possibilities. More importantly, the nature of forward planning means that it cannot automatically optimize irradiation parameters based on dose targets during the calculation process, thus having inherent limitations in terms of planning quality and design efficiency. This limitation severely restricts the development of BNCT technology in terms of precision, automation, and clinical application.

[0006] A review of the literature and related materials revealed that, to date, no method for inverse treatment planning has been reported in the field of BNCT treatment protocol design. Therefore, the purpose of this invention is to provide a method for generating inverse treatment plans for BNCT. This method transforms clinical requirements (such as target dose coverage, organ-at-risk tolerance dose, and target dose uniformity) into mathematical objective functions and constraints, thereby driving an optimization algorithm to automatically explore the optimal parameter configuration. Summary of the Invention

[0007] This invention proposes for the first time a reverse planning method for BNCT treatment based on nanodosimetry, with the uniform distribution of bioeffective dose as the control objective. Unlike traditional forward planning methods, this invention sets the uniformity of bioeffective dose in the tumor region as a clear optimization objective and integrates key biological factors such as RBE and CBE into the reverse optimization algorithm based on the nanodosimetry model mLNDM, thereby optimizing irradiation parameters (such as boron concentration distribution). While ensuring sufficient tumor dose coverage, it maximizes the protection of surrounding normal tissues, thus significantly improving the accuracy, safety, and planning efficiency of BNCT treatment.

[0008] The primary objective of this invention is to provide a method for reverse planning of BNCT treatment plans, the method comprising:

[0009] (1) Select calibration conditions, quantify radiation effects, and obtain nanodosimetric physical quantities based on the calculation model;

[0010] (2) Definition of target area and region of interest: Import the patient's CT images into TPS to accurately delineate the tumor target area as well as the key normal tissues and organs at risk that need to be protected;

[0011] (3) Boron concentration initialization: initialize all voxels 10 The concentration of B is initialized to a uniform preset value;

[0012] (4) Baseline dose calculation and normalization: Based on the initial boron concentration distribution obtained in step (3), the Monte Carlo method is used to perform simulation calculations to obtain the normalized dose response coefficient;

[0013] (5) Objective function construction and iterative initialization:

[0014] ① Determine the safe irradiation time: Calculate the maximum safe irradiation time based on the upper limit of the tolerated dose of key normal tissues and the normalized dose obtained in step (4);

[0015] ② Calculation of current bioeffective dose: Using the maximum safe irradiation time obtained in step ①, combined with the boron concentration of each voxel and the calculation model in step (1), the physical absorbed dose is converted into the bioeffective dose;

[0016] ③ Dose uniformity assessment: Define the objective function, the core of which is to assess the uniformity of the bioeffective dose within the tumor target area;

[0017] (6) Boron concentration optimization iteration: Based on the dose uniformity deviation calculated by the objective function, the boron concentration of each voxel in the tumor target area is automatically adjusted by the gradient descent method;

[0018] (7) Parameter update and cycle: The new boron concentration distribution calculated in step (6) is updated into the model of the treatment planning system, replacing the concentration value of the previous round. Based on the new concentration distribution, the system jumps back to step (5) to start a new round of dose calculation and objective function evaluation.

[0019] (8) Convergence judgment and loop termination: Set clear convergence criteria to terminate the iteration and output the optimal treatment plan.

[0020] Preferably, the quantification of the radiation effect described in step (1) is obtained from literature or by building an experimental platform to conduct experimental measurements.

[0021] Preferably, the calculation model in step (1) includes an RBE adaptive calculation model or a CBE adaptive calculation model, and the relevant physical quantities include one or more of the following: skin depth, target area / normal tissue in front of the target area, the position of highest neutron flux, target area / normal tissue behind the target area, target area / normal tissue behind the target area, and normal tissue behind the target area.

[0022] Preferably, the unified preset value described in step (3) is used as the benchmark starting point for subsequent optimization iterations.

[0023] Preferably, step ③ involves using a function to calculate the difference between the preset target dose distribution and the actual dose distribution calculated in the current iteration.

[0024] Preferably, the uniformity of the effective dose described in step ③ is calculated using the following method:

[0025]

[0026] in, Represents the total number of tumor voxels. Represents the effective dose prescription for the target area. Represents the bioeffective dose for each voxel in the target region. The dose distribution was considered to be sufficiently uniform.

[0027] A second objective of this invention is to provide a BNCT treatment planning backward planning system, the system comprising:

[0028] (1) Model module: Based on the thermal neutron beam parameters and nanodosimetric model, an adaptive CBE / RBE calculation model is derived to establish the conversion relationship between physical dose and biological dose;

[0029] (2) Data processing module: Reads raw dose data and preprocesses it into the physical dose and basic parameters required for calculation;

[0030] (3) Constraint module: The maximum safe irradiation time is calculated based on the normal tissue tolerance dose to ensure the safety of normal tissue;

[0031] (4) Iterative optimization module: Under the premise of fixed irradiation time, optimize the boron concentration in the target area and output the optimal treatment plan.

[0032] The beneficial effects of this invention are as follows: This invention creatively proposes a BNCT inverse treatment planning method with the goal of uniform biological effective dose. The method includes selecting calibration conditions, defining the target area and region of interest, initializing boron concentration, calculating and normalizing the baseline dose, constructing and iteratively initializing the objective function, optimizing and iterating the boron concentration, updating parameters and looping, and judging convergence and terminating the loop. The method has significant advantages in optimization effect and clear feasibility in operation process, showing great potential to reshape the existing treatment planning paradigm and develop into a standardized, individualized, and precise treatment planning method for future BNCT. Attached Figure Description

[0033] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0034] Figure 1 A Backward Planning Method for BNCT Treatment Planning Based on Nanodosimetry

[0035] Figure 2 The relationship curve between RBE / CBE and dose at a depth of 2.5 cm.

[0036] Figure 3 Baseline dose calculation and normalization

[0037] Figure 4 BNCT treatment plan reverse planning method

[0038] Note: The data in each chart is as follows, from top to bottom:

[0039] Top: Average boron concentration in the target area before update: 20 ppm; Validation dose tolerable in normal tissue: 12 Gy-Eq; Irradiation time: 1137.4393 seconds; Average bioeffective dose in the target area: 11.463 Gy-Eq; Average boron concentration in the target area after update: 50.711 ppm;

[0040] In the previous study: mean boron concentration in the target area before update: 54.6088 ppm; validated normal tissue tolerance dose: 12 Gy-Eq; irradiation time: 1176.6595 seconds; mean bioeffective dose in the target area: 18.2307 Gy-Eq; dose uniformity HI: 1.08%; mean boron concentration in the target area after update: 53.1999 ppm.

[0041] Below: Average boron concentration in the target area before update: 53.1999 ppm; Validation dose tolerable in normal tissue: 12 Gy-Eq; Irradiation time: 1174.9632 seconds; Average bioeffective dose in the target area: 18.0189 Gy-Eq; Dose evenness (HI): 0.10%; Average boron concentration in the target area after update: 53.0784 ppm; Detailed Implementation

[0042] The BNCT treatment plan inverse planning method is further described below with reference to specific embodiments.

[0043] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0044] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0045] It should also be understood that terms such as those defined in general dictionaries should be understood to have meanings consistent with their meanings in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless defined as here.

[0046] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this specification means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, and / or groups thereof.

[0047] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of those different embodiments or examples.

[0048] To facilitate understanding of the present invention, the present invention will be further explained and described below with reference to the accompanying drawings and specific embodiments. However, the specific embodiments do not constitute a limitation on the embodiments of the present invention.

[0049] Those skilled in the art should understand that the accompanying drawings are merely schematic diagrams of embodiments, and the components in the drawings are not necessarily essential for implementing the present invention.

[0050] Example 1: A method for backward planning of BNCT treatment plans

[0051] (1) According to the application scenario of the present invention, appropriate calibration conditions are selected, and the radiation effect is quantified and the relevant physical quantities of nanodosimetry are obtained simultaneously. Specifically, the determination of the BNCT radiation effect can be obtained from reliable literature or by building an experimental platform for experimental measurement. According to nanodosimetry theory, adaptive calculation models of RBE and CBE are obtained under BNCT irradiation conditions at depths of 1mm (skin), 10mm (target area / normal tissue in front of the target area), 25mm (the position with the highest neutron flux), 40mm (target area / normal tissue behind the target area), 60mm (target area / normal tissue behind the target area), and 80mm (normal tissue behind the target area), such as Figure 2 As shown.

[0052] (2) Definition of target area and region of interest

[0053] The patient's CT images are imported into TPS, where doctors or physicists can precisely delineate the tumor target area, as well as critical normal tissues and organs at risk that need to be protected.

[0054] (3) Initialization of boron concentration

[0055] All voxels 10 The B concentration is initialized to a uniform preset value. This value can serve as the baseline starting point for subsequent optimization iterations.

[0056] (4) Calculation and normalization of baseline dose

[0057] Based on the initial boron concentration distribution, a Monte Carlo simulation was performed. The core objective of this calculation was to obtain a normalized dose response coefficient. Specifically, by incorporating the inherent neutron flux trend, the simulation results were normalized to the physical absorbed dose deposited in each voxel under the conditions of "per source particle, per ppm boron concentration, and per second of irradiation time". This step established a rapid conversion basis from irradiation time and boron concentration to physical dose.

[0058] (5) Objective function construction and iterative initialization

[0059] ① Determine the safe irradiation time: Based on the upper limit of the tolerated dose of key normal tissues and the normalized physical dose obtained in step (4), calculate the maximum allowable irradiation time to ensure the safety of treatment.

[0060] ② Calculation of current bioeffective dose: Using the above irradiation time, combined with the boron concentration of each voxel and the adaptive calculation model of RBE and CBE in step (1), the physical absorbed dose is converted into the bioeffective dose.

[0061] ③ Dose Uniformity Assessment: Define an objective function whose core objective is to assess the uniformity of the effective biological dose within the tumor target area. That is, the function calculates the difference between a pre-defined target dose distribution (e.g., a uniform prescription dose within the target area) and the actual dose distribution calculated in the current iteration. The uniformity of the effective dose is calculated using the following method:

[0062]

[0063] in, Represents the total number of tumor voxels. Represents the effective dose prescription for the target area. Represents the bioeffective dose for each voxel in the target region. The dose distribution was considered to be sufficiently uniform.

[0064] (6) Boron concentration optimization iteration

[0065] Based on the dose uniformity deviation calculated using the objective function, the boron concentration of each voxel within the tumor target area is automatically adjusted using the gradient descent method. Essentially, this compensates for the non-uniformity of the dose distribution by increasing the equivalent boron concentration in low-dose regions or leveling the equivalent boron concentration in high-dose regions.

[0066] (7) Parameter update and loop

[0067] The new boron concentration distribution calculated by the optimization algorithm is updated in the treatment planning system model, replacing the concentration values ​​from the previous round. Based on the new concentration distribution, the system jumps back to step (5) to begin a new round of dose calculation and objective function evaluation.

[0068] (8) Convergence judgment and loop termination

[0069] Set explicit convergence criteria to terminate the iteration. For example, the homogeneity index of the bioeffective dose within the tumor target area can be calculated:

[0070]

[0071] When the index is below a preset threshold ( When the dose distribution is considered sufficiently uniform, the optimization process converges, and the final boron concentration distribution (as an ideal reference for the dosing regimen) and corresponding irradiation parameters are output. If the target is not met, iterative optimization continues.

[0072] Example 2: A BNCT Treatment Planning Backward Planning System

[0073] The basic algorithm logic of the BNCT treatment planning inverse programming system described in this embodiment is unique in that it handles a complex system involving the triple coupling of neutron flux, boron concentration distribution, and relative biological effects. The core logic involves establishing an adaptive CBE / RBE calculation model to calculate the safe irradiation time and optimize the boron concentration in the target region to meet the treatment dosage requirements.

[0074] A BNCT treatment planning backward planning system, comprising:

[0075] (1) Model layer: Based on the thermal neutron beam parameters and nanodosimetric model (simulating α, β parameters, cell survival curves, etc.), an adaptive CBE / RBE calculation model is derived to establish the conversion relationship between physical dose and biological dose.

[0076] (2) Data layer: Read the raw dose data and preprocess it to calculate the physical dose and basic parameters required for the calculation.

[0077] (3) Constraint layer: The safe irradiation time is calculated based on the normal tissue tolerance dose to ensure the safety of normal tissue.

[0078] (4) Iterative optimization layer: Under the premise of fixed irradiation time, optimize the boron concentration in the target area so that the biological dose in the tumor area meets the prescription requirements.

[0079] The entire algorithm achieves the core objectives of "normal tissue protection + tumor dose target achievement" in BNCT treatment. It converts physical doses into clinically relevant biological doses through a biological effect model and achieves precision treatment through boron concentration optimization.

[0080] Example 3, Application

[0081] In this embodiment, based on the method described in Embodiment 1, the thermal neutron beam flux distribution parameters based on the Lanzhou University BNCT research facility are calculated using the Monte Carlo simulation software based on TOPAS-nBio and the nanodosimetric model, and the adaptive calculation model of RBE and CBE in step (1) is applied.

[0082] Based on steps (2) and (3), a Snyder head phantom geometric model is constructed. In this model, a cubic tumor with a size of 3×3×3 cm³ is set, with a center depth of 3.5 cm, and corresponding anterior and posterior edge depths of 2 cm and 5 cm, respectively. All voxels are then... 10 The initial boron concentration was set at 20 ppm, which is close to the typical concentration in normal tissue. Based on this model, the feasibility and effectiveness of the BNCT reverse treatment planning method were preliminarily verified. In step (4) of the baseline dose calculation, the normalized boron dose was obtained as follows: Figure 3 As shown.

[0083] For step (2), the tolerance dose for normal tissue was 12.0 Gy-E, the tolerance dose for skin, and the calculated irradiation time was 1137.44 seconds initially and 1174.96 seconds iteratively optimized. Meanwhile, the study on BNCT treatment for malignant brain tumors and recurrent head and neck cancer reported in the literature (Chen, Y.-W.; Lee, Y.-Y.; Lin, C.-F.; Pan, P.-S.; Chen, J.-K.; Wang, C.-W.; Hsu, S.-M.; Kuo, Y.-C.; Lan, T.-L.; Hsu, SPC; et al. Salvage Boron Neutron Capture Therapy for Malignant Brain Tumor Patients in Compliance with Emergency and Compassionate Use: Evaluation of 34 Cases. Biology 2021, 10, 334.) showed that when at least 80% of the tumor volume received a dose of 18-25 Gy-E, the control rate could be significantly improved. Therefore, the target dose for the target area was set at 18 Gy-E, and the depth distribution of the target area boron dose and the depth distribution of CBE / RBE were iteratively optimized by combining the thermal neutron depth flux distribution curve (the highest flux point is located at a depth of 2.5 cm).

[0084] Research results are as follows Figure 4As shown, under the specific neutron flux distribution conditions of the BNCT device, the boron dose increases with increasing boron drug concentration, the CBE decreases with increasing boron dose, and the CBE is decoupled from the LET of short-range charged particles on a macroscopic scale. The optimization requirements are met when the target region boron dose exhibits a slow increasing trend from 5.15 Gy to 5.78 Gy, and the CBE distribution shows a decreasing trend from 2.94 to 2.80. At this point, the average bioeffective dose in the target region is approximately 18.02 GyE, the uniformity of the bioeffective dose distribution in the target region thickness is 0.1%, and the target region boron drug concentration distribution should increase from 39.25 ppm to 77.9 ppm in an approximately linear fashion.

[0085] In summary, this invention creatively proposes a BNCT inverse treatment planning method with the goal of achieving uniform bioeffective dose. The method includes selecting calibration conditions, defining the target area and region of interest, initializing boron concentration, calculating and normalizing the baseline dose, constructing and iteratively initializing the objective function, iteratively optimizing boron concentration, updating parameters, performing loop iterations, and determining convergence and terminating the loop. The method exhibits significant advantages in optimization effectiveness and demonstrates clear feasibility in its operational process, showcasing its immense potential to reshape the existing treatment planning paradigm and develop into a standardized, individualized, and precise treatment planning method for future BNCT procedures.

[0086] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A BNCT treatment planning inverse planning system, characterized in that, The system includes: Model module: Based on thermal neutron beam parameters and nanodosimetric model, an adaptive CBE / RBE calculation model is derived, and the conversion relationship from physical dose to biological dose is established; Data processing module: Reads raw dose data and preprocesses it into the physical dose and basic parameters required for calculation; Constraint module: Calculates the maximum safe irradiation time based on the normal tissue tolerance dose to ensure the safety of normal tissue; Iterative optimization module: Under the premise of fixed irradiation time, optimize the boron concentration in the target area and output the optimal treatment plan; The BNCT treatment plan inverse planning system described above executes the following BNCT treatment plan inverse planning method, which includes: (1) Select calibration conditions, quantify radiation effects, and obtain nanodosimetric physical quantities based on the calculation model; (2) Definition of target area and region of interest: Import the patient's CT images into TPS to accurately delineate the tumor target area as well as the key normal tissues and organs at risk that need to be protected; (3) Boron concentration initialization: initialize all voxels 10 The concentration of B is initialized to a uniform preset value; (4) Baseline dose calculation and normalization: Based on the initial boron concentration distribution obtained in step (3), the Monte Carlo method is used to perform simulation calculations to obtain the normalized dose response coefficient; (5) Objective function construction and iterative initialization: ① Determine the safe irradiation time: Calculate the maximum safe irradiation time based on the upper limit of the tolerated dose of key normal tissues and the normalized dose obtained in step (4); ② Calculation of current bioeffective dose: Using the maximum safe irradiation time obtained in step ①, combined with the boron concentration of each voxel and the calculation model in step (1), the physical absorbed dose is converted into the bioeffective dose; ③ Dose uniformity assessment: Define the objective function, the core of which is to assess the uniformity of the bioeffective dose within the tumor target area; (6) Boron concentration optimization iteration: Based on the dose uniformity deviation calculated by the objective function, the boron concentration of each voxel in the tumor target area is automatically adjusted by the gradient descent method; (7) Parameter update and cycle: The new boron concentration distribution calculated in step (6) is updated into the model of the treatment planning system, replacing the concentration value of the previous round. Based on the new concentration distribution, the system jumps back to step (5) to start a new round of dose calculation and objective function evaluation. (8) Convergence judgment and loop termination: Set clear convergence criteria to terminate the iteration and output the optimal treatment plan.

2. The BNCT treatment planning backward planning system as described in claim 1, characterized in that, The quantification of the radiation effect described in step (1) can be obtained from literature or by building an experimental platform to conduct experimental measurements.

3. The BNCT treatment planning backward planning system as described in claim 1, characterized in that, The calculation model described in step (1) includes the RBE adaptive calculation model and the CBE adaptive calculation model. The relevant physical quantities include one or more of the following: skin depth, target area / normal tissue in front of the target area, the position of the highest neutron flux, target area / normal tissue behind the target area, target area / normal tissue behind the target area, and normal tissue behind the target area.

4. The BNCT treatment planning inverse planning system as described in claim 1, characterized in that, The unified preset value mentioned in step (3) serves as the benchmark starting point for subsequent optimization iterations.

5. The BNCT treatment planning inverse planning system as described in claim 1, characterized in that, Step ③ describes the function that calculates the difference between the preset target dose distribution and the actual dose distribution calculated in the current iteration.

6. The BNCT treatment planning backward planning system as described in claim 1, characterized in that, The uniformity of the effective dose mentioned in step ③ is calculated by the following method: ， in, Represents the total number of tumor cells. Represents the effective dose prescription for the target area. Represents the bioeffective dose for each voxel in the target region. The dose distribution was considered to be sufficiently uniform.

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