Boron neutron reaction-based relative biological effect total value acquisition method, terminal and medium

Abstract

The invention provides a boron neutron reaction-based relative biological effect total value acquisition method, a terminal and a medium. The method comprises the following steps of: acquiring a cell survival fraction model and a reference model corresponding to each target depth; for each target depth, according to the survival fraction of the cells to be measured, respectively acquiring a mixed absorbed dose and a reference absorbed dose corresponding to the survival fraction of the cells to be measured; based on the mixed absorbed dose and the reference absorbed dose corresponding to each target depth, obtaining a relative biological effect total value of the mixed absorbed dose under the corresponding target depth; according to the method, the acquisition accuracy of the cell survival score model is improved, and the acquisition accuracy of the relative biological effect total value is effectively improved.

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 acquiring a total relative biological effect value based on a boron neutron reaction. Background Art

[0002] In the process of formulating the existing boron neutron capture therapy (BNCT) plan / scheme, the following equivalent equation is usually used to obtain the equivalent photon dose of the tumor target area and the organ 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, boron dose, nitrogen dose and hydrogen dose, respectively. 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 usually used to convert physical dose into biological dose, which is the ratio of the dose required for a certain biological effect caused by 250keV X-rays or gamma rays to the dose required for the same biological effect caused by the observed ionizing radiation. Since neutrons are constantly slowed down in the process of penetrating human tissues, the corresponding RBE values ​​for tumors at different depths also change accordingly.

[0006] In the prior art, the RBE value of the mixed absorbed dose is usually 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 of obtaining the total RBE value corresponding to the mixed absorbed dose based on a cell survival fraction model. However, the cell survival fraction model currently used often uses an existing empirical model or experimental model, and its model distribution is quite different from the actual distribution of the cell survival fraction at the target depth, resulting in a low accuracy of the model, which in turn reduces the accuracy of the total biological effect value obtained based on the model and makes it difficult to estimate. Summary of the invention

[0007] In view of the above-mentioned shortcomings of the prior art, the purpose of the present invention is to provide a method, terminal and computer storage medium for obtaining the total relative biological effect value based on boron neutron reaction, which can solve the problem of poor accuracy in obtaining the total relative biological effect value.

[0008] To achieve the above-mentioned and other related purposes, the present invention provides, in a first aspect, a method for obtaining a cell survival fraction model based on different target depths, characterized in that it includes:

[0009] 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 relative total biological effect value of the mixed absorbed dose at the corresponding target depth is obtained.

[0010] 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:

[0011] RBE 总 =D 0 / D 1

[0012] Among them, RBE 总 is the total relative biological effect at the target depth; D 1 is the mixed absorbed dose value; D 0 is the reference absorbed dose value.

[0013] In some embodiments of the first aspect of the present invention, the method for obtaining the cell survival fraction model corresponding to each target depth includes:

[0014] 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 after 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.

[0015] 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:

[0016] 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, so as to obtain the 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, so as to obtain groups of fitting sample pairs corresponding to the current target depth.

[0017] In some embodiments of the first aspect of the present invention, the cell survival experimental device comprises:

[0018] 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:

[0019] The type and thickness of the moderation material of each layer in the dose distribution adjuster are adjusted so that the dose distribution adjuster is adapted to the current target depth, so as to obtain a neutron beam adapted to the current target depth.

[0020] 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:

[0021] A plurality of initial dose distribution adjuster data are randomly generated to construct an iterative data group; each of the initial dose distribution adjuster data includes the material type and thickness of each layer constituting the dose distribution adjuster; the iterative data group is iteratively optimized using a genetic algorithm to obtain an optimized iterative data group; the dose distribution adjuster 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.

[0022] In some embodiments of the first aspect of the present invention, the iterative optimization of the iterative data set using a genetic algorithm comprises:

[0023] Generate a new population based on the current iterative data group, and use the new population as a new round of iterative data group;

[0024] Determine whether the new round of iterative data group meets the iteration termination condition. If so, use the new round of iterative data group as the optimized iterative data group; otherwise, use the new round of iterative data group as the current iterative data group and re-execute the iterative optimization process; wherein the iteration termination condition is that the current iteration number is greater than the preset iteration number or the new round of iterative data group contains the dose distribution regulator data whose fitness value is greater than the preset fitness threshold.

[0025] In some embodiments of the first aspect of the present invention, the fitness value is obtained by calculation based on a fitness function, and the fitness function expression is:

[0026] OBJ=A·|D thermal-max -D tumor |+B·F thermal-max

[0027] Wherein, OBJ represents the fitness value; A and B both represent weight factors; |D thermal-max -D tumor | represents the distance between the thermal neutron flux maximum depth and the target depth, F thermal-max It represents the maximum thermal neutron flux value, which is obtained based on the neutron energy spectrum; the maximum depth of the thermal neutron flux is obtained based on the dose distribution adjuster data.

[0028] The present invention provides a terminal in a second aspect, 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 methods for obtaining the total relative biological effect based on boron neutron reaction as described above, or executes any of the methods for obtaining the total relative biological effect based on boron neutron reaction as described above.

[0029] In a third aspect, the present invention provides a computer storage medium storing a computer program, which, when executed by a processor, 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.

[0030] As described above, the method, terminal and computer storage medium for obtaining the total relative biological effect value based on boron neutron reaction provided in the present application, by constructing fitting sample pairs corresponding to different target depths, solving the initial cell survival fraction model based on the fitting sample pairs, and obtaining the cell survival fraction model corresponding to the different target depths, thereby quickly obtaining the cell survival fraction model suitable for different target depths, and then obtaining the total relative biological effect value of the mixed absorbed dose at the corresponding target depth, which effectively improves the accuracy of obtaining the cell survival fraction model and the accuracy of obtaining the total relative biological effect value. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] 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;

[0032] Figure 2 It is a flow chart of an implementation method of collecting a plurality of fitting sample pairs in the present invention in one embodiment;

[0033] Figure 3 It is a schematic diagram of the process of step S101 in one embodiment of the present invention;

[0034] Figure 4 It is a schematic flow chart of another embodiment of the method for obtaining the cell survival fraction model based on different depths in the present invention;

[0035] Figure 5 It is a flow chart showing an implementation method of constructing a plurality of groups of fitting sample pairs at the current target depth in one embodiment of the present invention;

[0036] Figure 6 Shown is a schematic structural diagram of the cell survival experimental device in one embodiment of the present invention;

[0037] Figure 7 Shown is a schematic structural diagram of the cell survival experimental device of the present invention in another embodiment;

[0038] Figure 8 It is a schematic diagram of a process of adjusting the type and thickness of the moderator material of each layer in the present invention so that the dose distribution regulator can adapt to the corresponding target depth in an embodiment;

[0039] Fig. 9 It is a schematic diagram of the process of step S802 in one embodiment of the present invention;

[0040] Fig.10It is a schematic flow chart of a method for obtaining a total relative biological effect value based on boron neutron reaction according to the present invention in one embodiment;

[0041] Fig.11 Shown is a schematic diagram of the structure of the terminal in one embodiment of the present invention. DETAILED DESCRIPTION

[0042] The following describes the embodiments of the present application through specific examples, and those skilled in the art can easily understand other advantages and effects of the present application from the contents disclosed in this specification. The present application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways 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 without conflict.

[0043] It should be noted that in the following description, reference is made to the accompanying drawings, which describe several embodiments of the present application. It should be understood that other embodiments may be used, and mechanical, structural, electrical, and operational changes may be made without departing from the spirit and scope of the present application.

[0044] 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 "comprises", "includes", "includes" indicate the presence of the described features, operations, elements, components, items, kinds, and / or groups, but do not exclude the presence, occurrence, or addition of one or more other features, operations, elements, components, items, kinds, and / or groups. The terms "or" and "and / or" used herein are interpreted as inclusive, or mean any one or any combination.

[0045] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the technical solution in the embodiments of the present invention is further described in detail through the following embodiments and in combination 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 used to limit the invention.

[0046] In order to solve the technical problems existing in the prior art, the present application firstly 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.

[0047] 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 absorption 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.

[0048] It should be noted that the method for obtaining the cell survival fraction model provided in the present application can also be applied to the case where the number of target depths is single or multiple.

[0049] See also Figure 1 , showing a schematic flow chart of a method for acquiring the cell survival fraction model based on boron neutron reaction provided in the present application in one embodiment.

[0050] like Figure 1 As shown, the method comprises the following steps:

[0051] S100, collecting several groups of fitting sample pairs at the current target depth;

[0052] Wherein, the fitting sample pair is a sample data pair required for model fitting and solving the cell survival score model;

[0053] 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.

[0054] Specifically, in the cell survival experiment of 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:

[0055] 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.

[0056] In this embodiment, the number of groups of the fitting sample pairs is not less than the number of model parameters to be fitted in the cell survival score model; illustratively, when the number of model parameters to be fitted is 4, the number of groups of the fitting sample pairs constructed is not less than 4.

[0057] It should be noted that, in some specific embodiments, the number of the fitting sample pairs may be slightly smaller than the number of the model parameters; illustratively, when the number of parameters of the model parameters to be fitted is 4, the number of the fitting sample pairs constructed may also be 3.

[0058] S200, using each of the fitting sample pairs, fitting the model parameters in the initial cell survival fraction model to be fitted, so as to obtain a cell survival fraction model corresponding to the current target depth.

[0059] Specifically, each group of fitting sample pairs at the current target depth is input into the cell survival score 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 score model to obtain the cell survival score model at the current target depth.

[0060] The method for obtaining the cell survival score model provided in this embodiment obtains the cell survival score model by collecting multiple groups of fitting sample pairs and solving the cell survival score model based on the fitting sample pairs, which not only improves the efficiency of obtaining the cell survival score model, but also effectively improves the model accuracy of the cell survival score model.

[0061] 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.

[0062] More specifically, the initial model of cell survival fraction is:

[0063]

[0064] 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.

[0065] 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.

[0066] When the constructed cell survival fraction model does not take into account 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 have a certain difference from the true value, which in turn leads to the problem that the fitted cell survival fraction model still has problems such as insufficient accuracy; therefore, in order 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, in the preset cell survival fraction basic model, the synergistic parameters between the reaction particles are introduced to obtain the initial cell survival fraction model to be fitted.

[0067] 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 influence of repairable cell damage on the absorbed dose of various reaction particles.

[0068] 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; that is, the effect of the biological efficiency generated by a certain type of reaction particles (such as boron particles) in 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.

[0069] In a specific embodiment, the cell survival fraction basic model adopts the classic cell survival fraction model, which is:

[0070]

[0071] The synergy parameter is a geometric mean constructed based on the quadratic term coefficients and is:

[0072]

[0073] 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 reaction particle j (j-th type reaction particle).

[0074] In the classic cell survival fraction model, the synergistic parameter is introduced, and the introduced cell survival fraction model is logarithmized to obtain a new cell survival fraction model:

[0075]

[0076] Wherein, 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 coefficient of the first-order term corresponding to the first reaction particle i; β i represents the coefficient of the quadratic term 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.

[0077] Based on the new cell survival fraction model, it is determined that the model coefficients to be fitted include four linear coefficients (α 1 , α 2 , α 3 , α4 ) and the four quadratic coefficients (β 1 , β 2 , β 3 , β 4 ) has a total of 8 model coefficients, then the number of fitting sample pairs corresponding to each target depth is not less than 8.

[0078] It should be noted that, in other specific embodiments, the synergy coefficient may also be other mathematical expressions for characterizing the synergy effect between two types of reaction particles in terms of biological effects, such as Pearson correlation coefficient, Spearman correlation coefficient, etc.

[0079] 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 As shown, including:

[0080] S101, selecting a corresponding number of sample absorbed doses according to the number of the fitting sample pairs:

[0081] The absorbed dose of each sample is evenly distributed within the interval.

[0082] S102, collecting the cell survival fraction corresponding to the absorbed dose of each sample at the current target depth;

[0083] S103, constructing a fitting sample pair corresponding to the current depth based on the sample absorbed dose and the corresponding cell survival fraction.

[0084] In a specific implementation, when step S101 is executed, Figure 3 As shown, it includes the following sub-steps:

[0085] S101A, obtain the interval range of the mixed absorbed dose corresponding to the current target depth during the boron neutron reaction;

[0086] S101B, based on the number of the fitting sample pairs, dividing the interval range into a corresponding number of sub-intervals;

[0087] S101C, in each of the sub-intervals, extracting the average value of the mixed absorbed dose in the sub-interval as the sample absorbed dose corresponding to the sub-interval.

[0088] By extracting sample absorbed doses in different sub-intervals, the obtained sample absorbed doses are distributed more evenly in the interval range, thereby making the data distribution of the fitting sample pairs constructed based on the sample absorbed doses more even, avoiding the poor fitting effect caused by uneven data distribution, thereby improving the fitting accuracy of the cell survival score model.

[0089] In some optional embodiments, the acquisition of several groups of fitting sample pairs at the current target depth is based on acquisition obtained by a cell survival experimental device.

[0090] In the actual BNCT treatment process, the location of the tumor in the body is often different, that is, the depth of the radiation source is often different; for different radiation source depths, the paths traversed by various types of reaction particles in the boron neutron reaction are different, so the cell survival fraction corresponding to the same absorbed dose is often different, that is, the cell survival fraction models corresponding to different depths are different.

[0091] Therefore, in order to obtain the cell survival fraction models corresponding to different target depths, the present application also provides another method for obtaining the cell survival fraction models based on different depths, which is used to obtain the cell survival fraction models corresponding to different target depths.

[0092] See also Figure 4 , showing a schematic flow chart of a method for acquiring a cell survival score model based on different depths provided in the present application in one embodiment.

[0093] like Figure 4 As shown, the method includes:

[0094] S10, determining a neutron beam corresponding to each target depth;

[0095] Specifically, according to the depth value of the current target depth, the energy of the neutron flux corresponding to the current target depth is determined by utilizing the mapping relationship between the target depth and the neutron flux energy; and according to the energy, the corresponding neutron beam is output.

[0096] 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 of the target depths.

[0097] 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 of the target depths.

[0098] Exemplarily, when the target depth includes a first target depth H 1 , the second target depth H 2 and the third target depth H 3 When the first target depth H is collected, 1 Next n groups of first fitting sample pairs, second target depth H 2 Next n sets of second fitting sample pairs, and third target depth H 3 Next n groups of third fitting sample pairs;

[0099] Using the first target depth H 1 The n first fitting sample pairs under the condition are fitted to the model parameters in the initial model of the cell survival fraction to be fitted to obtain the first target depth H 1 The corresponding cell survival fraction model;

[0100] Using the second target depth H 2 The n groups of second fitting sample pairs under the condition of fitting the model parameters in the initial model of the cell survival fraction to be fitted are fitted to obtain the second target depth H 2 The corresponding cell survival fraction model;

[0101] and using the third target depth H 3 The n groups of third fitting sample pairs under the condition of fitting the model parameters in the initial model of the cell survival fraction to be fitted are fitted to obtain the third target depth H 3 The corresponding cell survival fraction model.

[0102] In some optional embodiments, for a single target depth, the implementation method of constructing several groups of fitting sample pairs at the current target depth is as follows: Figure 5 As shown, including:

[0103] S21, based on the cell survival experiment 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 the cell survival score of the boron-containing solution at each irradiation distance;

[0104] The irradiation distance is the distance between the boron-containing solution and the incident port of the neutron beam along the incident direction.

[0105] The irradiation distance corresponds to the sample absorbed dose, that is, different irradiation distances correspond to different sample absorbed doses.

[0106] 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 experiment device; the experimental results corresponding to each boron-containing solution are measured to obtain the cell survival scores corresponding to the absorbed doses of different samples.

[0107] S22, construct a fitting sample pair based on the sample absorbed dose and cell survival fraction corresponding to the same irradiation distance;

[0108] The above steps S21 to S22 are performed for each target depth, so as to obtain a fitting sample pair corresponding to each target depth.

[0109] In one embodiment, step S21 is performed based on a cell survival experiment device; see Figure 6 , which is a schematic diagram of the structure 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 .

[0110] The incident port 100 is disposed 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 .

[0111] The water mold 200 is used to load liquid, such as water.

[0112] The cell suspension tubes 300 are arranged in the water model at a certain interval and are connected to each other through the screw 400, so that when the screw is rotated, each cell suspension tube also rotates.

[0113] Using the cell survival experiment device, a cell survival experiment is performed on boron-containing solutions at different irradiation distances in the device, including:

[0114] The cells were cultured in a culture medium containing the second-generation boron drug BPA (the second-generation boron drug BPA was dissolved in Tris-HCl pH=8.0 buffer, and the buffer was added to a normal culture medium to obtain a culture medium) and placed in a CO 2 The cells are cultured in an incubator and used for experiments when they are in a logarithmic growth phase; the V79 cells in the logarithmic growth phase are moved to a cell suspension tube, and the front surface of the water model is used as the starting position. Based on a preset distance interval, the cell suspension tubes are 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 is 0.5 cm.

[0115] Fix the cell suspension tube containing cells on the rotating screw and set the speed to 3 rpm to keep the cells in suspension. Start irradiation. To avoid the influence of sublethal cell damage repair on the experimental results, set the irradiation time of each irradiation to be the same. After irradiation, count the cells in each cell suspension tube. Dilute the cells and inoculate them in a culture dish. 2 The cells were cultured in an incubator; formaldehyde was used to fix and stain the cells, and a cell imaging device was used to detect the cell survival rate to obtain the cell survival score corresponding to each of the cell suspension tubes.

[0116] In practical applications, since the parameters such as power, material and thickness of the neutron source accelerator that forms the neutron beam 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 score model corresponding to different target depths.

[0117] To solve this technical problem, in some specific embodiments, a cell survival experiment device with neutron source energy adjustment is used to perform step S21; Figure 7 As shown in Figure 2, the cell survival experimental setup is similar to Figure 6 The devices shown are basically the same, except that a neutron source regulator 500 is provided at the neutron incident port of the cell survival experiment device for regulating the energy of the neutron beam to obtain a neutron beam adapted to the target depth.

[0118] Furthermore, in order to improve the adjustment precision and accuracy of the neutron beam energy, the neutron source adjuster includes a dose distribution adjuster (Dose Distribution Shifter, DDS); the dose distribution adjuster is a structural component formed by stacking several layers of different types of moderation materials; by adjusting the type and thickness of each layer of moderation material, the dose distribution adjuster is adapted to the corresponding target depth.

[0119] 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 As shown, including:

[0120] Step S801 , randomly generating a plurality of initial dose distribution adjuster data, the initial dose distribution adjuster data including the material type of each layer and the thickness of each layer, and all the initial dose distribution adjuster data constitute an iterative data group.

[0121] 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 realize 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.

[0122] Based on the numbering of the current candidate materials, multiple groups of numbering groups are randomly generated, each group of numbering groups has multiple numbers, and then based on the candidate materials corresponding to the numbers in each group of numbering groups, the material distribution data corresponding to each group of numbering groups 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 numbering groups 1-3-5 are polyethylene, acrylic acid, and boron carbide. Based on experimental data, it can be seen that designing the number of material layers in the dose distribution regulator data as 3 layers is easier 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 numbering group. Then, the thickness of each material in each material distribution data is randomly generated within a preset range, and then the initial dose distribution regulator data corresponding to each material distribution data is obtained. Further, the preset range of the random thickness of each candidate material in each material distribution data can be set to 0-3cm. Each of the initial dose distribution adjuster 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 adjuster data, all the plurality of initial dose distribution adjuster data need to be combined into an iterative data set.

[0123] Step S802, iteratively optimizing the iterative data group by using a genetic algorithm to obtain an optimized iterative data group, and taking the dose distribution adjuster data with the smallest fitness value in the optimized iterative data group as a design scheme for the dose distribution displacement device.

[0124] like Fig. 9 As shown, step S802 specifically includes sub-step S8021 and step S8022.

[0125] Step S8021, obtaining the current iteration data group to obtain the new round of iteration data group.

[0126] Specifically, the current iterative data group is first used as the existing population in the genetic algorithm, and the fitness value of each dose distribution regulator data in the current iterative data group is first calculated, and then part of the dose distribution regulator data is screened out from the current iterative data group based on the fitness value in ascending order, and then the screened dose distribution regulator data is cross-mutated to obtain multiple dose distribution regulator data after cross-mutation. Secondly, the fitness value of all cross-mutated dose distribution regulator data is obtained, and on the basis of all dose distribution regulator data in the current iterative data group and all cross-mutated dose distribution regulator data, part of the dose distribution regulator data is screened out based on the fitness value in ascending order to form a new population, and the new population is used as a new round of iterative data group.

[0127] The cross-mutation of the selected dose distribution regulator data specifically includes: cross-mutating and mutating the material type of the selected dose distribution regulator data to obtain the dose distribution regulator data after the cross-mutation of the material type; and then cross-mutating and mutating the material thickness of the dose distribution regulator data after the cross-mutation of the material type to obtain multiple cross-mutated dose distribution regulator data. It should be noted that the material thickness of the dose distribution regulator data can also be cross-mutated first, and then the material type of the dose distribution regulator data can be cross-mutated.

[0128] The fitness value of the dose distribution regulator data is obtained in the following way: 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.

[0129] 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.

[0130] The specific fitness value is obtained based on the fitness function calculation. The fitness function expression of the programming software MATLAB is designed as:

[0131] OBJ=A·|D thermal-max -D tumor |+B·F thermal-max

[0132] Among them, OBJ represents the fitness value. The lower the fitness value, the closer the individual is to the set optimization target. A and B both represent weight factors. When optimizing different targets, the weight factors can be adjusted according to the importance of different optimization targets, and the weight factors can be set to negative numbers. |D thermal-max -D tumor | represents the distance between the depth of the maximum thermal neutron flux in the recipient body and the target depth in the center of the tumor, F thermal-max It represents the maximum thermal neutron flux value in the receptor body, which is obtained based on the outlet neutron energy spectrum of the beam shaper in the current BNCT device.

[0133] The fitness value of each dose distribution adjuster data in the current iteration data group and the fitness values ​​of all mutated dose distribution adjuster data are obtained in the above manner.

[0134] 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 the new round of iterative data group based on the current iterative data group.

[0135] 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 met the requirements. At this time, the newly acquired new round of iterative data group is 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 to that there exists 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 determined whether there exists 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 there is no dose distribution displacement device design scheme that meets the requirements in the new round of iteration data group. 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).

[0136] 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.

[0137] The method for acquiring a cell survival score model provided in this embodiment can use the same cell survival experimental device to realize the collection of sample absorbed doses and corresponding cell survival scores at different target depths, so as to quickly obtain each group of fitting sample pairs based on the collected sample absorbed doses and the corresponding cell survival scores, and then solve the cell survival score model based on the fitting samples; compared with the cumbersome operation of solving the models corresponding to different target depths in the prior art, the present application can quickly obtain a cell survival score model suitable for different target depths, which not only improves the acquisition efficiency of models at different target depths, but also effectively improves the model accuracy of the cell survival score model by using multiple groups of fitting sample pairs to solve the model.

[0138] 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.

[0139] 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 in the boron neutron reaction process.

[0140] Exemplarily, 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 the present 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.

[0141] See also Fig.10 , showing a schematic flow chart of a method for obtaining the total relative biological effect value based on boron neutron reaction provided in the present application in one embodiment.

[0142] like Fig.10 As shown, the method comprises the following steps:

[0143] S1, obtaining a cell survival fraction model corresponding to each target depth, and obtaining a reference model corresponding to each target depth;

[0144] The reference model is a cell survival fraction model corresponding to gamma rays, that is, a distribution of the relationship between the cell absorption dose corresponding to gamma rays and the cell survival fraction;

[0145] Specifically, after determining the number of target depths, any of the above methods for acquiring a cell survival fraction model is used to acquire a cell survival fraction model corresponding to each of the target depths; this process is the same as the implementation process in the above embodiment and will not be repeated here.

[0146] S2, for each target depth, respectively obtaining the mixed absorbed dose and the reference absorbed dose corresponding to the survival of the cells to be measured according to the survival fraction of the cells 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;

[0147] Among them, 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.

[0148] Specifically, for the first target depth H 1 , input the cell survival fraction M to be measured into the cell survival fraction model corresponding to the current target depth to obtain the corresponding mixed absorbed dose value D 1 ; and input the cell survival fraction M to be determined into the reference model corresponding to the current target depth to obtain the corresponding reference absorbed dose value D 0

[0149] Based on the mixed absorbed dose value D 1 and the reference absorbed dose value D 0 , get the first target depth H 1 The total RBE value under , is:

[0150] RBE 总1 =D 0 / D 1

[0151] Similarly, for the second target depth H 2 , get the second target depth H 2 The total RBE value under , is:

[0152] RBE 总2 =D 0 / D 2

[0153] The same goes for the rest, so I won’t go into details here.

[0154] It should be noted that, in the absence of conflict, the above embodiments and features in the embodiments may be combined with each other; for example, based on Figure 7 The cell survival experiment setup is shown. 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.

[0155] 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.

[0156] See also Fig.11 , is an optional hardware structure diagram of an electronic terminal 700 provided in an embodiment of the present invention. The electronic terminal 700 may be a live broadcast machine, a camera, a mobile phone, a computer device, a tablet device, a personal digital processing device, a factory background processing device, etc. that integrates photo / video functions. 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 through a bus system 705. It can be understood that the bus system 705 is used to realize the connection and communication between these components. In addition to the data bus, the bus system 705 also includes a power bus, a control bus and a status signal bus.

[0157] 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.

[0158] It is understood that the memory 702 can be a volatile memory or a non-volatile memory, and can also include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), which is used as an external cache. By way of exemplary but not limiting explanation, many forms of RAM are available, such as static random access memory (SRAM), synchronous static random access memory (SSRAM). The memory described in the embodiments of the present invention is intended to include but is not limited to these and any other suitable categories of memory.

[0159] 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 an operating system 7021 and an application 7022; the operating system 7021 includes various system programs, such as a framework layer, a core library layer, a driver layer, etc., for implementing various basic services and processing hardware-based tasks. The application 7022 can include various applications, such as a media player (MediaPlayer), a browser (Browser), etc., for implementing various application services. The method for obtaining the total relative biological effect value based on the boron neutron reaction of the embodiment of the present invention can be included in the application 7022.

[0160] The method disclosed in the above embodiment of the present invention can be applied to the processor 701, or implemented by the processor 701. The processor 701 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit in the processor 701 or the instruction in the form of software. The above processor 701 may be a general processor, a digital signal processor (DSP, Digital Signal Processor), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The processor 701 can implement or execute the various methods, steps and logic block diagrams disclosed in the embodiment of the present invention. The general processor 701 may be a microprocessor or any conventional processor, etc. In combination with the steps of the accessory optimization method provided in the embodiment of the present invention, it can be directly embodied as a hardware decoding processor to execute, or it can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium, which is located in a memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

[0161] In an exemplary embodiment, the electronic terminal 700 may be implemented by one or more application specific integrated circuits (ASIC), DSP, programmable logic device (PLD), complex programmable logic device (CPLD) to execute the aforementioned method.

[0162] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when called by a processor, implements the method for obtaining the total relative biological effect value based on boron neutron reaction provided by the present invention.

[0163] Among them, the computer-readable storage medium can be a tangible device that can hold and store instructions used by the 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 of the above. More specific examples of computer-readable storage media (a non-exhaustive list) 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 disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, and a mechanical encoding device.

[0164] 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 a network interface in each computing / processing device receives 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.

[0165] 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 execution order 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.

[0166] 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 familiar with 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 a person of ordinary skill in the art without departing from the spirit and technical concept disclosed by the present invention shall still 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, a mixed absorbed dose and a reference absorbed dose corresponding to the cell survival fraction to be measured are respectively obtained; Based on the mixed absorbed dose corresponding to each target depth and the reference absorbed dose, the total relative biological effect value of the mixed absorbed dose at the corresponding target depth is obtained; wherein, The method for obtaining the cell survival score model corresponding to each target depth includes: Collect several groups of fitting sample pairs at the current target depth; based on the fitting sample pairs at each target depth, solve the model parameters to be fitted in the initial model of the cell survival fraction to obtain the cell survival fraction model at each target depth; the fitting sample pairs include sample absorbed doses and cell survival fractions corresponding to the sample absorbed doses 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: Inputting the cell survival fraction to be determined into the cell survival fraction model corresponding to the current target depth to obtain a corresponding mixed absorbed dose value; and inputting the cell survival fraction into the reference model corresponding to the current target depth to obtain a corresponding reference absorbed dose value; Based on the mixed absorbed dose and the reference absorbed dose, the total relative biological effect value of the mixed absorbed dose at the corresponding target depth is obtained as follows: 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.

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 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.

4. The method for obtaining the total relative biological effect value based on boron neutron reaction according to claim 3, characterized in that: The cell survival score initial model is a model obtained by optimizing a preset cell survival score basic model based on the 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.

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 coefficient of the first-order term corresponding to the first reaction particle i, β i represents the coefficient of the quadratic term 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, is the coordination 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 solving the model parameters to be fitted in the initial model of the cell survival fraction based on the fitting sample pairs at each target depth, at a single target depth, includes: The fitting sample pairs of each group at the current target depth are respectively input into the initial model of the cell survival score; 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 model of the cell survival score to obtain the cell survival score 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: Using a neutron beam corresponding to the current target depth, a cell survival experiment is performed on the boron-containing solution at different irradiation distances in the cell survival experiment device to obtain the 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 each group of fitting sample pairs corresponding to the current target depth.

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 arranged 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 acquiring the neutron beam corresponding to the current target depth includes: The type and thickness of the moderation material of each layer in the dose distribution adjuster are adjusted so that the dose distribution adjuster is adapted to the current target depth, so as to obtain a neutron beam 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 executes the method for obtaining the total relative biological effect value based on boron neutron reaction as described in any one of claims 1 to 8.

10. A computer storage medium storing a computer program, characterized in that: 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.

Images