A coupling method between microdosimetry model and Monte Carlo neutron transport model

Abstract

A method for coupling a microdosimetry model with a Monte Carlo neutron transport model comprises the following steps: conducting an in vitro cell survival experiment to obtain experimental data; establishing a microdosimetry model based on microdosimetry and experimental data, and correcting the influence of overkill effect, dose rate effect and intracellular boron distribution heterogeneity on the microdosimetry model; calculating the physical absorption dose through a Monte Carlo transport model; and coupling the microdosimetry model with the Monte Carlo transport to calculate the biological effective dose. The present invention establishes a set of RBE models suitable for BNCT based on microdosimetry, greatly improves the calculation accuracy and speed, and realizes the coupling calculation of the microdosimetry model with the Monte Carlo transport model to calculate the biological effective dose.

Description

Technical Field

[0001] The present invention relates to the field of BNCT diagnosis and treatment, and in particular to a method for coupling a microdosimetry model with a Monte Carlo neutron transport model. Background Art

[0002] BNCT technology has become a new hot spot in particle therapy research and development and one of the important options for future tumor radiotherapy because of its ability to accurately and efficiently treat cancer. Physical absorption dose is an important parameter output by the Treatment Planning System (TPS). It can be used to estimate the degree of radiation damage to tissues and organs, as well as to evaluate the effectiveness and safety of radiation therapy. The Monte Carlo transport model has wide practicability, controllable accuracy and parallel computing capabilities, so the physical absorption dose of TPS is generally calculated using the Monte Carlo transport model.

[0003] However, in BNCT treatment, the biological effective dose is usually used instead of the physical absorption dose to design the treatment plan. The biological effective dose is defined as the product of the physical absorption dose and the relative biological effectiveness (RBE), while RBE is defined as the ratio of the gamma-ray physical absorption dose required to achieve the same biological endpoint to the physical absorption dose of each BNCT, which can achieve the unified quantification of the dose of different radiation fields. The introduction of RBE reduces the complexity of the prescription dose of the tumor target area and the dose limit of normal tissues and organs in BNCT treatment on the one hand, and on the other hand, it provides the possibility of drawing on the reliable experience of photon radiotherapy in BNCT treatment. The radiation field of BNCT is a mixed radiation field, which mainly includes boron dose, nitrogen dose, hydrogen dose and photon dose. The relative biological effect (RBE) is an extremely important parameter in BNCT treatment. Accurate calculation of RBE is an important prerequisite for achieving precise BNCT treatment.

[0004] In the clinical treatment of BNCT, the accuracy of dose calculation is very important. The dose expression of BNCT can be divided into physical absorption dose and biological effective dose. The biological effective dose is defined as the product of relative biological effect (RBE) and physical absorption dose, which is an important factor in evaluating clinical treatment. The traditional method of calculating the biological effective dose of BNCT is to calculate the physical absorption dose of each dose component separately, multiply it by the corresponding RBE and sum it, so it is called RBE weighted dose. The simple use of RBE weighted dose ignores the synergistic effect of each dose component on the therapeutic effect, and the influencing factors of RBE are complex, so a fixed value should not be used. Sara et al. estimated the biological effective dose of brain tumors and skin melanoma on the clinical target area, and found that the dose obtained by the fixed value RBE calculation method was greater than or less than the actual dose. The particles produced by BNCT have a higher RBE. Unlike conventional photon radiotherapy, the dose output by TPS should be the biological effective dose rather than the physical absorption dose. Therefore, it is urgent to establish an accurate biophysical model and couple it with the Monte Carlo transport model to complete the biological effective dose calculation of TPS.

[0005] The Microdosimetric Kinetic Model (MK) is one of the most widely used RBE models with the most clinical experience in recent years, and has rich research experience in ion beam therapy. The MK model was proposed by Hawkins and is mainly based on microdosimetry theory. Before applying the MK model to calculate RBE, the corresponding microdose line energy spectrum must be obtained. The accuracy of the microdose line energy spectrum directly determines the accuracy of RBE calculation. Dai Tianyuan et al. applied the MK model to heavy ion radiotherapy. The calculation results showed that the biological effective dose calculated based on the MK model was consistent with the biological effective dose in the carbon ion treatment planning system. Kase et al. have now applied the MK model to the National Institute of Radiological Medicine (NIRS) and Chiba Carbon Ion Therapy Device (HIMAC) in Japan. In 2014, Japanese inventors tried to apply this theory to the field of BNCT research, and subsequently developed the SMK model, which took into account the dose heterogeneity, overkill effect and dose rate effect that occurred during BNCT radiotherapy. However, the model has not yet been applied to the BNCT diagnosis and treatment planning system. Summary of the invention

[0006] In order to overcome the shortcomings of the prior art, the present invention proposes a coupling method of a microdosimetry model and a Monte Carlo neutron transport model to solve the problems related to biological effective dose calculation in the BNCT diagnosis and treatment planning system.

[0007] The technical solution of the present invention is implemented as follows: a method for coupling a microdosimetry model with a Monte Carlo neutron transport model comprises the steps of:

[0008] S1, perform in vitro cell survival experiments and obtain experimental data;

[0009] S2, based on microdosimetry and experimental data, a microdosimetry model is established, and the effects of overkill effect, dose rate effect and intracellular boron distribution heterogeneity on the microdosimetry model are corrected;

[0010] S3, calculation of physical absorbed dose by Monte Carlo transport model;

[0011] S4, coupling microdosimetry model with Monte Carlo transport to calculate biological effective dose.

[0012] Furthermore, step S1 includes the steps of

[0013] S11, G422 cells and CNE-2 cells were added to the culture medium;

[0014] S12, the culture medium was placed in an incubator at 37°C and 5% atmospheric CO2 to maintain saturated humidity;

[0015] S13, preparing BPA and novel boron drug solution;

[0016] S14, made into cell suspension;

[0017] S15, calculation of intracellular boron concentration;

[0018] S16, cell irradiation experiments using the vehicle-mounted neutron source X-TANS;

[0019] S17, monitor cell apoptosis rate, determine cell growth curve, and calculate cell survival fraction;

[0020] S18, perform data statistical analysis to obtain experimental data.

[0021] Further, in said S2, based on microdosimetry and according to experimental data, a microdosimetry model is established, comprising the steps of:

[0022] S21, Monte Carlo simulation is performed to solve the corresponding microdosimetry parameters under the experimental conditions in S1;

[0023] S22, designing an optimization algorithm, combining the microdosimetric parameters obtained in S21, and solving the microdosimetric model parameters corresponding to the model under experimental conditions;

[0024] S23, calculation and verification of the microdosimetry model.

[0025] Furthermore, the calculation and verification of the microdosimetry model in S23 includes the steps of: outputting biological doses and relative biological effects at different positions based on the microdosimetry model, and comparing and verifying them with the experimental data in S1.

[0026] Furthermore, the correction of the influence of overkill effect, dose rate effect and intracellular boron distribution heterogeneity on the microdosimetry model in S2 includes the steps of: introducing a saturation correction parameter in the microdosimetry model to correct the influence of the overkill effect; introducing a dose rate constant and a time factor in the microdosimetry model to correct the influence of the dose rate effect; determining the distribution ratio of different boron drugs in the organelles through the experiment in S1, and then calculating the process parameters of the microdosimetry model in the calculation process according to the cell matrix simulation, generating process data when using different boron drugs, and correcting the influence of boron distribution heterogeneity on the microdosimetry model.

[0027] Furthermore, the step S3 includes the steps of

[0028] S31, reads DICOM format and converts it into a geometric model that can be read by MCX itself;

[0029] S32, after calculation using the Monte Carlo transport model, outputs four BNCT dose results: boron dose, hydrogen dose, nitrogen dose and photon dose.

[0030] Furthermore, the S4 comprises the steps of:

[0031] S41, read the dose results and relative deviations corresponding to the four doses of BNCT: boron dose, hydrogen dose, nitrogen dose and photon dose;

[0032] S42, calculate the specific energy of the four doses, multiply them with the corresponding four doses and take the weighted average to obtain the specific energy parameters under the weight of the four doses, and then input them into the microdosimetry model, and the microdose model calculates the biological effective dose; calculate the relative deviations of the four doses, multiply them with the corresponding relative deviations of the four doses and take the weighted average to obtain the specific energy parameters under the weight of the relative deviations of the four doses, and then input them into the microdosimetry model, and the microdose model calculates the biological effective dose deviation.

[0033] Furthermore, the S4 also includes the step of generating a DVH and a dose depth curve.

[0034] Furthermore, the calculation and verification of the microdosimetry model in S23 also includes the steps of: comparing and verifying the DVH and biological effective dose obtained by coupling with MCX with the experimental data in S1.

[0035] The beneficial effect of the present invention is that, compared with the prior art, the present invention establishes a set of RBE models suitable for BNCT based on microdosimetry, which greatly improves the calculation accuracy and speed, and realizes the coupling calculation of the microdosimetry model and the Monte Carlo transport model to calculate the biological effective dose. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1It is a schematic flow chart of a method for coupling a microdosimetry model with a Monte Carlo neutron transport model of the present invention;

[0037] Figure 2 It is a schematic diagram of the in vitro cell survival experiment process of the present invention;

[0038] Figure 3 It is a schematic diagram of the flow of calculating physical absorbed dose using the Monte Carlo transport model in the present invention. DETAILED DESCRIPTION

[0039] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0040] See also Figure 1 The present invention provides a method for coupling a microdosimetry model with a Monte Carlo neutron transport model, comprising the steps of:

[0041] S1, perform in vitro cell survival experiments and obtain experimental data;

[0042] S2, based on microdosimetry and experimental data, a microdosimetry model is established, and the effects of overkill effect, dose rate effect and intracellular boron distribution heterogeneity on the microdosimetry model are corrected;

[0043] S3, calculation of physically absorbed dose by Monte Carlo transport model; and

[0044] S4, coupling microdosimetry model with Monte Carlo transport to calculate biological effective dose.

[0045] See also Figure 2, step S1 performs an in vitro cell survival experiment to provide data support for the establishment of the relative biological effect (RBE) model; CNE-2 cells are a human nasopharyngeal carcinoma cell line, which is often used in research and related studies in the laboratory. This cell line was first established in 1981 from the lymph node metastasis of a human nasopharyngeal carcinoma patient. CNE-2 cells have the characteristics of rapid proliferation, easy culture and high metastatic ability, so they are widely used in studying the pathogenesis, treatment methods and drug screening of nasopharyngeal carcinoma. G422 glioma cells are a human glioma cell line, which are often used to study the pathogenesis, treatment methods and drug screening of gliomas. In order to study the irradiation effect of BNCT of G422 cells and CNE-2 cells, the following group experiments were performed. As the experimental group, tumor cells incubated in boron-containing culture medium (BPA, BSH) for 12 hours were irradiated with neutron sources for different times, so that the absorbed doses obtained by the cells were 4Gy and 8Gy respectively. A gamma ray control group was set up so that the cells received the same absorbed dose as the experimental group; a neutron ray control group was set up, and the neutron source irradiated the cell samples without boron, and the irradiation time was the same as the experimental group; a no-radiation control group was set up.

[0046] Step S2 is based on microdosimetry to establish a relative biological effect (RBE) model, and considers the overkill effect, dose rate effect and intracellular boron distribution heterogeneity. The overkill effect refers to the phenomenon that when the dose rate or linear energy transfer (LET) of radiation is too high, the killing effect on cancer cells is reduced. This effect can be considered by introducing a saturation correction parameter in the microdosimetry model. The dose rate effect refers to the effect of changes in radiation dose rate on biological effects during radiotherapy. The radiation effect is small at low dose rates and more significant at high dose rates. Introducing a dose rate constant (which can be corrected by experimental fitting) in the microdosimetry model and introducing a time factor can consider the dose rate effect caused by irradiation time. Boron distribution heterogeneity refers to the difference in the distribution of different boron drugs in tissue cells. First, the distribution ratio of different boron drugs in organelles is determined experimentally, and then the process parameters of the model in the calculation process can be calculated based on the cell matrix simulation, thereby generating process data when using different boron drugs.

[0047] The steps to establish the relative biological effect (RBE) model include:

[0048] S21, Monte Carlo simulation is performed to solve the corresponding microdosimetry parameters under the experimental conditions in S1;

[0049] S22, design an optimization algorithm, combine the microdosimetry parameters obtained in S21, and solve the microdosimetry model parameters corresponding to the model under experimental conditions;

[0050] S23, calculation and verification of the microdosimetry model.

[0051] In step S23, there are two methods for calculating and verifying the microdosimetry model: one method is to establish a relative biological model, and then output the biological dose and relative biological effect at different positions based on the model, which can be compared and verified with the experiment in S1; the other method is to compare and verify the DVH and biological effective dose obtained by coupling with MCX with the experiment.

[0052] In step S3, the Monte Carlo transport model calculates the physical absorbed dose. The Monte Carlo transport model selected in one embodiment of the present invention is a Monte Carlo particle transport calculation program independently developed by the Nuclear Engineering Computational Physics Laboratory NECP of Xi'an Jiaotong University. It is a Monte Carlo-deterministic coupling program with independent intellectual property rights. It uses the most advanced theoretical model to achieve high-fidelity neutron-photon coupled transport calculations. MCX adopts advanced CADIS and FW-CADIS theories, supports automatic variance reduction function, and can improve the efficiency of Monte Carlo calculations by hundreds or thousands of times. The MCX calculation process is as follows: Figure 3 As shown. MCX can read DICOM format and convert it into a geometric model that MCX itself can read. When performing simulation calculations, MCX requires the user to provide the radiation source, geometric material and boron concentration. After calculations by the Monte Carlo transport model, four BNCT dose results can be output: boron dose, hydrogen dose, nitrogen dose and photon dose.

[0053] In step S4, a microdosimetry model and Monte Carlo transport coupling calculation are performed, including the following steps:

[0054] S41, read the dose results and relative deviations corresponding to the four doses of BNCT: boron dose, hydrogen dose, nitrogen dose and photon dose;

[0055] S42, calculate the specific energy of the four doses, multiply them with the corresponding four doses and take the weighted average to obtain the specific energy parameters under the weight of the four doses, and then input them into the microdosimetry model, and the microdose model calculates the biological effective dose; calculate the relative deviations of the four doses, multiply them with the corresponding relative deviations of the four doses and take the weighted average to obtain the specific energy parameters under the weight of the relative deviations of the four doses, and then input them into the microdosimetry model, and the microdose model calculates the biological effective dose deviation.

[0056] Specific energy is a key parameter in microdosimetry (microdosimetry parameters under experimental conditions were obtained through S21 calculation), which indicates the energy deposition per unit mass at the micrometer scale. The microdosimetry model calculates the specific energy of four doses in advance, and then multiplies them with the corresponding four doses and weighted averages them to obtain the specific energy parameters under the weighted four doses. Then, the biological dose can be solved by inputting them into the microdosimetry model. The solution process of the relative deviation of the biological effective dose is similar to the calculation process of the biological effective dose.

[0057] In order to facilitate the calculation of the microdosimetry model, the present invention can accurately read the dose file format output by MCX in S3 and use it as input to calculate the biological effective dose. The principle of DVH acquisition is to divide the irradiated tissue into many small voxels (volume elements) through the dose calculation algorithm, and then calculate the dose of each voxel and count the number of voxels receiving a given dose range; the dose depth curve is to count the dose distribution at different depths in a certain direction. When the biological effective dose and biological effective dose deviation are calculated, the DVH and dose depth curve can be generated through the program post-processing module.

[0058] DVH is the abbreviation of Dose-Volume Histogram. It is a graphical representation method used to describe the dose distribution of the target area and normal tissue in the radiotherapy plan. DVH shows the volume percentage of the target area or tissue at different dose levels. By analyzing DVH, doctors can evaluate the coverage of the target area by the radiotherapy plan and the dose limitation of normal tissue. DVH analysis helps to optimize the treatment plan to ensure that the target area is adequately covered by the dose while minimizing the side effects on normal tissue.

[0059] The Dose-Dose Curve is a curve that describes how radiation dose varies with depth. It is obtained by measurement or calculation and is used to understand the distribution of radiation dose in tissues. The Dose-Dose Curve is critical to determining appropriate radiation doses and treatment plans. By analyzing the Dose-Dose Curve, doctors can evaluate the dose coverage of the target area and predict the dose limitations of normal tissues, thereby optimizing the treatment plan to ensure that the target area receives sufficient dose while minimizing side effects on normal tissues.

[0060] In order to solve the problems related to the complexity of the influencing factors of the relative biological effect of BNCT and slow calculation, the present invention realizes the accurate calculation of the biological effective dose of the BNCT treatment planning software by coupling the output of the Monte Carlo calculation program MCX with the input of the microdosimetry model, and greatly reduces the calculation time.

[0061] The present invention sets up multiple control groups through S1, analyzes the biological effects of boron-containing cells and non-boron-containing cells under neutron irradiation, and provides data support for cell experiments for boron neutron capture therapy (BNCT) by comparing the differences in cell survival scores.

[0062] The post-processing module of the present invention can output DVH and dose depth curves. DVH and dose depth curves are the main indicators that doctors pay attention to when making radiotherapy plans. They can help doctors understand the distribution of tissues and optimize treatment plans. In order to facilitate doctors to analyze the results more intuitively, the present invention has developed a post-processing module based on microdosimetry output, which can realize the DVH and dose depth curve functions.

[0063] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for coupling a microdosimetry model with a Monte Carlo neutron transport model, characterized in that: Included steps S1, perform in vitro cell survival experiments and obtain experimental data; S2, based on microdosimetry and experimental data, establish a microdosimetry model, including steps S21, Monte Carlo simulation is performed to solve the corresponding microdosimetry parameters under the experimental conditions in S1; S22, designing an optimization algorithm, combining the microdosimetric parameters obtained in S21, and solving the microdosimetric model parameters corresponding to the model under experimental conditions; S23, calculating and verifying the microdosimetry model, including the steps of: outputting biological doses and relative biological effects at different positions based on the microdosimetry model, and comparing and verifying with the experimental data in S1; Correcting the influence of overkill effect, dose rate effect and intracellular boron distribution heterogeneity on the microdosimetry model, including the steps of: introducing a saturation correction parameter in the microdosimetry model to correct the influence of the overkill effect; introducing a dose rate constant and a time factor in the microdosimetry model to correct the influence of the dose rate effect; determining the distribution ratio of different boron drugs in the organelles through the experiment in S1, and then calculating the process parameters of the microdosimetry model in the calculation process according to the cell matrix simulation, generating process data when using different boron drugs, and correcting the influence of boron distribution heterogeneity on the microdosimetry model; S3, calculate the physical absorbed dose by Monte Carlo transport model, including the following steps: S31, reads DICOM format and converts it into a geometric model that can be read by MCX itself; S32, after calculation by Monte Carlo transport model, outputs four dose results of BNCT: boron dose, hydrogen dose, nitrogen dose and photon dose; S4, coupling the microdosimetry model with Monte Carlo transport to calculate the biological effective dose, including the following steps: S41, read the dose results and relative deviations corresponding to the four doses of BNCT: boron dose, hydrogen dose, nitrogen dose and photon dose; S42, calculate the specific energy of the four doses, multiply them with the corresponding four doses and take the weighted average, to obtain the specific energy parameters under the weight of the four doses, then input them into the microdosimetry model, and the microdose model calculates the biological effective dose; calculate the specific energy of the relative deviations of the four doses, multiply them with the corresponding relative deviations of the four doses and take the weighted average, to obtain the specific energy parameters under the weight of the relative deviations of the four doses, then input them into the microdosimetry model, and the microdose model calculates the biological effective dose deviation.

2. The method for coupling a microdosimetry model with a Monte Carlo neutron transport model according to claim 1, characterized in that: Step S1 includes the steps S11, G422 cells and CNE-2 cells were added to the culture medium; S12, the culture medium was placed in an incubator at 37°C and 5% atmospheric CO2 to maintain saturated humidity; S13, preparing BPA and novel boron drug solution; S14, made into cell suspension; S15, calculation of intracellular boron concentration; S16, cell irradiation experiments using a vehicle-mounted neutron source; S17, monitor cell apoptosis rate, determine cell growth curve, and calculate cell survival fraction; S18, perform data statistical analysis to obtain experimental data.

3. The method for coupling a microdosimetry model with a Monte Carlo neutron transport model according to claim 1, characterized in that: The S4 further comprises the step of generating a DVH and a dose depth curve.

4. The method for coupling a microdosimetry model with a Monte Carlo neutron transport model as claimed in claim 3, characterized in that: The calculation and verification of the microdosimetry model in S23 also includes the steps of: comparing and verifying the DVH and biological effective dose obtained by coupling calculation with MCX with the experimental data in S1.

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