Boron drug transport simulation and neutron-boron drug transport coupling simulation method and medium

Abstract

The present application provides a coupled simulation method and medium for boron drug transport simulation and neutron-boron drug transport, the method comprising: setting a plurality of voxel grids and boron drug transport parameters; performing offline encoding on each voxel grid using the boron drug transport parameters to obtain a corresponding boron drug transport simulation model, the boron drug transport simulation model being used to predict the boron drug outflow rate and the boron drug concentration within the voxel grid based on radiation intensity, boron drug inflow rate, and radiation exposure time; obtaining a CT image of a target object, and matching the voxel grids according to the CT image to obtain a voxel model of the target object; obtaining the boron drug concentration within the voxel model based on the boron drug transport simulation model of all voxel grids in the voxel model. The present application can generate boron drug transport simulation models of various voxel grids offline, and directly couple each voxel grid based on the individual patient situation, quickly obtain the distribution of boron drug concentration in the patient's body, and fully consider the non-uniformity of boron drug transport.

Description

Technical Field

[0001] The present application belongs to the field of radiation technology and relates to a coupled simulation method and medium for boron drug transport simulation and neutron-boron drug transport. Background Art

[0002] Boron neutron capture therapy (BNCT), a highly promising cancer treatment, has garnered significant attention in recent years with the development of accelerators. Its principle is based on the high capture cross-section of 10B for thermal neutrons. When a boron-containing compound (boron drug) is specifically taken up by tumor cells, it is then irradiated with a thermal neutron beam. The 10B captures the thermal neutrons, triggering a nuclear reaction that produces high-energy alpha particles and 7Li nuclei. These particles have an extremely short range, only a few microns, meaning they damage only the tumor cells containing the 10B, with minimal impact on surrounding normal tissue. This unique therapeutic mechanism offers a highly precise approach to cancer treatment, potentially improving tumor treatment efficacy while significantly reducing side effects on normal tissue.

[0003] The Treatment Planning System (TPS) is a critical component of the entire boron neutron capture therapy (BNCT) process. In BNCT-TPS, accurate dose calculation is crucial for ensuring both treatment efficacy and safety. For example, precise dose calculation ensures that tumor tissue receives a sufficient therapeutic dose to completely eliminate tumor cells, while simultaneously keeping the dose to normal tissue within a safe range to avoid serious complications caused by excessive doses. However, in actual BNCT treatments, dose deficits can occur due to various factors, severely impacting further improvements in treatment efficacy. Therefore, generating accurate BNCT treatment plans based on these multiple factors is a pressing technical challenge for those skilled in the art. Summary of the Invention

[0004] The purpose of this application is to provide a coupled simulation method and medium for boron drug transport simulation and neutron-boron drug transport, so as to solve the technical problem of how to generate an accurate BNCT treatment plan based on multiple factors.

[0005] In a first aspect, the present application provides a boron drug transport simulation method, which is applicable to a BNCT treatment planning system, and comprises:

[0006] Setting a plurality of voxel grids and boron drug transport parameters, wherein the voxel grids correspond to various types of human tissue materials;

[0007] Offline encoding is performed on each voxel grid using the boron drug transport parameter to obtain a corresponding boron drug transport simulation model, wherein the boron drug transport simulation model is used to predict the boron drug outflow rate and the boron drug concentration within the voxel grid based on the radiation intensity, the boron drug inflow rate and the radiation exposure time;

[0008] Acquire a CT image of the target object, and match at least one of the voxel grids according to the CT image to acquire a voxel model of the target object;

[0009] The boron drug concentration in the voxel model is obtained based on a boron drug transport simulation model of all voxel grids in the voxel model.

[0010] In some embodiments of the first aspect of the present application, offline encoding each voxel grid using the boron drug transport parameter includes:

[0011] constructing a control equation for the voxel grid, wherein the control equation is established based on a computational fluid dynamics equation and a convection-diffusion-reaction equation;

[0012] Given different radiation intensities, boron drug inflow rates, and radiation exposure times for each voxel grid, and solving the control equation in combination with the boron drug transport parameters to obtain the corresponding boron drug outflow rates and boron drug concentrations within the voxel grid;

[0013] A boron drug transport simulation model for each voxel grid is offline encoded based on the given radiation intensity, the boron drug inflow rate, the radiation exposure time, the obtained boron drug outflow rate, and the boron drug concentration within the voxel grid.

[0014] In some embodiments of the first aspect of the present application, the method includes:

[0015] defining a boron drug inflow rate and a boron drug outflow rate in a two-dimensional phase space, wherein the two-dimensional phase space includes a three-dimensional spatial phase space and a time phase space;

[0016] In the three-dimensional phase space, the three-dimensional spatial distribution of the boron drug inflow rate is calculated based on quadrature discretization, so as to solve the control equation in combination with the boron drug transport parameter to obtain the corresponding three-dimensional spatial distribution of the boron drug outflow rate and the three-dimensional spatial distribution of the boron drug concentration;

[0017] In the time phase space, the time distribution of the boron drug inflow rate is calculated based on the asymptotic state approximation, so as to solve the control equation in combination with the boron drug transport parameters to obtain the corresponding time distribution of the boron drug outflow rate and the time distribution of the boron drug concentration.

[0018] In some embodiments of the first aspect of the present application, the boron drug transport parameters include the boron drug's characteristic diffusion coefficient, the body fluid characteristic flow rate, and the free boron conversion rate.

[0019] In a second aspect, the present application provides a coupled simulation method for neutron-boron drug transport, which is applicable to a BNCT treatment planning system, and comprises:

[0020] A plurality of voxel grids and boron drug transport parameters are set, and each voxel grid is offline encoded using the boron drug transport parameters to obtain a corresponding boron drug transport simulation model; the voxel grid corresponds to various types of human tissue materials; the boron drug transport simulation model is used to predict the boron drug outflow rate and the boron drug concentration within the voxel grid based on radiation intensity, boron drug inflow rate and radiation exposure time;

[0021] Offline encoding is performed on each voxel grid to obtain a corresponding physical coding layer, wherein the physical coding layer is used to predict a corresponding neutron outflow and neutron flux distribution based on a neutron incident flux and a boron dose concentration;

[0022] Acquire a CT image of the target object, and match at least one of the voxel grids according to the CT image to acquire a voxel model of the target object;

[0023] A physical coding layer of all voxel grids in the voxel model and a boron drug transport simulation model are bidirectionally coupled to obtain neutron flux distribution and boron drug concentration in the voxel model.

[0024] In some implementations of the second aspect of the present application, offline encoding each voxel grid to obtain a corresponding physical coding layer includes:

[0025] Customizing the neutron inflow and the neutron outflow in an eight-dimensional phase space; the eight-dimensional phase space includes a time phase space, an energy phase space, a three-dimensional angle phase space, and a three-dimensional space phase space;

[0026] Assigning different neutron incident flux and boron concentration to each voxel grid to correspondingly obtain the neutron outgoing flux and the neutron flux distribution in the eight-dimensional phase space;

[0027] The physical coding layer of each voxel grid is offline coded based on the given neutron incident flux and boron concentration and the corresponding neutron outgoing flux and neutron flux distribution.

[0028] In some embodiments of the second aspect of the present application, the method includes:

[0029] In combination with the eight-dimensional phase space definition of the neutron incident flow and the neutron outgoing flow, spatial integration is performed on the voxel grid to characterize the neutron transport process within the voxel grid as the relationship characteristic between the neutron incident flow and the neutron outgoing flow.

[0030] In some embodiments of the second aspect of the present application, bidirectional coupling between the physical coding layer and the boron drug transport simulation model based on all voxel grids in the voxel model includes:

[0031] Using the boron drug concentration output by the boron drug transport simulation model as an input to the physical coding layer, so as to perform online coupling on the physical coding layers of all the voxel grids and obtain the neutron flux distribution in the voxel model;

[0032] The neutron flux distribution output by the physical coding layer is used as an input of the boron drug transport simulation model to perform online coupling on the boron drug transport simulation models of all the voxel grids to obtain the boron drug concentration in the voxel model.

[0033] In some embodiments of the second aspect of the present application, the method includes:

[0034] Setting a voxel grid in the voxel model as an initial grid, and assigning radiation source information and a boron drug administration scheme to the initial grid, wherein the radiation source information includes a radiation intensity of a neutron source and a radiation irradiation time, and the boron drug administration scheme includes a boron drug inflow rate and a boron drug concentration;

[0035] Inputting the radiation intensity of the neutron source, the boron medicine inflow rate and the radiation irradiation time into the boron medicine transport simulation model of the initial grid to obtain the corresponding boron medicine outflow rate and boron medicine concentration;

[0036] Determining a neutron incident flux entering the initial grid based on the radiation intensity of the neutron source, and inputting the boron dose concentration and the neutron incident flux into the physical coding layer of the initial grid to obtain a corresponding neutron outgoing flux and neutron flux distribution;

[0037] Using the neutron flux distribution of the initial grid, the boron drug outflow rate of the initial grid, and the radiation exposure time as inputs of a next voxel grid, obtaining the corresponding boron drug outflow rate and boron drug concentration based on the boron drug transport simulation model of the next voxel grid, and in this way until all the voxel grids are traversed to obtain the boron drug concentration in the voxel model;

[0038] The neutron outflow flux of the initial grid and the boron concentration of the initial grid are used as inputs of the next voxel grid to predict the corresponding neutron outflow flux and neutron flux distribution based on the physical coding layer of the next voxel grid, so as to traverse all the voxel grids and obtain the neutron flux distribution in the voxel model.

[0039] In a third aspect, the present application provides a computer storage medium, wherein the computer program implements the method described above when executed by a processor.

[0040] As described above, the method and medium for coupled simulation of boron drug transport and neutron-boron drug transport provided in this application have the following beneficial effects:

[0041] First, this application innovatively proposes a boron drug transport simulation method under radiation conditions. In view of the complex mechanism of the boron drug transport process, a boron drug transport simulation model that specifically characterizes the heterogeneity of boron drug transport in voxel grids under radiation conditions is constructed in the "three-dimensional space-time" phase space. Based on the actual situation of the target object, each voxel grid is coupled to establish a personalized boron drug transport simulation mechanism, which can quickly obtain the boron drug concentration in the target object.

[0042] Secondly, this application innovatively proposes a dynamic neutron transport simulation method. In response to the complex mechanism of the neutron transport process, a physical coding layer that can specifically characterize the voxel grid particle transport heterogeneity is proposed in the eight-dimensional phase space of "time-energy-three-dimensional space-three-dimensional angle coupling", thereby enabling the rapid acquisition of the neutron flux distribution in the body based on the actual situation of the target object.

[0043] Finally, this application further proposes a transport coupling method that takes into account multiple factors of neutron-boron drug transport. Based on a full analysis of particle transport heterogeneity and boron drug transport heterogeneity, it further realizes the bidirectional coupling mechanism between the two, thereby being able to generate a more accurate BNCT treatment plan under the premise of considering multiple factors, thereby improving the accuracy and safety performance of BNCT dose assessment and accelerating the clinical promotion of BNCT.

[0044] In addition, this application innovatively proposes an offline encoding-online coupling technical solution, which can offline encode each voxel grid without considering the patient's individual situation, obtain a boron drug transport simulation model and physical coding layer at the voxel grid level, and directly perform online coupling and bidirectional coupling based on the individual diagnosis and treatment needs of different patients, thereby directly and quickly predicting the boron drug concentration and neutron flux distribution in the patient's body, and then generating a BNCT treatment plan. This application does not require the collection of a large amount of sample set case data, nor does it require repeated extensive pre-calculation and model training based on individual diagnosis and treatment needs, greatly improving the timeliness of generating BNCT treatment plans based on boron drug concentration and neutron flux distribution. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 Shown is a flow chart of the boron drug transport simulation method provided in an embodiment of the present application.

[0046] Figure 2 Shown is a flow chart of the boron drug transport simulation method provided in an embodiment of the present application.

[0047] Figure 3 Shown is a schematic diagram of a voxel grid provided by an embodiment of the present application.

[0048] Figure 4 Shown is a flow chart of the boron drug transport simulation method provided in an embodiment of the present application.

[0049] Figure 5 Shown is a schematic diagram of the distribution of N quadrature points in the three-dimensional angular phase space provided by an embodiment of the present application.

[0050] Figure 6 A schematic diagram showing the principle of obtaining a boron drug transport simulation model described in the examples of this application is shown.

[0051] Figure 7 Shown is a flow chart of the coupled simulation method for neutron-boron drug transport provided in an embodiment of the present application.

[0052] Figure 8 Shown is a flow chart of the coupled simulation method for neutron-boron drug transport provided in an embodiment of the present application.

[0053] Figure 9 Shown is a schematic diagram of the relationship between the three-dimensional angular phase space and the three-dimensional spatial phase space provided in an embodiment of the present application.

[0054] Figure 10 A schematic diagram showing the principle of obtaining the physical coding layer provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0055] 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.

[0056] 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 also be used, and that mechanical composition, structural, electrical, and operational changes may be made without departing from the spirit and scope of the present application. The following detailed description should not be considered restrictive, and the scope of the embodiments of the present application is limited only by the claims of the published patents. The terms used herein are only for describing specific embodiments and are not intended to limit the present application. Spatially related terms, such as "upper", "lower", "left", "right", "below", "below", "lower", "above", "upper", etc., may be used in the text to facilitate the description of the relationship between an element or feature shown in the figure and another element or feature.

[0057] Furthermore, 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 the 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.

[0058] During BNCT treatment, accurate dose calculation is crucial for ensuring both therapeutic efficacy and safety. However, in actual BNCT treatment, dose deficits can occur due to a variety of factors, severely impacting further improvements in treatment effectiveness. Among these factors, "particle transport heterogeneity" is a key factor. When neutrons propagate through human tissue, the particle transport process is influenced by independent variables such as three-dimensional space, angle, energy, and time, taking into account factors such as the complexity of the tissue's composition and structure. Neutron scattering and absorption can vary. For example, in dense tissues like bone, the probability of neutron scattering increases, leading to an uneven distribution of neutron flux. This results in differences in the neutron dose received by different parts of the tumor tissue, and some tumor regions may not receive an adequate therapeutic dose.

[0059] Furthermore, the heterogeneity of boron drug delivery cannot be ignored. The distribution of boron drugs in the body is not ideally uniform. Factors such as vascularity and cellular metabolic activity within tumor tissue can affect boron drug uptake and distribution. Insufficient vascular perfusion in some tumor regions may result in low boron drug concentrations, preventing effective neutron capture reactions and causing dose loss. Furthermore, BNCT features bidirectional neutron-boron drug targeting, and neutron targeting can affect boron drug distribution. These factors can significantly impact the therapeutic efficacy of BNCT.

[0060] Currently, to accurately adapt treatment plans to patients' real-time conditions, the "integrated diagnosis and treatment" clinical strategy is gaining increasing attention. This strategy emphasizes the close integration of the diagnostic and treatment processes. To this end, existing technologies utilize artificial intelligence methods to rapidly and data-drivenly obtain the neutron flux distribution within the patient's body to generate BNCT treatment plans. However, this approach only analyzes the cause of particle transport inhomogeneity and does not consider the factor of boron drug transport inhomogeneity, which affects the accuracy of BNCT treatment plan generation. In addition, this type of method has poor generalization capabilities. To improve analysis accuracy and generalization capabilities, a large amount of sample data must be prepared to train the model. However, if the actual patient situation differs significantly from the sample set cases, it is impossible to obtain a more accurate analysis result using the existing model, and a large amount of pre-calculation and model training must be performed again, which greatly affects the timeliness of BNCT treatment plan generation.

[0061] In order to at least solve the above-mentioned technical problems, the present application provides a coupled simulation method and medium for boron drug transport simulation and neutron-boron drug transport, which can quickly simulate the boron drug transport process in the target object. On the basis of considering the boron drug distribution, it further combines the neutron transport factor to realize the coupled simulation method of neutron-boron drug transport, thereby being able to quickly predict the boron drug concentration and neutron flux distribution in different target objects, thereby providing a basis for accurately calculating the BNCT dose and improving the accuracy and timeliness of BNCT treatment plan generation.

[0062] Figure 1 The flow chart of the boron drug transport simulation method provided in the embodiment of the present application is shown. The neutron transport simulation method provided in the present application is applicable to the BNCT treatment planning system to quickly generate a BNCT treatment plan. Figure 1 As shown, the neutron transport simulation method includes steps S1 to S3.

[0063] S1. Setting a plurality of voxel grids and boron drug transport parameters, wherein the voxel grids correspond to various types of human tissue materials.

[0064] In some embodiments, various human tissue materials are constructed using the human tissue material element database published by the International Commission on Radiation Units and Measurements (ICRU), and each type of human tissue material is set as a voxel grid. For example, if there are N types of human tissue material grids, then N corresponding voxel grids are set.

[0065] In some embodiments, the boron drug transport parameters include a boron drug diffusion coefficient, a body fluid flow rate, and a free boron conversion rate. Given boron drug transport parameters, a voxel-based boron drug transport simulation model can be effectively established.

[0066] The characteristic diffusion coefficient of a boron drug is a physical quantity that measures the drug's diffusion capacity. It is affected by the size, shape, polarity, and other properties of the drug molecule, and is also related to the internal environment, such as the viscosity and temperature of tissue fluids. The characteristic flow rate of body fluids refers to the speed at which body fluids circulate and flow within the body, reflecting the flow of body fluids in vessels such as blood vessels and lymphatic vessels. The free boron conversion rate refers to the rate at which boron is converted from one chemical form to another within the body, reflecting the metabolic processes and chemical reaction rates of boron within the body.

[0067] It should be noted that the values ​​of the boron drug transport parameters are determined by those skilled in the art, and this application is not limited thereto.

[0068] S2. Offline encoding is performed on each voxel grid using the boron drug transport parameters to obtain a corresponding boron drug transport simulation model, wherein the boron drug transport simulation model is used to predict the boron drug outflow rate and the boron drug concentration within the voxel grid based on radiation intensity, boron drug inflow rate and radiation exposure time.

[0069] In order to quickly obtain the boron drug transport process and boron drug concentration distribution in the target object, this application offline encodes each voxel grid to obtain the corresponding boron drug transport simulation model, thereby predicting the boron drug outflow rate and boron drug concentration within the voxel grid based on the given radiation intensity, boron drug inflow rate and radiation exposure time. In the process of establishing the boron drug transport simulation model, this application takes into account the boron drug transport mechanism under radiation conditions, making the simulation of the boron drug transport process more accurate. Figure 2 The flow chart of the boron drug transport simulation method provided in the embodiment of the present application is shown. Figure 2 As shown, the offline encoding of each voxel grid using the boron drug transport parameters includes steps S21 to S23.

[0070] S21. Constructing a control equation of the voxel grid, wherein the control equation is established based on a computational fluid dynamics equation and a convection-diffusion-reaction equation.

[0071] Figure 3 Shown is a schematic diagram of a voxel grid provided by an embodiment of the present application. Figure 3 As shown, when the boron drug enters the voxel grid, it will be transported within the voxel grid. When free boron reacts chemically with the biomolecules within the voxel grid, bound boron is formed. That is, during the transport of the boron drug within the voxel grid, free boron and bound boron will be converted to each other. Furthermore, in the embodiments of the present application, the conversion between free boron and bound boron is considered to be in dynamic equilibrium, i.e., the change in boron drug concentration caused by the conversion of bound boron to free boron is not considered.

[0072] Based on this, this application combines the computational fluid dynamics (CFD) model with the convection / diffusion / reaction (CDR) model to construct the control equation of the voxel grid, thereby characterizing the transport process of boron drugs within the voxel grid under radiation conditions.

[0073] Specifically, the control equation of the voxel grid under radiation conditions is shown in formula (1).

[0074]

[0075] Among them, r is three-dimensional space, t is time, is the free boron concentration (mol / m 3 ), the first term on the left side of the equation is the relationship between the free boron concentration and time (t), and the unit is (mol / m3·s.).

[0076] Where D is the characteristic diffusion coefficient of the boron drug (m 2 / s), reflecting the diffusion ability of boron drug in the medium. is the Laplace operator of the free boron concentration (mol / m 5 ), the unit after multiplying it by D is mol / (m 3 ·s).

[0077] in, is the free boron concentration gradient (mol / m 4 ), v is the flow rate of body fluid, and the unit after multiplying the two is mol / (m 3 ·s).

[0078] Where k is the free boron conversion rate, which represents the conversion ratio of free boron per unit time. The unit is mol / (m 3 ·s).

[0079] in, The unit is mol / (m 3 s), is the neutron flux; is the absorption cross section of boron. All the dimensions in the formula are NL −3 T −1 .

[0080] As shown in Equation (1), the left side represents the change in boron concentration over time. The first term on the right side is the diffusion term, which is used to characterize the transfer of boron drug from high concentration to low concentration within the voxel grid. The second term is the convection term, which is used to characterize the change in boron drug concentration caused by the flow of boron drug with body fluids. The third term is the elimination term, which is used to characterize the change in boron drug concentration caused by body metabolism. The fourth term is the radiation consumption term. In fact, by constructing the governing equations of the voxel grid, it is possible to characterize the influence of diffusion, convection, elimination, and radiation consumption on the transport process of boron drug within the voxel grid, providing a solid foundation for the establishment of a simulation model of boron drug transport under radiation conditions.

[0081] S22. Give each voxel grid a different radiation intensity, the boron drug inflow rate and the radiation irradiation time, and solve the control equation in combination with the boron drug transport parameters to obtain the corresponding boron drug outflow rate and the boron drug concentration in the voxel grid.

[0082] In some embodiments, in order to achieve a rapid response of the boron drug transport simulation model based on a voxel grid to a given radiation intensity, the boron drug inflow rate, and the radiation exposure time, so as to predict the corresponding boron drug outflow rate and the boron drug concentration within the voxel grid, the present application processes Equation (1) to characterize the boron drug transport process within the voxel grid as the characteristic relationship between the boron drug inflow rate and the boron drug outflow rate. The boron drug inflow rate is characterized by the boron drug concentration entering the voxel grid from the surface, and the boron drug outflow rate is characterized by the boron drug concentration diffused out of the voxel grid from the surface.

[0083] Specifically, the boron drug inflow rate is defined as:

[0084]

[0085] The boron drug elution rate is defined as:

[0086]

[0087] The unit of boron inflow rate and boron outflow rate is mol / (m 2 ·s), the units of the two terms on the right side of the equation are also mol / (m 2 ·s), dimension is NL -2 T -1 . And the negative sign in the formula indicates that the diffusion direction of the boron drug is opposite to the direction of the concentration gradient.

[0088] Where n is the unit normal vector of the voxel grid surface, and the normal direction points to the outside of the voxel grid.

[0089] Combining the above definition, we can spatially integrate Equation (1) within the internal region m of a certain voxel grid to obtain Equation (2):

[0090]

[0091] According to Green's second formula, we can get formula (3):

[0092]

[0093] The negative sign on the right side of formula (3) also indicates that the diffusion direction of the boron drug is opposite to the direction of the concentration gradient.

[0094] According to Gauss's formula, we can get formula (4):

[0095]

[0096] The final control equation of the voxel grid is shown in Equation (5):

[0097]

[0098] The units of the first and second terms on the left and right sides of the equation are both mol / (m 3 ·s), after triple integration in space, the unit is mol / s, and the dimension is NT -1 .

[0099] Then, it can be seen from formula (5) that the boron drug transport process in each voxel grid can actually be characterized by the characteristic relationship between the boron drug inflow rate and the boron drug outflow rate in the voxel grid. That is, when simulating the boron drug transport process under radiation conditions based on formula (5), it can actually be used To characterize the boron drug transport process, and based on this, the boron drug concentration is obtained. By simulating the boron drug transport process in two-dimensional phase space based on Equation (5), the temporal and spatial distribution of the boron drug can be comprehensively considered to determine the boron drug concentration and further determine the boron drug efflux rate.

[0100] S23. Offline encode the boron drug transport simulation model of each voxel grid based on the given radiation intensity, the boron drug inflow rate, the radiation exposure time, the obtained boron drug outflow rate, and the boron drug concentration within the voxel grid.

[0101] As mentioned above, from formula (5), it can be seen that the boron drug transport process within the voxel grid can be characterized as the characteristic relationship between the boron drug inflow rate and the boron drug outflow rate within the voxel grid. At this time, given different radiation intensities, boron drug inflow rates, and radiation exposure times for each voxel grid, and combined with the values ​​of the preset boron drug transport parameters, a set of algebraic equations can be constructed based on formula (5) to solve the corresponding boron drug outflow rate and the boron drug concentration within the voxel grid. At this time, a pre-trained model can be trained using a large amount of given input data and corresponding acquired input data to obtain a boron drug transport simulation model, so that the voxel grid can quickly respond to the given radiation intensity, boron drug inflow rate, and radiation exposure time based on the model to predict the corresponding boron drug outflow rate and the boron drug concentration within the voxel grid. In addition, the construction of the boron drug transport simulation model can be explained based on formula (5), reflecting that the non-uniformity of boron drug transport is fully considered during the construction process, and the interpretability is strong.

[0102] Among them, the pre-trained model is a neural network model, and this application does not impose any restrictions on the model type.

[0103] Figure 4 The flow chart of the boron drug transport simulation method provided in the embodiment of the present application is shown. Figure 4 As shown, different radiation intensities, boron drug inflow rates and radiation irradiation times are given to each voxel grid, and the control equation is solved in combination with the boron drug transport parameters to obtain the corresponding boron drug outflow rate and the boron drug concentration in the voxel grid, including steps S221 to S223.

[0104] S221. Define the boron drug inflow rate and the boron drug outflow rate in a two-dimensional phase space, wherein the two-dimensional phase space includes a three-dimensional spatial phase space and a time phase space.

[0105] As mentioned above, the boron drug inflow rate and boron drug outflow rate are customized in the two-dimensional phase space to reflect the changes in the spatiotemporal distribution of the boron drug concentration during the transportation process.

[0106] S222. In the three-dimensional phase space, the three-dimensional spatial distribution of the boron drug inflow rate is calculated based on quadrature discretization, so as to solve the control equation in combination with the boron drug transport parameters to obtain the corresponding three-dimensional spatial distribution of the boron drug outflow rate and the three-dimensional spatial distribution of the boron drug concentration.

[0107] In some embodiments, S N The discrete calculation is performed at the quadrature point to obtain the integral value of the three-dimensional angle phase space, that is, the three-dimensional spatial distribution of the boron drug concentration within the voxel grid. Figure 5As shown, N classical quadrature points are selected in the three-dimensional angular phase space to obtain the distribution function value of the boron drug in each discrete angular direction, and the distribution function values ​​in all discrete angular directions are integrated using formula (6) to approximately obtain the integral value of the three-dimensional angular phase space, that is, the three-dimensional spatial distribution of the boron drug concentration.

[0108]

[0109] Based on this, the formula (5) can be solved by combining the preset boron drug transport parameter values ​​with the given input radiation intensity and radiation irradiation time to obtain the corresponding three-dimensional spatial distribution of the boron drug outflow rate and the three-dimensional spatial distribution of the boron drug concentration.

[0110] S223. In the time phase space, the time distribution of the boron drug inflow rate is calculated based on the asymptotic state approximation, so as to solve the control equation in combination with the boron drug transport parameters to obtain the corresponding time distribution of the boron drug outflow rate and the time distribution of the boron drug concentration.

[0111] In some embodiments, in the time phase space, the time distribution of the boron drug inflow rate is discretely calculated based on the asymptotic state approximation to obtain the corresponding time distribution of the boron drug concentration. That is, in the time dimension, the time derivative term of the asymptotic state approximation processing formula is used to obtain the change of the boron drug concentration in the time phase space over time. Among them, the time derivative term of the asymptotic state approximation processing formula generally refers to the processing method of the time derivative part when the time-dependent differential equation is discretized or approximated. In some embodiments, the time distribution of the boron drug inflow rate is generally discretely calculated at a time interval of 1% of the treatment time. For example, the forward Euler format can be used for discrete calculations.

[0112] Based on this, the preset boron drug transport parameter values ​​and the given input radiation intensity and radiation irradiation time can be combined to solve Equation (5) to obtain the corresponding time distribution of the boron drug outflow rate and the time distribution of the boron drug concentration.

[0113] Figure 6 The schematic diagram of the principle of obtaining the boron drug transport simulation model described in one embodiment of the present application is shown. Figure 6 As shown in the figure, for each voxel grid, different radiation intensities, boron inflow rates, and radiation exposure times are input. Under the radiation conditions, the boron transport process within the voxel grid is simulated based on the governing equation to obtain the corresponding boron outflow rate and boron concentration. In this way, the model is trained based on the given inputs and corresponding outputs, and the required boron transport simulation model is ultimately obtained, thereby enabling the rapid prediction of the corresponding boron outflow rate and boron concentration based on the given radiation intensity, boron inflow rate, and radiation exposure time.

[0114] S3. Acquire a CT image of the target object, and match at least one voxel grid according to the CT image to acquire a voxel model of the target object.

[0115] S4. Obtaining the boron drug concentration in the voxel model based on the boron drug transport simulation model of all voxel grids in the voxel model.

[0116] Specifically, after a boron drug transport simulation model is constructed for each voxel grid, its voxel model can be obtained based on the specific information of the target object, and the boron drug transport simulation models of all voxel grids in the voxel model can be online coupled to obtain the boron drug concentration in the voxel model.

[0117] In some embodiments, obtaining a CT image of the target object and matching at least one of the voxel grids according to the CT image to obtain a voxel model of the target object includes: obtaining a CT image of the target object, determining a cancerous area in the CT image, thereby matching at least one corresponding voxel grid, and obtaining the voxel model of the target object through the matched voxel grid.

[0118] Furthermore, the cancerous region can actually be composed of multiple voxel grids, meaning that a voxel grid is an even smaller unit of division. For example, based on CT images, the cancerous region can be determined to be the target subject's brain. Since the brain is composed of multiple tissue materials, this region is matched to multiple voxel grids. In other embodiments, a specific cancerous region may be sufficiently precise, in which case a single voxel grid is matched. Furthermore, the voxel model of the target subject can also include voxel grids corresponding to the cancerous region and voxel grids of normal regions. In other words, all voxel grids are matched according to the various tissue materials of the target subject to form the voxel model.

[0119] For example, step S1 sets N voxel grids, and the voxel model of a target object is composed of M voxel grids (M is not greater than N). Then, the boron drug transport simulation models of the M voxel grids can be coupled, and the corresponding boron drug outflow rate and boron drug concentration can be predicted by the boron drug transport simulation models of the M voxel grids. Then, based on the boron drug concentration in all voxel grids, the boron drug concentration in the voxel model of the target object can actually be obtained.

[0120] In some embodiments, obtaining the boron drug concentration in the voxel model based on the boron drug transport simulation model of all voxel grids in the voxel model includes steps S41 to S43.

[0121] S41. Set a voxel grid in the voxel model as an initial grid, and assign a radiation intensity, a boron medicine inflow rate, and a radiation irradiation time to the initial grid.

[0122] S42. Predicting the corresponding boron drug outflow rate and boron drug concentration based on the boron drug transport simulation model of the initial grid.

[0123] S43. Use the boron drug outflow rate of the initial grid as the boron drug inflow rate of the next voxel grid, and predict the corresponding boron drug outflow rate and boron drug concentration based on the boron drug transport simulation model of the next voxel grid, until all the voxel grids are traversed.

[0124] For example, the voxel model of a target object is composed of M voxel grids. Given the boron drug outflow rate J set in the treatment plan, in1 , and set the pixel grid M1 as the initial grid. in1 Input into M1 to predict the corresponding boron drug outflow rate J through the boron drug transport simulation model of M1 out1 and the boron drug concentration in M1, the boron drug effluent rate J of M1 out1 The boron drug inflow rate of the next voxel grid M2 is used to predict the corresponding boron drug outflow rate J through the boron drug transport simulation model of M2. out2 and the boron drug concentration in M2, and so on until all the voxel grids are traversed to obtain the boron drug concentration in all voxel grids, that is, the boron drug concentration in the voxel grid.

[0125] Therefore, without the need to know any information about the patient in advance, the present application can generate a boron drug transport simulation model of a voxel grid offline, thereby quickly simulating the transport process of the boron drug within the voxel grid, and ultimately obtaining the boron drug outflow rate and the boron drug concentration within the voxel grid. Moreover, the boron drug transport simulation model based on the voxel grid can quickly couple the voxel grid according to the individual situation of the target object, thereby quickly obtaining the boron drug distribution in the target object's body based on the consideration of the heterogeneity of boron drug transport.

[0126] The embodiments of the present application also provide a coupled simulation method for neutron-boron drug transport, which is applicable to a BNCT treatment planning system. Figure 7 The flow chart of the coupled simulation method of neutron-boron drug transport provided in the embodiment of the present application is shown. Figure 7 As shown, the method includes steps S5 to S8.

[0127] S5. Setting a plurality of voxel grids and boron drug transport parameters, and performing offline encoding on each voxel grid using the boron drug transport parameters to obtain a corresponding boron drug transport simulation model.

[0128] As previously described, multiple voxel grids are set up, and a boron drug transport simulation model is obtained for each voxel grid, referring to the aforementioned embodiments. The voxel grids correspond to various types of human tissue materials, and the boron drug transport simulation model is used to predict the boron drug outflow rate and boron drug concentration within the voxel grid based on radiation intensity, boron drug inflow rate, and radiation exposure time.

[0129] S6. Offline encoding is performed on each voxel grid to obtain a corresponding physical coding layer, where the physical coding layer is used to predict the corresponding neutron outgoing flux and neutron flux distribution based on the neutron incident flux and boron concentration.

[0130] Specifically, offline coding involves constructing a physical coding layer for each voxel grid directly from a large amount of universal data, without requiring any prior knowledge of the patient. This layer allows for rapid simulation of neutron transport within the voxel grid, given a given neutron flux and boron concentration, to predict the corresponding neutron outflow and neutron flux distribution. The neutron flux distribution is essentially the distribution of neutron flux across different phase space dimensions, representing the complete state of the neutron flux in phase space.

[0131] like Figure 8 As shown, performing offline encoding on each voxel grid to obtain a corresponding physical coding layer includes steps S61 to S63.

[0132] S61. Customize the neutron incident flow and the neutron outgoing flow in an eight-dimensional phase space; the eight-dimensional phase space includes a time phase space, an energy phase space, a three-dimensional angle phase space, and a three-dimensional space phase space.

[0133] Specifically, the neutron incident flux is defined as , and the neutron incident flow is located on the voxel grid surface and the angle between the neutron motion direction and the normal direction is greater than 90 degrees, the neutron outflow is defined as , and the neutron outflow is located on the surface of the voxel grid and the angle between the neutron motion direction and the normal direction is less than 90 degrees. In addition, the internal area of ​​the voxel grid is denoted as m, and the surface is denoted as S.

[0134] When the neutron incident flow enters the voxel grid, the transport process of the neutron beam in the voxel grid can actually be expressed by the dynamic particle transport equation, as shown in Equation (7):

[0135]

[0136] Where, t is time; r is three-dimensional space; is the three-dimensional angle; E is the particle energy.

[0137] The first term on the left side of the equation represents the rate of change of the neutron flux over time, divided by the neutron velocity v. It reflects the degree of change in the neutron flux with a specific energy E and moving along the direction Ω per unit volume per unit time, taking into account the time accumulation effect caused by the neutrons moving at the velocity v. Neutron flux , v is the neutron velocity (cm·s −1 ).

[0138] The second term on the left side of the equation is the convection term, which represents the change of neutrons in space due to their own motion (moving along the direction Ω at a speed v), that is, the influence of the spatial transport process on the neutron flux. The unit is .

[0139] Among them, the third term on the left side of the equation represents the collision removal term. is the total cross section (cm -1 ), which represents the combined probability of a neutron deviating from its original direction and energy state due to various interactions with the medium (such as absorption and scattering). Multiplying this probability by the neutron flux represents the reduction in the number of neutrons of a specific energy and direction per unit volume due to various interactions, such as collisions.

[0140] The first term on the right side of the equation is the scattering term, and its integration is performed over all possible incident energies E' and incident directions Ω'. is the scattering cross section , which means that within a unit volume, the neutrons have an energy of E ', direction Ω' scattered to energy E The probability of Ω in the direction Ω, which is multiplied by the neutron flux and then integrated and summed, can obtain the number of neutrons with the current energy and direction produced by scattering.

[0141] The second term on the right side of the equation Exogenous term , i.e., the BNCT neutron source, represents the number of neutrons produced per unit volume at position r, energy E, direction Ω, and time t.

[0142] The first term on the left side of Equation (7) is the rate of change of neutrons over time, the second term is the neutron leakage rate, and the third term is the neutron absorption rate. The right side of the equation is the neutron production rate, of which the first term is the neutron source; the second term is the scattered neutron production rate. In fact, Equation (7) represents the dynamic transport process of neutrons. According to Equation (7), it can be seen that the neutron flux is affected by neutron leakage, interaction losses with boron charge (total cross section and scattering cross section), scattering, and source terms. Solving Equation (7) can simulate the neutron transport process and thereby obtain the neutron flux distribution and neutron outflow.

[0143] Combining the above-mentioned eight-dimensional phase space definition of the neutron inflow and neutron outflow, a spatial integration is performed on the voxel grid to characterize the neutron transport process within the voxel grid as the characteristic relationship between the neutron inflow and the neutron outflow. That is, combining the above definition and spatially integrating Equation (7) within the interior region m of a certain voxel grid, we obtain Equation (8):

[0144]

[0145] That is, from Equation (8), we can know that the dynamic transport process of neutrons in each voxel grid can actually be expressed as the characteristic relationship between the neutron incident flow and the neutron outgoing flow in the voxel grid, that is, .

[0146] in, Figure 9 The figure shows the relationship between the three-dimensional angular phase space and the three-dimensional spatial phase space provided by the embodiments of the present application. By simulating the neutron transport process within the voxel grid based on Equation (8) in the eight-dimensional phase space, the influence of various variables on the dynamic transport process of neutrons within the voxel grid can be comprehensively considered, thereby obtaining the neutron flux distribution and neutron outflow corresponding to the neutron incident flux and boron concentration in the eight-dimensional phase space, making it possible to more accurately simulate the neutron transport process within the voxel grid.

[0147] S62. Assign different neutron incident fluxes and boron concentrations to each voxel grid to correspondingly obtain the neutron outgoing flux and the neutron flux distribution in the eight-dimensional phase space.

[0148] S63. Offline encode the physical coding layer of each voxel grid based on the given neutron incident flux and boron concentration and the corresponding neutron outgoing flux and neutron flux distribution.

[0149] Specifically, giving different neutron incident fluxes and boron concentrations to each voxel grid to correspondingly obtain the neutron outgoing flux and the neutron flux distribution in the eight-dimensional phase space includes: simulating the neutron transport process within the voxel grid based on the eight-dimensional phase space distribution of the neutron incident flux and the two-dimensional phase space distribution of the boron concentration to obtain the eight-dimensional phase space distribution of the neutron outgoing flux and the eight-dimensional phase space distribution of the neutron flux; wherein the neutron transport process is characterized by the characteristic relationship between the neutron incident flux and the neutron outgoing flux.

[0150] As mentioned above, from Equation (8), it can be seen that the dynamic neutron transport process within the voxel grid can be characterized as the characteristic relationship between the neutron incident flux and the corresponding neutron outgoing flux. At this time, the neutron transport process within the voxel grid can be simulated in the eight-dimensional phase space based on the spatiotemporal distribution of the neutron incident flux under the boron concentration by the Monte Carlo method, so as to obtain the eight-dimensional phase space distribution of the neutron outgoing flux and the eight-dimensional phase space distribution of the neutron flux. And based on Equation (8), it can be seen that the neutron transport process can be characterized as the characteristic relationship between the neutron incident flux and the neutron outgoing flux. At this time, the Monte Carlo method can be used to obtain a large number of neutron outgoing fluxes and neutron flux distributions, and the given neutron incident flux, boron concentration and corresponding neutron outgoing flux and neutron flux distribution are used to train the input-output prediction model of the voxel grid, that is, to construct a physical coding layer, so that the voxel grid can quickly respond to the given neutron incident flux to predict the corresponding neutron outgoing flux and neutron flux distribution. Moreover, the construction process of the physical coding layer, that is, the neutron transport process within each voxel grid, can be explained based on Equation (8), which is highly interpretable.

[0151] Among them, the input-output prediction model is a neural network model, and this application does not impose any restrictions on the model type.

[0152] In some embodiments, in the time phase space, the time distribution of the neutron incident flow is discretely calculated based on the asymptotic state approximation to obtain the time distribution of the neutron outflow and the time distribution of the neutron flux. That is, in the time dimension, the time derivative term of the asymptotic state approximation formula is used to obtain the change of the neutron flux with time in the time phase space, that is, to obtain the time distribution of the neutron flux and the time distribution of the neutron outflow. Among them, the time derivative term of the asymptotic state approximation formula generally refers to the way of processing the time derivative part when discretizing or approximating the time-dependent differential equation. In some embodiments, the time variable of the neutron incident flow is discretely calculated, usually at a time interval of 1% of the treatment time. For example, the forward Euler format can be used for discrete calculation.

[0153] In some embodiments, the energy distribution of the neutron inflow is discretized in energy phase space based on a cluster approximation to obtain the energy distribution of the neutron outflow and the energy distribution of the neutron flux. That is, in the energy dimension, a "cluster approximation" approach is used for discretization, assuming that within a certain energy range, the neutron flux does not change, and thus the energy distribution of the neutron outflow will also not change.

[0154] In some implementations, in a three-dimensional angular phase space, the three-dimensional angular distribution of the neutron incident flow is discretely calculated based on quadrature discretization to correspondingly obtain the three-dimensional angular distribution of the neutron outflow and the three-dimensional angular distribution of the neutron flux.

[0155] In some embodiments, in the three-dimensional phase space, the three-dimensional spatial distribution of the neutron incident flow is discretely calculated based on quadrature discretization to obtain the three-dimensional spatial distribution of the neutron outflow and the three-dimensional spatial distribution of the neutron flux respectively.

[0156] For the three-dimensional angular phase space, the SN quadrature point can be used for discrete calculation to obtain the integral value of the three-dimensional angular phase space, that is, the three-dimensional angular distribution of the neutron flux in the voxel grid, and the three-dimensional angular distribution of the neutron outflow can be simulated using Monte Carlo. In some embodiments, Figure 5 As shown in Figure 1, N classical quadrature points are selected in the three-dimensional angular phase space to obtain the distribution function value of neutrons in each discrete angular direction. Then, the distribution function values ​​in all discrete angular directions are integrated using Equation (6) to approximately obtain the integral value of the three-dimensional angular phase space, that is, the angular distribution of the neutron flux.

[0157] Among them, for the three-dimensional phase space, discrete calculations are performed according to the integration points of the classical multidimensional plane. Similarly, solving Equation (6) in the form of weighted summation can approximate the integral value of the three-dimensional phase space, that is, the three-dimensional spatial distribution of the neutron flux, and the three-dimensional spatial distribution of the neutron outflow is simulated using Monte Carlo.

[0158] Figure 10 The schematic diagram of the principle of obtaining the physical coding layer described in one embodiment of the present application is shown. Figure 10 As shown, for each voxel grid, different boron concentrations and neutron incident fluxes are input, and the Monte Carlo method is used to simulate the neutron transport process based on the boron distribution in the voxel grid to obtain the corresponding neutron outflow and neutron flux distribution. The model is trained according to the given input and the corresponding output, and finally the required physical coding layer is obtained, so that the corresponding neutron outflow and neutron flux distribution can be quickly predicted based on the given neutron outflow and boron concentration.

[0159] S7. Acquire a CT image of the target object, and match at least one of the voxel grids according to the CT image to acquire a voxel model of the target object.

[0160] As previously described, after constructing a boron drug transport simulation model and a physical coding layer for each voxel grid, a voxel model of the target object can be obtained based on the specific information of the target object. In some embodiments, obtaining a CT image of the target object and matching at least one of the voxel grids with the CT image to obtain the voxel model of the target object includes: obtaining a CT image of the target object, determining a cancerous area in the CT image, matching the at least one corresponding voxel grid, and obtaining the voxel model of the target object using the matched voxel grid.

[0161] Furthermore, the cancerous region can actually be composed of multiple voxel grids, meaning that a voxel grid is an even smaller unit of division. For example, based on CT images, the cancerous region can be determined to be the target subject's brain. Since the brain is composed of multiple tissue materials, this region is matched to multiple voxel grids. In other embodiments, a specific cancerous region may be sufficiently precise, in which case a single voxel grid is matched. Furthermore, the voxel model of the target subject can also include voxel grids corresponding to the cancerous region and voxel grids of normal regions. In other words, all voxel grids are matched according to the various tissue materials of the target subject to form the voxel model.

[0162] S8. Perform bidirectional coupling based on the physical coding layer of all voxel grids in the voxel model and the boron drug transport simulation model to obtain the neutron flux distribution and boron drug concentration in the voxel model.

[0163] As mentioned above, the present application actually generates the physical coding layer and boron drug transport simulation method corresponding to each voxel grid offline without knowing any information about the patient in advance. At this time, the corresponding voxel model is obtained according to the actual situation of different target objects. And the physical coding layers of all voxel grids in the voxel model are coupled to predict the neutron flux distribution in the target object. Similarly, the present application also couples the boron drug transport simulation model of all voxel grids in the voxel model to predict the boron drug concentration in the target object.

[0164] Furthermore, in order to simultaneously consider the neutron transport and boron drug transport processes in the target object, and considering the characteristics of BNCT with neutron-boron drug bidirectional targeting, in fact, during the coupling process of the Internet of Things coding layer coupling and the boron drug transport simulation model, the two must form a bidirectional coupling relationship at the voxel grid level, so as to fully reflect the characteristics that BNCT treatment is actually affected by the combined action of the two.

[0165] Specifically, bidirectional coupling is performed based on the physical coding layer and the boron drug transport simulation model of all voxel grids in the voxel model, including: using the boron drug concentration output by the boron drug transport simulation model as an input of the physical coding layer to perform online coupling on the physical coding layers of all the voxel grids to obtain the neutron flux distribution in the voxel model; using the neutron flux distribution output by the physical coding layer as an input of the boron drug transport simulation model to perform online coupling on the boron drug transport simulation model of all the voxel grids to obtain the boron drug concentration in the voxel model.

[0166] In some embodiments, bidirectionally coupling the physical coding layer and the boron drug transport simulation model based on all voxel grids in the voxel model includes:

[0167] (1) A voxel grid in the voxel model is set as an initial grid, and a radiation source information and a boron drug administration scheme are given to the initial grid, wherein the radiation source information includes a radiation intensity of a neutron source and a radiation irradiation time, and the boron drug administration method includes a boron drug inflow rate and a boron drug concentration.

[0168] (2) The radiation intensity of the neutron source, the boron medicine inflow rate and the radiation irradiation time are input into the boron medicine transport simulation model of the initial grid to obtain the corresponding boron medicine outflow rate and boron medicine concentration.

[0169] (3) Determine the neutron flux entering the initial grid based on the radiation intensity of the neutron source, and input the boron concentration and the neutron flux into the physical coding layer of the initial grid to obtain the corresponding neutron outflow and neutron flux distribution. The neutron flux entering the initial grid based on the radiation intensity of the neutron source needs to be determined according to factors such as the type of neutron source and the environment. Those skilled in the art can determine the neutron flux based on the radiation intensity of the neutron source and in combination with other information, and this application does not limit this.

[0170] (4) The neutron flux distribution of the initial grid, the boron drug outflow rate of the initial grid and the radiation irradiation time are used as inputs of the next voxel grid, so as to obtain the corresponding boron drug outflow rate and boron drug concentration based on the boron drug transport simulation model of the next voxel grid, and thus obtain the boron drug concentration in the voxel model by traversing all the voxel grids.

[0171] (5) The neutron outflow flux of the initial grid and the boron concentration of the initial grid are used as inputs of the next voxel grid to predict the corresponding neutron outflow flux and neutron flux distribution based on the physical coding layer of the next voxel grid, so as to traverse all the voxel grids and obtain the neutron flux distribution in the voxel model.

[0172] It should be noted that there is no fixed order of execution between (2) and (3), and there is no fixed order of execution between (5) and (6).

[0173] In fact, the process of bidirectional coupling can be considered as the need to consider the output of the boron drug transport simulation model in the coupling process of the physical coding layer of the voxel grid, and the need to consider the output of the physical coding layer in the coupling process of the boron drug transport simulation model of the voxel grid. This is exactly in line with the characteristics of BNCT with neutron-boron drug bidirectional targeting, making the BNCT treatment plan generated based on this method more accurate.

[0174] The protection scope of the neutron transport simulation method described in the embodiment of the present application is not limited to the execution order of the steps listed in this embodiment. All solutions implemented by adding, reducing, or replacing steps in the existing technology based on the principles of the present application are included in the protection scope of the present application.

[0175] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon, which, when called by a processor, implements the boron drug transport simulation method and / or the neutron-boron drug transport coupling simulation method provided in the present application.

[0176] 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.

[0177] The computer-readable program characterized 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.

[0178] The above embodiments are merely illustrative of the principles and effects of this application and are not intended to limit this application. Anyone skilled in the art may modify or alter the above embodiments without departing from the spirit and scope of this application. Therefore, all equivalent modifications or alterations made by one of ordinary skill in the art without departing from the spirit and technical concepts disclosed in this application shall be covered by the claims of this application.

Claims

1. A boron drug transport simulation method, characterized in that: The method is applicable to a BNCT treatment planning system, and the method comprises: Setting a plurality of voxel grids and boron drug transport parameters, wherein the voxel grids correspond to various types of human tissue materials; Offline encoding is performed on each voxel grid using the boron drug transport parameter to obtain a corresponding boron drug transport simulation model, wherein the boron drug transport simulation model is used to predict the boron drug outflow rate and the boron drug concentration within the voxel grid based on the radiation intensity, the boron drug inflow rate and the radiation exposure time; Acquire a CT image of the target object, and match at least one of the voxel grids according to the CT image to acquire a voxel model of the target object; Obtaining the boron drug concentration within the voxel model based on a boron drug transport simulation model of all voxel grids in the voxel model; wherein performing offline encoding on each voxel grid using the boron drug transport parameter comprises: constructing a control equation for the voxel grid, wherein the control equation is established based on a computational fluid dynamics equation and a convection-diffusion-reaction equation; Given different radiation intensities, boron drug inflow rates, and radiation exposure times for each voxel grid, and solving the control equation in combination with the boron drug transport parameters to obtain the corresponding boron drug outflow rates and boron drug concentrations within the voxel grid; A boron drug transport simulation model for each voxel grid is offline encoded based on the given radiation intensity, the boron drug inflow rate, the radiation exposure time, the obtained boron drug outflow rate, and the boron drug concentration within the voxel grid.

2. The boron drug transport simulation method according to claim 1, characterized in that: The method comprises: defining a boron drug inflow rate and a boron drug outflow rate in a two-dimensional phase space, wherein the two-dimensional phase space includes a three-dimensional spatial phase space and a time phase space; In the three-dimensional phase space, the three-dimensional spatial distribution of the boron drug inflow rate is calculated based on quadrature discretization, so as to solve the control equation in combination with the boron drug transport parameter to obtain the corresponding three-dimensional spatial distribution of the boron drug outflow rate and the three-dimensional spatial distribution of the boron drug concentration; In the time phase space, the time distribution of the boron drug inflow rate is calculated based on the asymptotic state approximation, so as to solve the control equation in combination with the boron drug transport parameters to obtain the corresponding time distribution of the boron drug outflow rate and the time distribution of the boron drug concentration.

3. The boron drug transport simulation method according to claim 1, characterized in that: The boron drug transport parameters include the boron drug's characteristic diffusion coefficient, body fluid characteristic flow rate, and free boron conversion rate.

4. A coupled simulation method for neutron-boron drug transport, characterized in that: The method is applicable to a BNCT treatment planning system, and the method comprises: A plurality of voxel grids and boron drug transport parameters are set, and each voxel grid is offline encoded using the boron drug transport parameters to obtain a corresponding boron drug transport simulation model; the voxel grid corresponds to various types of human tissue materials; the boron drug transport simulation model is used to predict the boron drug outflow rate and the boron drug concentration within the voxel grid based on radiation intensity, boron drug inflow rate and radiation exposure time; Offline encoding is performed on each voxel grid to obtain a corresponding physical coding layer, wherein the physical coding layer is used to predict a corresponding neutron outflow and neutron flux distribution based on a neutron incident flux and a boron dose concentration; Acquire a CT image of the target object, and match at least one of the voxel grids according to the CT image to acquire a voxel model of the target object; Bidirectional coupling is performed based on the physical coding layer of all voxel grids in the voxel model and the boron drug transport simulation model to obtain the neutron flux distribution and boron drug concentration in the voxel model; wherein the offline encoding of each voxel grid using the boron drug transport parameter includes: constructing a control equation for the voxel grid, wherein the control equation is established based on a computational fluid dynamics equation and a convection-diffusion-reaction equation; Given different radiation intensities, boron drug inflow rates, and radiation exposure times for each voxel grid, and solving the control equation in combination with the boron drug transport parameters to obtain the corresponding boron drug outflow rates and boron drug concentrations within the voxel grid; Offline encoding a boron drug transport simulation model for each voxel grid based on the given radiation intensity, the boron drug inflow rate, the radiation exposure time, the obtained boron drug outflow rate, and the boron drug concentration within the voxel grid; The offline encoding of each voxel grid to obtain a corresponding physical coding layer includes: Customizing the neutron inflow and the neutron outflow in an eight-dimensional phase space; the eight-dimensional phase space includes a time phase space, an energy phase space, a three-dimensional angle phase space, and a three-dimensional space phase space; Assigning different neutron incident flux and boron concentration to each voxel grid to correspondingly obtain the neutron outgoing flux and the neutron flux distribution in the eight-dimensional phase space; The physical coding layer of each voxel grid is offline coded based on the given neutron incident flux and boron concentration and the corresponding neutron outgoing flux and neutron flux distribution.

5. The coupled simulation method of neutron-boron drug transport according to claim 4, characterized in that: The method comprises: In combination with the eight-dimensional phase space definition of the neutron incident flow and the neutron outgoing flow, spatial integration is performed on the voxel grid to characterize the neutron transport process within the voxel grid as the relationship characteristic between the neutron incident flow and the neutron outgoing flow.

6. The coupled simulation method of neutron-boron drug transport according to claim 4, characterized in that: The bidirectional coupling between the physical coding layer and the boron drug transport simulation model based on all voxel grids in the voxel model includes: Using the boron drug concentration output by the boron drug transport simulation model as an input to the physical coding layer, so as to perform online coupling on the physical coding layers of all the voxel grids and obtain the neutron flux distribution in the voxel model; The neutron flux distribution output by the physical coding layer is used as an input of the boron drug transport simulation model to perform online coupling on the boron drug transport simulation models of all the voxel grids to obtain the boron drug concentration in the voxel model.

7. The coupled simulation method of neutron-boron drug transport according to claim 6, characterized in that: The method comprises: Setting a voxel grid in the voxel model as an initial grid, and assigning radiation source information and a boron drug administration scheme to the initial grid, wherein the radiation source information includes a radiation intensity of a neutron source and a radiation irradiation time, and the boron drug administration scheme includes a boron drug inflow rate and a boron drug concentration; Inputting the radiation intensity of the neutron source, the boron medicine inflow rate and the radiation irradiation time into the boron medicine transport simulation model of the initial grid to obtain the corresponding boron medicine outflow rate and boron medicine concentration; Determining a neutron incident flux entering the initial grid based on the radiation intensity of the neutron source, and inputting the boron dose concentration and the neutron incident flux into the physical coding layer of the initial grid to obtain a corresponding neutron outgoing flux and neutron flux distribution; Using the neutron flux distribution of the initial grid, the boron drug outflow rate of the initial grid, and the radiation exposure time as inputs of a next voxel grid, obtaining the corresponding boron drug outflow rate and boron drug concentration based on the boron drug transport simulation model of the next voxel grid, and in this way until all the voxel grids are traversed to obtain the boron drug concentration in the voxel model; The neutron outflow flux of the initial grid and the boron concentration of the initial grid are used as inputs of the next voxel grid to predict the corresponding neutron outflow flux and neutron flux distribution based on the physical coding layer of the next voxel grid, so as to traverse all the voxel grids and obtain the neutron flux distribution in the voxel model.

8. A computer storage medium storing a computer program, wherein: When the computer program is executed by a processor, the boron drug transport simulation method according to any one of claims 1 to 3 or the coupled neutron-boron drug transport simulation method according to any one of claims 4 to 7 is implemented.

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