Method, terminal and medium for obtaining total relative biological effect value based on boron neutron reaction

Abstract

The present invention provides a method, terminal and medium for obtaining a relative total biological effect value based on a boron neutron reaction. The method comprises obtaining a cell survival fraction model and a reference model corresponding to each target depth; obtaining, for each target depth, a mixed absorbed dose and a reference absorbed dose corresponding to the cell survival fraction to be measured according to the cell survival fraction to be measured; and obtaining a relative total biological effect value of the mixed absorbed dose at the corresponding target depth based on the mixed absorbed dose and the reference absorbed dose corresponding to each target depth. The present invention improves the accuracy of obtaining the cell survival fraction model while effectively improving the accuracy of obtaining the relative total biological effect value.

Description

Technical Field

[0001] The present invention relates to the field of medical physics technology, and in particular to a method, a terminal and a computer storage medium for obtaining a relative total biological effect value based on a boron neutron reaction. Background Art

[0002] In the current process of formulating boron neutron capture therapy (BNCT) plans / schemes, the following equivalent equation is usually used to obtain the equivalent photon dose to the tumor target and organs at risk:

[0003] D T =CBE B ×D B +RBE N ×D N +RBE H ×D H +RBE γ ×D γ

[0004] Among them, D B 、D N 、D H are the doses caused by the reaction of neutrons with boron, nitrogen and hydrogen in the human body, namely the boron dose, nitrogen dose and hydrogen dose respectively, D γ It is the sum of the dose caused by gamma rays produced by hydrogen capturing neutrons in the human body and the dose caused by gamma rays contained in the neutron source, that is, the photon dose.

[0005] In actual treatment, the relative biological effectiveness (RBE) is often used to convert physical dose into biological dose. This is the ratio of the dose required to induce a specific biological effect from a 250 keV X-ray or gamma ray to the dose required to induce the same biological effect from the observed ionizing radiation. Because neutrons are gradually slowed down as they penetrate human tissue, the RBE value corresponding to tumors at different depths varies accordingly.

[0006] In the prior art, the RBE value for the mixed absorbed dose is typically obtained based on biological experiments in neutron source reactors, and its accuracy is often low. In this regard, in the prior art, there is already a method for obtaining the total RBE value corresponding to the mixed absorbed dose based on a cell survival fraction model. However, the cell survival fraction models currently used often utilize existing empirical models or experimental models, and their model distribution differs significantly from the actual distribution of cell survival fraction at the target depth, resulting in low model accuracy. This in turn reduces the accuracy of the equivalent photon dose value obtained based on the model and makes it difficult to estimate. Summary of the Invention

[0007] In view of the shortcomings of the prior art described above, the present invention aims to provide a method, terminal, and computer storage medium for obtaining a cell survival fraction model based on boron neutron reactions, which can address the poor accuracy of existing cell survival fraction models. To achieve the above and other related objectives, the present invention provides, in a first aspect, a method for obtaining a cell survival fraction model based on different target depths, characterized by comprising:

[0008] A cell survival fraction model and a reference model corresponding to each target depth are obtained; wherein the reference model is a cell survival fraction model corresponding to gamma rays; for each target depth, a mixed absorbed dose and a reference absorbed dose corresponding to the cell survival fraction to be measured are obtained respectively according to the cell survival fraction to be measured; based on the mixed absorbed dose and the reference absorbed dose corresponding to each target depth, a total relative biological effect value of the mixed absorbed dose at the corresponding target depth is obtained.

[0009] In some embodiments of the first aspect of the present invention, the total relative biological effect value of the mixed absorbed dose at the corresponding target depth is obtained based on the mixed absorbed dose corresponding to each target depth and the reference absorbed dose, which is:

[0010] RBE 总 =D0 / D1

[0011] Among them, RBE 总 is the total relative biological effect value at the target depth; D1 is the mixed absorbed dose value; D0 is the reference absorbed dose value.

[0012] In some embodiments of the first aspect of the present invention, a method for obtaining the cell survival fraction model corresponding to each target depth includes:

[0013] Based on the fitting sample pairs at each target depth, the model parameters to be fitted in the initial cell survival fraction model are solved respectively to obtain the cell survival fraction model at each target depth; wherein the initial cell survival fraction model is a model obtained by optimizing the preset cell survival fraction basic model based on the synergy parameter; the synergy parameter is used to characterize the synergistic effect of a single type of reaction particles on the absorbed dose of other types of reaction particles during the boron neutron reaction.

[0014] In some embodiments of the first aspect of the present invention, the fitting sample pair includes a sample absorbed dose collected at the current target depth and a cell survival fraction corresponding to the sample absorbed dose; and a method for obtaining the fitting sample pair at the target depth includes:

[0015] A cell survival experiment is performed on a boron-containing solution at different irradiation distances in a cell survival experiment device using a neutron beam corresponding to the current target depth to obtain a cell survival fraction of the boron-containing solution at each irradiation distance; wherein the irradiation distance corresponds to the sample absorbed dose; the sample absorbed dose and the cell survival fraction corresponding to each irradiation distance are respectively constructed as fitting sample pairs to obtain groups of fitting sample pairs corresponding to the current target depth.

[0016] In some embodiments of the first aspect of the present invention, the cell survival experimental device comprises:

[0017] A dose distribution regulator is provided at the neutron incident port of the cell survival experimental device and is used to adjust the energy of the neutron beam; the dose distribution regulator is formed by stacking several layers of different types of moderation materials; and the method for obtaining the neutron beam corresponding to the current target depth includes:

[0018] The type and thickness of the moderator material of each layer in the dose distribution adjuster are adjusted to adapt the dose distribution adjuster to the current target depth, so as to obtain a neutron beam that is adapted to the current target depth.

[0019] In some embodiments of the first aspect of the present invention, the method for adjusting the type and thickness of the moderator material of each layer in the dose distribution adjuster includes:

[0020] A plurality of initial dose distribution regulator data are randomly generated to construct an iterative data group; each of the initial dose distribution regulator data includes the material type and thickness of each layer constituting the dose distribution regulator; the iterative data group is iteratively optimized using a genetic algorithm to obtain an optimized iterative data group; the dose distribution regulator data with the smallest fitness value in the optimized iterative data group is extracted; wherein the fitness value is used to characterize the degree of proximity between the iterative result and the set optimization target; the optimization target is associated with the target depth.

[0021] In a second aspect, the present invention provides a terminal comprising: a processor and a memory, wherein the memory is communicatively connected to the processor; the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the terminal executes any of the above-described methods for obtaining the total relative biological effect value based on boron neutron reaction, or executes any of the above-described methods for obtaining the total relative biological effect value based on boron neutron reaction.

[0022] In a third aspect, the present invention provides a computer storage medium storing a computer program. When the computer program is executed by a processor, it implements any of the above-described methods for obtaining the total relative biological effect value based on boron neutron reaction, or implements any of the above-described methods for obtaining the total relative biological effect value based on boron neutron reaction.

[0023] As described above, the method, terminal, and computer storage medium for obtaining a total relative biological effect value based on a boron neutron reaction provided herein construct fitting sample pairs and solve a cell survival fraction model based on the fitting sample pairs, thereby not only improving the efficiency of obtaining the cell survival fraction model but also effectively enhancing the model's accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 Shown is a schematic flow chart of a method for obtaining a cell survival fraction model based on boron neutron reaction provided by the present invention in one embodiment;

[0025] Figure 2 Shown is a flow chart of an implementation method of collecting a plurality of fitting sample pairs according to the present invention in one embodiment;

[0026] Figure 3 Shown is a flow chart of step S101 in one embodiment of the present invention;

[0027] Figure 4 Shown is a flow chart of another embodiment of the method for obtaining a cell survival fraction model based on different depths according to the present invention;

[0028] Figure 5 Shown is a flow chart of an implementation method of constructing a plurality of fitting sample pairs at the current target depth according to the present invention in one embodiment;

[0029] Figure 6 Shown is a schematic structural diagram of the cell survival experimental device in one embodiment of the present invention;

[0030] Figure 7 Shown is a schematic structural diagram of the cell survival experimental device of the present invention in another embodiment;

[0031] Figure 8 Shown is a flow chart of an embodiment of the present invention for adapting the dose distribution adjuster to the corresponding target depth by adjusting the type and thickness of the moderator material of each layer;

[0032] Figure 9 Shown is a flow chart of step S802 in one embodiment of the present invention;

[0033] Figure 10Shown is a flow chart of a method for obtaining a relative total biological effect value based on boron neutron reaction according to one embodiment of the present invention;

[0034] Figure 11 Shown is a schematic structural diagram of the terminal in one embodiment of the present invention. DETAILED DESCRIPTION

[0035] The following describes the embodiments of the present application through specific examples. Those skilled in the art can easily understand the other advantages and effects of the present application from the content disclosed in this specification. The present application can also be implemented or applied through other different specific embodiments. The details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that the following embodiments and features in the embodiments can be combined with each other unless they conflict.

[0036] It should be noted that in the following description, reference is made to the accompanying drawings, which illustrate several embodiments of the present application. It should be understood that other embodiments may be used and that mechanical, structural, electrical, and operational changes may be made without departing from the spirit and scope of the present application.

[0037] Also, as used herein, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context indicates otherwise. It should be further understood that the terms "comprise," "include," and "include" indicate the presence of stated features, operations, elements, components, items, categories, and / or groups, but do not preclude the presence, occurrence, or addition of one or more other features, operations, elements, components, items, categories, and / or groups. The terms "or" and "and / or" used herein are to be interpreted as inclusive, or mean any one or any combination.

[0038] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the technical solutions in the embodiments of the present invention are further described in detail through the following embodiments and in conjunction with the accompanying drawings. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the invention.

[0039] In order to solve the technical problems existing in the prior art, the present application first provides a method for obtaining a cell survival fraction model based on boron neutron reaction, which is used to obtain a cell survival fraction model corresponding to a target depth.

[0040] The cell survival fraction model is a model function used to characterize the relationship between the cell absorption dose of mixed particles (hereinafter referred to as "mixed absorbed dose") and the cell survival fraction; the mixed dose is the boron neutron reaction ( 10 B captures a neutron, 10 B(n,α)7 The sum of the cell absorption doses corresponding to each reaction particle generated during the Li reaction.

[0041] It should be noted that the method for obtaining the cell survival fraction model provided in this application can also be applied to situations where the number of target depths is single or multiple.

[0042] See also Figure 1 , which is a schematic flow chart of a method for obtaining a cell survival fraction model based on boron neutron reaction provided in the present application in one embodiment.

[0043] like Figure 1 As shown, the method includes the following steps:

[0044] S100, collecting several groups of fitting sample pairs at the current target depth;

[0045] The fitting sample pair is a sample data pair required for performing model fitting and solving the cell survival fraction model;

[0046] In a single fitting sample pair, it includes: a cell absorbed dose, and a cell survival fraction corresponding to the cell absorbed dose at the current target depth; that is, the cell survival fraction corresponding to the same cell absorbed dose is different for different target depths.

[0047] Specifically, in the cell survival experiment of the boron neutron reaction, several groups of fitting sample pairs are collected respectively; the number of the fitting sample pairs is adapted to the number of model parameters to be fitted. For a single group of fitting sample pairs, the collection method is as follows:

[0048] A cell absorption dose is selected, and the cell survival fraction corresponding to the cell absorption dose at the current target depth is collected; the collected cell survival fraction and the corresponding cell absorption dose are constructed into a set of fitting sample pairs.

[0049] In this embodiment, the number of the fitting sample pairs is not less than the number of model parameters to be fitted in the cell survival fraction model; illustratively, when the number of model parameters to be fitted is 4, the number of the fitting sample pairs constructed is not less than 4.

[0050] It should be noted that, in some specific embodiments, the number of groups of the fitting sample pairs may also be slightly smaller than the number of the model parameters; for example, when the number of parameters of the model parameters to be fitted is 4, the number of groups of the fitting sample pairs constructed can also be 3 groups.

[0051] S200 , using each of the fitting sample pairs, fitting the model parameters in the initial cell survival fraction model to be fitted, to obtain a cell survival fraction model corresponding to the current target depth.

[0052] Specifically, each group of fitting sample pairs at the current target depth is input into the cell survival fraction model respectively; the model parameters to be fitted in the model are solved to obtain the optimal solution of each model parameter at the current target depth; each optimal solution is substituted into the cell survival fraction model to obtain the cell survival fraction model at the current target depth.

[0053] The method for obtaining a cell survival fraction model provided in this embodiment obtains a cell survival fraction model by collecting multiple sets of fitting sample pairs and solving the cell survival fraction model based on the fitting sample pairs. This not only improves the efficiency of obtaining the cell survival fraction model, but also effectively improves the model accuracy of the cell survival fraction model.

[0054] In some optional embodiments, the model parameters in the initial model of the cell survival fraction include a linear term coefficient and a quadratic term coefficient; wherein the linear term coefficient and the quadratic term coefficient correspond to the effects of irreparable cell damage and repairable cell damage on the absorbed dose, respectively.

[0055] More specifically, the initial model of cell survival fraction is:

[0056]

[0057] Wherein, D represents the absorbed dose, S represents the cell survival fraction, α and β represent the linear term coefficient and the quadratic term coefficient corresponding to the absorbed dose, respectively.

[0058] It should be noted that, in other specific embodiments, the initial cell survival fraction model may also adopt other model functions for characterizing the relationship between the mixed absorbed dose and the cell survival fraction.

[0059] When the constructed cell survival fraction model does not consider the mutual influence of different reaction particles on each other's biological efficiency during the boron neutron reaction process, the cell survival fraction or mixed absorbed dose calculated based on the cell survival fraction model will often differ from the true value to a certain extent, thereby causing the fitted cell survival fraction model to still have problems such as insufficient accuracy. Therefore, to further improve the accuracy of the cell survival fraction model, in some embodiments, the initial cell survival fraction model is a cell survival fraction model optimized based on synergistic parameters, that is, the synergistic parameters between the reaction particles are introduced into the preset cell survival fraction basic model to obtain the initial cell survival fraction model to be fitted.

[0060] The cell survival fraction basic model is an existing cell survival fraction model, and the model parameters of the model at least include the quadratic term coefficient, which is used to characterize the effect of repairable cell damage on the absorbed dose of various reactive particles.

[0061] The synergy parameter is used to characterize the synergistic effect of various types of reaction particles on each other's absorbed dose during the boron neutron reaction process; that is, the effect of the biological efficiency generated by a certain type of reaction particles (such as boron particles) during the reaction process on the biological efficiency of another type of reaction particles (such as hydrogen particles) in the same reaction process. In this embodiment, the synergy parameter is a parameter constructed based on the quadratic term coefficient.

[0062] In a specific embodiment, the cell survival fraction basic model adopts the classic cell survival fraction model, which is:

[0063]

[0064] The synergy parameter is a geometric mean constructed based on the quadratic coefficients, which is:

[0065]

[0066] Among them, β i represents the quadratic term coefficient corresponding to the first reaction particle i (i-th type reaction particle); β j Represents the quadratic term coefficient corresponding to the second reactive particle j (the jth type reactive particle).

[0067] The synergistic parameter is introduced into the classic cell survival fraction model, and the introduced cell survival fraction model is logarithmized to obtain a new cell survival fraction model:

[0068]

[0069] Where D represents the absorbed dose, S represents the cell survival fraction, α and β represent the linear coefficient and the quadratic coefficient corresponding to the absorbed dose, respectively; α i represents the linear coefficient corresponding to the first reaction particle i; β i represents the quadratic term coefficient corresponding to the first reaction particle i; β j represents the coefficient of the quadratic term corresponding to the second reaction particle j; D i represents the absorbed dose corresponding to the first reaction particle i, D j represents the absorbed dose corresponding to the second reactive particle j.

[0070] Based on the new cell survival fraction model, it is determined that the model coefficients to be fitted include 4 linear term coefficients (α1, α2, α3, α4) and 4 quadratic term coefficients (β1, β2, β3, β4), a total of 8 model coefficients, and the number of fitting sample pairs corresponding to each target depth is not less than 8.

[0071] It should be noted that, in other specific embodiments, the synergy coefficient may also be other mathematical expressions for characterizing the synergistic effect between two types of reactive particles in terms of biological effects, such as Pearson correlation coefficient, Spearman correlation coefficient, etc.

[0072] In order to further improve the fitting effect of the cell survival fraction model, in some optional embodiments, the method of collecting several groups of fitting sample pairs at the current target depth is as follows: Figure 2 Shown, including:

[0073] S101, selecting a corresponding number of sample absorbed doses according to the number of fitting sample pairs:

[0074] The absorbed dose of each sample is evenly distributed within the interval.

[0075] S102, collecting the cell survival fraction corresponding to the absorbed dose of each sample at the current target depth;

[0076] S103: Constructing a fitting sample pair corresponding to the current depth based on the sample absorbed dose and the corresponding cell survival fraction.

[0077] In a specific embodiment, when step S101 is executed, Figure 3 As shown, it includes the following sub-steps:

[0078] S101A, obtains the range of mixed absorbed dose corresponding to the current target depth during the boron neutron reaction process;

[0079] S101B, dividing the interval range into a corresponding number of subintervals based on the number of fitting sample pairs;

[0080] S101C, in each of the subintervals, extracting the mean value of the mixed absorbed dose within the subinterval as the sample absorbed dose corresponding to the subinterval.

[0081] By extracting sample absorbed doses in different subintervals, the obtained sample absorbed doses are distributed more evenly within the interval range, thereby making the data distribution of the fitting sample pairs constructed based on the sample absorbed doses more even, avoiding poor fitting results caused by uneven data distribution, and thus improving the fitting accuracy of the cell survival fraction model.

[0082] In some optional embodiments, the acquisition of several groups of fitting sample pairs at the current target depth is based on acquisition by a cell survival experimental device.

[0083] During actual BNCT treatment, the location of the tumor in the body often varies, meaning the depth of the radiation source often varies. Because the paths traversed by various types of reactive particles in the boron neutron reaction differ at different radiation source depths, the cell survival fraction corresponding to the same absorbed dose often differs, meaning that different depths result in different cell survival fraction models.

[0084] Therefore, in order to obtain cell survival fraction models corresponding to different target depths, the present application also provides another method for obtaining cell survival fraction models based on different depths, which is used to obtain cell survival fraction models corresponding to different target depths.

[0085] See also Figure 4 , which is a flow chart of an embodiment of the method for obtaining the cell survival fraction model based on different depths provided in the present application.

[0086] like Figure 4 As shown, the method includes:

[0087] S10, determining the neutron beam corresponding to each target depth;

[0088] Specifically, according to the depth value of the current target depth, the mapping relationship between the target depth and the neutron flux energy is used to determine the energy of the neutron flux corresponding to the current target depth; and according to the energy, the corresponding neutron beam is output.

[0089] S20 , for different target depths, respectively executing a process of acquiring a cell survival fraction model corresponding to the target depth to obtain a cell survival fraction model corresponding to each target depth.

[0090] Among them, for different target depths, Figure 1 The method shown executes the acquisition process of the cell survival fraction model corresponding to the target depth respectively to obtain the cell survival fraction model corresponding to each target depth.

[0091] Exemplarily, when the target depth includes a first target depth H1, a second target depth H2, and a third target depth H3, n groups of first fitting sample pairs at the first target depth H1, n groups of second fitting sample pairs at the second target depth H2, and n groups of third fitting sample pairs at the third target depth H3 are collected respectively;

[0092] Using the n groups of first fitting sample pairs at the first target depth H1, the model parameters in the initial cell survival fraction model to be fitted are fitted to obtain a cell survival fraction model corresponding to the first target depth H1;

[0093] Using the n sets of second fitting sample pairs at the second target depth H2, the model parameters in the initial cell survival fraction model to be fitted are fitted to obtain a cell survival fraction model corresponding to the second target depth H2;

[0094] The model parameters in the initial cell survival fraction model to be fitted are fitted using the n sets of third fitting sample pairs at the third target depth H3 to obtain a cell survival fraction model corresponding to the third target depth H3.

[0095] In some optional embodiments, for a single target depth, the implementation method of constructing several sets of fitting sample pairs at the current target depth is as follows: Figure 5 Shown, including:

[0096] S21, based on the cell survival experimental device, using a neutron beam corresponding to the current target depth, performing a cell survival experiment on the boron-containing solution at different irradiation distances to obtain a cell survival fraction of the boron-containing solution at each irradiation distance;

[0097] The irradiation distance is the distance between the boron-containing solution and the incident port of the neutron beam along the incident direction.

[0098] The irradiation distance corresponds to the sample absorbed dose, that is, different irradiation distances correspond to different sample absorbed doses.

[0099] Specifically, after determining the absorbed dose of each sample, a neutron beam corresponding to the current target depth is used to perform a cell survival experiment on the boron-containing solutions at different irradiation distances in the cell survival experimental device; the experimental results corresponding to each boron-containing solution are measured to obtain the cell survival fraction corresponding to the absorbed dose of different samples.

[0100] S22, construct a fitting sample pair based on the sample absorbed dose and cell survival fraction corresponding to the same irradiation distance;

[0101] The above steps S21 to S22 are performed for each target depth, thereby obtaining a fitting sample pair corresponding to each target depth.

[0102] In one embodiment, step S21 is performed based on a cell survival experimental device; see Figure 6 , which is a schematic structural diagram of the cell survival experimental device in one embodiment; Figure 6 As shown, the cell survival experimental device includes: an incident port 100 , a water model 200 , a plurality of cell suspension tubes 300 and a rotating screw 400 .

[0103] The incident port 100 is provided on one side end surface of the cell survival experiment device, and is used to allow the neutron beam to be injected into the cell survival experiment device through the incident port 100 .

[0104] The water mold 200 is used to load liquid, such as water.

[0105] The cell suspension tubes 300 are arranged in the water mold at certain intervals and are connected to each other through a screw 400, so that when the screw is rotated, the cell suspension tubes also rotate.

[0106] The cell survival experiment device is used to perform a cell survival experiment on boron-containing solutions at different irradiation distances in the device, including:

[0107] The cells were cultured in a culture medium containing the second-generation boron drug BPA (a culture medium obtained by dissolving the second-generation boron drug BPA in a Tris-HCl pH=8.0 buffer solution and adding the buffer solution to a normal culture medium) and placed in a CO2 incubator for culture. The cells were used for experiments when they were in the logarithmic growth phase. The V79 cells in the logarithmic growth phase were moved to a cell suspension tube, and the front surface of the water model was used as the starting position. Based on a preset distance interval, the cell suspension tubes were placed at different positions from the front surface to obtain a sufficient number of samples for solving the cell survival model. Exemplarily, the distance interval was 0.5 cm.

[0108] A cell suspension tube containing cells was secured to a rotating screw at 3 rpm to maintain the cells in suspension. Irradiation was initiated, and to prevent the influence of sublethal cell damage repair on experimental results, the irradiation duration was set to the same for each irradiation. After irradiation, the cells in each cell suspension tube were counted. The cells were diluted and inoculated into a culture dish and cultured in a CO2 incubator. The cells were fixed with formaldehyde and stained, and cell viability was measured using a cell imaging device to obtain the corresponding cell survival score for each cell suspension tube.

[0109] In practical applications, since the parameters of the neutron source accelerator that forms the neutron beam, such as power, material, and thickness, are relatively fixed, the energy of the neutron beam formed by the neutron source accelerator is often relatively fixed and difficult to adjust according to demand; therefore, the target depth corresponding to the existing cell survival experimental device is often relatively single; as a result, based on the existing cell survival experimental device, it is impossible to conveniently and efficiently obtain the cell survival fraction model corresponding to different target depths.

[0110] To solve this technical problem, in some specific embodiments, a cell survival experimental device with neutron source energy adjustment is used to perform step S21; Figure 7 As shown in the figure, the cell survival experimental device is Figure 6The devices shown are basically the same, except that the cell survival experimental device is provided with a neutron source regulator 500 at the neutron incident port for regulating the energy of the neutron beam to obtain a neutron beam adapted to the target depth.

[0111] Furthermore, in order to improve the adjustment precision and accuracy of the neutron beam energy, the neutron source adjuster includes a dose distribution shifter (DDS); the dose distribution shifter is a structural component formed by stacking several layers of different types of moderator materials; by adjusting the type and thickness of the moderator material of each layer, the dose distribution shifter is adapted to the corresponding target depth.

[0112] In a specific embodiment, the dose distribution regulator is adapted to the corresponding target depth by adjusting the type and thickness of the moderator material of each layer, such as Figure 8 Shown, including:

[0113] Step S801 : randomly generating a plurality of initial dose distribution adjuster data, wherein the initial dose distribution adjuster data includes the material type and thickness of each layer, and all the initial dose distribution adjuster data constitute an iterative data group.

[0114] Specifically, all materials that can be used to construct a dose distribution regulator are selected as candidate materials for the dose distribution regulator. All materials suitable for neutron moderation and absorption can be used as candidate materials. Since hydrogen-containing materials combined with thermal neutron absorbers can achieve the function of thermal neutron distribution regulation, the candidate materials for the dose distribution regulator are preferably hydrogen-containing materials. For example, the candidate materials for the dose distribution regulator may include moderation materials such as polyethylene, water, acrylic acid, boron-containing polyethylene, and boron carbide. Obtain all available candidate materials for the dose distribution regulator under the current conditions, and number all the obtained candidate materials so that all candidate materials have different numbers.

[0115] Based on the numbers of the current candidate materials, multiple number groups are randomly generated, each number group having multiple numbers, and then based on the candidate materials corresponding to the numbers in each number group, the material distribution data corresponding to each number group is generated. For example, assuming that polyethylene is numbered 1, water is numbered 2, acrylic acid is numbered 3, boron-containing polyethylene is numbered 4, and boron carbide is numbered 5, then the material distribution data corresponding to the number groups 1-3-5 are polyethylene, acrylic acid, and boron carbide. Based on experimental data, it can be seen that setting the number of material layers in the dose distribution regulator data to 3 layers is more likely to achieve the maximum dose caused by thermal neutrons deposited at the center of the tumor than setting it to other layers. Therefore, the number of material layers in the dose distribution regulator data is preferably designed to be 3 layers, and there are 3 numbers in each number group. Then, the thickness of each material in each material distribution data is randomly generated within a preset range, and the initial dose distribution regulator data corresponding to each material distribution data is obtained. Furthermore, the preset range of the random thickness of each candidate material in each material distribution data can be set to 0-3cm. Each initial dose distribution modifier data thus obtained has a fixed material type and each type of material has a fixed thickness. After obtaining a plurality of initial dose distribution modifier data, all the plurality of initial dose distribution modifier data need to be combined into an iterative data group.

[0116] Step S802 , iteratively optimizing the iterative data set by a genetic algorithm to obtain an optimized iterative data set, and using the dose distribution adjuster data with the smallest fitness value in the optimized iterative data set as a design solution for the dose distribution displacement device.

[0117] like Figure 9 As shown, step S802 specifically includes sub-step S8021 and step S8022.

[0118] Step S8021: Obtain the current iteration data group to obtain the new round of iteration data group.

[0119] Specifically, the current iterative data set is first used as the existing population in the genetic algorithm, and the fitness value of each dose distribution modifier data in the current iterative data set is first calculated. Then, based on the fitness value in ascending order, some dose distribution modifier data are screened out from the current iterative data set, and the screened dose distribution modifier data are cross-mutated to obtain multiple cross-mutated dose distribution modifier data. Secondly, the fitness values ​​of all cross-mutated dose distribution modifier data are obtained, and based on all dose distribution modifier data in the current iterative data set and all cross-mutated dose distribution modifier data, some dose distribution modifier data are screened out based on the fitness value in ascending order to form a new population, and the new population is used as the new iterative data set.

[0120] Cross-mutating the selected dose distribution modifier data specifically includes: cross-mutating and mutating the material type of the selected dose distribution modifier data to obtain dose distribution modifier data after cross-mutation of the material type; and then cross-mutating and mutating the material thickness of the dose distribution modifier data after cross-mutation of the material type to obtain multiple cross-mutated dose distribution modifier data. It should be noted that cross-mutating the material thickness of the dose distribution modifier data can also be performed first, and then cross-mutating the material type of the dose distribution modifier data.

[0121] The fitness value of the dose distribution regulator data is obtained as follows: based on the dose distribution regulator data, a model is built in the Monte Carlo software (MCNP) to obtain a simulated dose distribution regulator, and then the Monte Carlo software is run to output the thermal neutron flux distribution data when the simulated dose distribution regulator is set at the beam outlet of the beam shaper in the BNCT device, that is, the thermal neutron flux distribution data corresponding to the dose distribution regulator data is obtained; then the programming software MATLAB reads the thermal neutron flux distribution data file output by the Monte Carlo software, extracts the calculation results to output the fitness value of the dose distribution regulator data.

[0122] It should be noted that the above-mentioned Monte Carlo software sets the target depth of the tumor center as the optimization target; and the fitness value of the dose distribution regulator data needs to be set to be linearly related to the distance between the depth of the maximum value of the thermal neutron flux in the recipient body and the target depth of the tumor center.

[0123] The specific fitness value is obtained based on the fitness function calculation. The fitness function expression of the programming software MATLAB is designed as:

[0124] OBJ=A·|D thermal-max -D tumor |+B·F thermal-max

[0125] Among them, OBJ represents the fitness value. The lower the fitness value, the closer the individual is to the set optimization goal. A and B both represent weight factors. When optimizing different goals, the weight factors can be adjusted according to the importance of different optimization goals, and the weight factors can be set to negative numbers. | D thermal-max -D tumor | represents the distance between the depth of maximum thermal neutron flux in the recipient body and the target depth of the tumor center, F thermal-max The maximum thermal neutron flux in the receptor is obtained based on the exit neutron energy spectrum of the beam shaper in the current BNCT device.

[0126] The fitness value of each dose distribution adjuster data in the current iterative data group and the fitness values ​​of all mutated dose distribution adjuster data are obtained in the above manner.

[0127] Step S8022, determine whether the new round of iterative data group meets the iteration termination condition. If so, select the dose distribution adjuster data with the smallest fitness value in the new round of iterative data group as the dose distribution displacement device design scheme; otherwise, use the new round of iterative data group as the current iterative data group, and obtain a new round of iterative data group based on the current iterative data group.

[0128] Specifically, determine whether the newly acquired new round of iterative data group meets the iteration termination condition, and further determine whether the number of iterations to which the acquired new round of iterative data group belongs (that is, the number of iterations currently performed) is greater than the preset number of iterations. If so, it means that the current number of iterations has reached a sufficient number. At this time, the dose distribution adjuster data with the smallest fitness value in the new round of iterative data group is selected as the design scheme of the dose distribution displacement device; otherwise, it means that the current number of iterations has not yet met the requirements. At this time, the newly acquired new round of iterative data group is required to be used as the current iterative data group, and step S8021 is re-executed to obtain a new new round of iterative data group (that is, a new round of iterative data group is obtained based on the current iterative data group). It should be noted that the above-mentioned iteration termination condition can also be set as the presence of dose distribution adjuster data with a fitness value greater than a preset fitness threshold in the new round of iteration data group, that is, it is judged whether there is dose distribution adjuster data with a fitness value greater than the preset fitness threshold in the latest acquired new round of iteration data group. If so, it means that a dose distribution displacement device design scheme that meets the requirements has been found. At this time, the dose distribution adjuster data with the smallest fitness value in the new round of iteration data group is selected as the design scheme of the dose distribution displacement device. Otherwise, it means that the new round of iteration data group does not have a dose distribution displacement device design scheme that meets the requirements. At this time, the latest acquired new round of iteration data group is used as the current iteration data group, and step S802 is re-executed to obtain a new new round of iteration data group (that is, a new round of iteration data group is obtained based on the current iteration data group).

[0129] Furthermore, the above two iteration termination conditions may exist at the same time, that is, the iteration can be stopped when any one of the above two termination conditions is met during the judgment.

[0130] The method for obtaining a cell survival fraction model provided in this embodiment can utilize the same cell survival experimental apparatus to achieve the collection of sample absorbed doses and corresponding cell survival fractions at different target depths. Based on the collected sample absorbed doses and corresponding cell survival fractions, each group of fitting sample pairs can be quickly obtained, and the cell survival fraction model can then be solved based on the fitting samples. Compared to the cumbersome operation of separately solving models corresponding to different target depths in the prior art, the present application can quickly obtain cell survival fraction models applicable to different target depths, thereby improving not only the efficiency of obtaining models at different target depths but also the accuracy of the cell survival fraction model by using multiple groups of fitting sample pairs to solve the model.

[0131] Based on the same technical concept, the present application also provides a method for obtaining the total relative biological effect value based on boron neutron reaction, which is used to obtain the total relative biological effect value corresponding to the mixed absorbed dose at different target depths, that is, the total RBE value of the mixed absorbed dose.

[0132] Among them, the total RBE value of the mixed absorbed dose is a comprehensive value of the RBE value corresponding to the boron dose, the RBE value corresponding to the hydrogen dose, and the RBE value corresponding to the nitrogen dose, which is used to characterize the total relative biological effect characteristics of the mixed particles during the boron neutron reaction process.

[0133] For example, when the cell survival fraction to be measured is 1%, the cell survival fraction of 1% is taken as the biological endpoint. Based on the method for obtaining the cell survival fraction model provided in this application, the total RBE value of the mixed absorbed dose corresponding to the cell survival fraction of 1% at different target depths can be obtained.

[0134] See also Figure 10 , which is a flow chart of a method for obtaining the total relative biological effect value based on boron neutron reaction provided in this application in one embodiment.

[0135] like Figure 10 As shown, the method includes the following steps:

[0136] S1, obtaining a cell survival fraction model corresponding to each target depth, and obtaining a reference model corresponding to each target depth;

[0137] The reference model is a cell survival fraction model corresponding to gamma rays, that is, a model used to characterize the relationship between the cell absorbed dose corresponding to gamma rays and the cell survival fraction;

[0138] Specifically, after determining the number of target depths, any of the above-described cell survival fraction model acquisition methods is used to acquire a cell survival fraction model corresponding to each target depth. This process is the same as the implementation process in the above embodiment and will not be repeated here.

[0139] S2, for each target depth, obtaining the mixed absorbed dose and the reference absorbed dose corresponding to the cell survival to be measured according to the cell survival fraction to be measured, so as to obtain the total RBE value of the mixed absorbed dose at the current target depth based on the mixed absorbed dose and the reference absorbed dose;

[0140] The mixed absorbed dose value is the absorbed dose value corresponding to the cell survival fraction to be measured in the cell survival fraction model corresponding to the target depth; the reference absorbed dose value is the absorbed dose value corresponding to the cell survival fraction to be measured in the reference model corresponding to the target depth.

[0141] Specifically, for the first target depth H1, the cell survival fraction M to be measured is input into the cell survival fraction model corresponding to the current target depth to obtain the corresponding mixed absorbed dose value D1; and the cell survival fraction M to be measured is input into the reference model corresponding to the current target depth to obtain the corresponding reference absorbed dose value D0

[0142] Based on the mixed absorbed dose value D1 and the reference absorbed dose value D0, the total RBE value at the first target depth H1 is obtained as follows:

[0143] RBE 总1 =D0 / D1

[0144] Similarly, for the second target depth H2, the total RBE value at the second target depth H2 is obtained as:

[0145] RBE 总2 =D0 / D2

[0146] The same goes for other cases, so I won’t go into details here.

[0147] It should be noted that, in the absence of conflict, the above embodiments and features in the embodiments can be combined with each other; for example, based on Figure 7 The cell survival experiment setup is shown, performed Figure 1 The method for obtaining the cell survival fraction model is shown to conveniently and quickly obtain the cell survival fraction model corresponding to the target depth.

[0148] Based on the same technical concept, the method for obtaining the total relative biological effect value based on boron neutron reaction provided in the above embodiment of the present invention can be implemented on the terminal side or the server side.

[0149] See also Figure 11, is a schematic diagram of an optional hardware structure of an electronic terminal 700 provided in an embodiment of the present invention. The electronic terminal 700 can be a live broadcast machine with integrated photo / video functions, a video camera, a mobile phone, a computer device, a tablet device, a personal digital processing device, a factory back-end processing device, etc. The electronic terminal 700 includes: at least one processor 701, a memory 702, at least one network interface 704, and a user interface 706. The various components in the device are coupled together via a bus system 705. It can be understood that the bus system 705 is used to achieve connection and communication between these components. In addition to including a data bus, the bus system 705 also includes a power bus, a control bus, and a status signal bus.

[0150] The user interface 706 may include a display, a keyboard, a mouse, a trackball, a click gun, keys, buttons, a touch pad or a touch screen.

[0151] It will be appreciated that the memory 702 may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. The non-volatile memory may be a read-only memory (ROM) or a programmable read-only memory (PROM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM) and synchronous static random access memory (SSRAM). The memories described in the embodiments of the present invention are intended to include, but are not limited to, these and any other suitable types of memories.

[0152] The memory 702 in the embodiment of the present invention is used to store various categories of data to support the operation of the electronic terminal 700. Examples of these data include: any executable program used to operate on the electronic terminal 700, such as the operating system 7021 and the application 7022; the operating system 7021 includes various system programs, such as the framework layer, the core library layer, the driver layer, etc., which are used to implement various basic services and process hardware-based tasks. The application 7022 can include various applications, such as a media player (MediaPlayer), a browser (Browser), etc., which are used to implement various application services. The method for obtaining the total relative biological effect value based on the boron neutron reaction according to the embodiment of the present invention can be included in the application 7022.

[0153] The methods disclosed in the above embodiments of the present invention can be applied to or implemented by processor 701. Processor 701 may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by hardware integrated logic circuits in processor 701 or by software instructions. The above processor 701 may be a general-purpose processor, a digital signal processor (DSP), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Processor 701 can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor 701 may be a microprocessor or any conventional processor. The steps of the accessory optimization method provided in the embodiments of the present invention can be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium located in a memory. The processor reads the information in the memory and, in conjunction with its hardware, completes the steps of the above method.

[0154] In an exemplary embodiment, the electronic terminal 700 may be configured to execute the aforementioned method using one or more application specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), or complex programmable logic devices (CPLDs).

[0155] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon. When the program is called by a processor, the method for obtaining the total relative biological effect value based on boron neutron reaction provided by the present invention is implemented.

[0156] Among them, a computer-readable storage medium can be a tangible device that can hold and store instructions used by an instruction execution device. The computer-readable storage medium can be, for example, (but not limited to) an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, and a mechanical encoding device.

[0157] The computer-readable program described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in each computing / processing device.

[0158] It should be noted that, in the various embodiments of the present application, the serial numbers of the above steps do not indicate the order of execution. The order of execution of the steps should be determined by their functions and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0159] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the present invention. Anyone skilled in the art may modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by one of ordinary skill in the art without departing from the spirit and technical principles disclosed herein are intended to be covered by the claims of the present invention.

Claims

1. A method for obtaining the total relative biological effect value based on boron neutron reaction, characterized in that: include: Obtaining a cell survival fraction model and a reference model corresponding to each target depth; For each target depth, according to the cell survival fraction to be measured, the mixed absorbed dose and the reference absorbed dose corresponding to the cell survival fraction to be measured are obtained respectively; Based on the mixed absorbed dose and the reference absorbed dose corresponding to each target depth, the relative biological effect total value of the mixed absorbed dose at the corresponding target depth is obtained, which is: RBE 总 =D0 / D1; Among them, RBE 总 is the total relative biological effect value at the target depth; D1 is the mixed absorbed dose value; D0 is the reference absorbed dose value; The method for obtaining the cell survival fraction model corresponding to each target depth includes: Several groups of fitting sample pairs at the current target depth are collected; based on the fitting sample pairs at each target depth, the model parameters to be fitted in the initial cell survival fraction model are respectively solved to obtain the cell survival fraction model at each target depth; the fitting sample pairs include the sample absorbed dose and the cell survival fraction corresponding to the sample absorbed dose at the current target depth.

2. The method for obtaining the total relative biological effect value based on boron neutron reaction according to claim 1, characterized in that: For a single target depth, the method for obtaining the total relative biological effect value of the mixed absorbed dose at the corresponding target depth includes: The cell survival fraction to be measured is input into the cell survival fraction model corresponding to the current target depth to obtain a corresponding mixed absorbed dose value; and the cell survival fraction is input into the reference model corresponding to the current target depth to obtain a corresponding reference absorbed dose value.

3. The method for obtaining the total relative biological effect value based on boron neutron reaction according to claim 1, characterized in that: The model parameters in the initial model of cell survival fraction include a linear term coefficient and a quadratic term coefficient; wherein the linear term coefficient and the quadratic term coefficient correspond to the effects of irreparable cell damage and repairable cell damage on the absorbed dose, respectively.

4. The method for obtaining the total relative biological effect value based on boron neutron reaction according to claim 3, characterized in that: The initial cell survival fraction model is a model obtained by optimizing a preset cell survival fraction basic model based on synergistic parameters; The synergy parameter is a parameter constructed based on the quadratic term coefficient, and is used to characterize the synergistic effect of a single type of reaction particles on the absorbed dose of other types of reaction particles during the boron neutron reaction process.

5. The method for obtaining the total relative biological effect value based on boron neutron reaction according to claim 4, characterized in that: The initial model of cell survival fraction is: The cell survival fraction basic model is: Where S represents the cell survival fraction, D represents the absorbed dose, α and β represent the linear coefficient and the quadratic coefficient corresponding to the absorbed dose, respectively. i represents the linear coefficient corresponding to the first reaction particle i, β i represents the quadratic term coefficient corresponding to the first reaction particle i, β j represents the quadratic term coefficient corresponding to the second reaction particle j, D i represents the absorbed dose corresponding to the first reaction particle i, D j represents the absorbed dose corresponding to the second reactive particle j, is the collaborative parameter.

6. The method for obtaining the total relative biological effect value based on boron neutron reaction according to claim 1, characterized in that: The implementation method of respectively calculating the model parameters to be fitted in the initial cell survival fraction model based on the fitting sample pairs at each target depth, when a single target depth is present, includes: Each group of fitting sample pairs at the current target depth is input into the initial cell survival fraction model respectively; the model parameters to be fitted in the model are solved to obtain the optimal solution of each model parameter at the current target depth; each optimal solution is substituted into the initial cell survival fraction model to obtain the cell survival fraction model at the current target depth.

7. The method for obtaining the total relative biological effect value based on boron neutron reaction according to claim 1, characterized in that: The method for obtaining the fitting sample pair at the target depth includes: Performing a cell survival experiment on the boron-containing solution at different irradiation distances in the cell survival experiment device using a neutron beam corresponding to the current target depth to obtain a cell survival fraction of the boron-containing solution at each irradiation distance; wherein the irradiation distance corresponds to the sample absorbed dose; A fitting sample pair is constructed based on the sample absorbed dose and cell survival fraction corresponding to the same irradiation distance.

8. The method for obtaining the total relative biological effect value based on boron neutron reaction according to claim 7, characterized in that: The cell survival experimental device comprises: A dose distribution regulator is provided at the neutron incident port of the cell survival experimental device and is used to adjust the energy of the neutron beam; the dose distribution regulator is formed by stacking several layers of different types of moderation materials; Furthermore, the method for acquiring the neutron beam corresponding to the current target depth includes: The type and thickness of the moderator material of each layer in the dose distribution adjuster are adjusted to adapt the dose distribution adjuster to the current target depth, so as to obtain a neutron beam that is adapted to the current target depth.

9. A terminal, characterized in that: include: a processor and a memory, wherein the memory is communicatively connected to the processor; The memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the terminal performs the method for obtaining the total relative biological effect value based on boron neutron reaction according to any one of claims 1 to 8.

10. A computer storage medium storing a computer program, wherein: When the computer program is executed by a processor, the method for obtaining the total relative biological effect value based on boron neutron reaction according to any one of claims 1 to 8 is implemented.

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