Coefficient acquisition method for dose calculation, radiotherapy system and related device

Abstract

The invention provides a coefficient acquisition method for dose calculation, a radiotherapy system and a related device. The method comprises the following steps: acquiring reference dose distribution information of particles transported in a target material; dividing the particle energy in a non-equidistant manner according to the particle energy from small to large so as to obtain a plurality of nodes; wherein each node corresponds to different particle energy; and according to the reference dose distribution information, obtaining a reference expansion coefficient and a reference deflection coefficient of each node of the particle transported in the target material. The transport characteristics of the particles in different materials are obtained in an accurate, simple and visual mode, the reference coefficient is used for dose calculation and treatment plan making of radiotherapy, and the treatment effect and safety are improved.

Description

[0001] This application is a divisional application of the Chinese application with application number CN202310779340.8, application date June 28, 2023, and invention name “Coefficient acquisition method for dose calculation, radiotherapy system and related devices”. Technical Field

[0002] The present application relates to the technical field of radiotherapy, and in particular to a coefficient acquisition method for dose calculation, an electronic device, a computer-readable storage medium, a computer program product, and a radiotherapy system. Background Art

[0003] Radiotherapy is widely used in cancer treatment. Accurate calculation of the dose distribution of particles (such as protons) in target tissues is crucial for treatment planning and dose adjustment. However, there are some problems in obtaining the transport characteristics of particles in different materials, such as low accuracy, complex calculations, or lack of intuitiveness, which cannot meet clinical needs.

[0004] Based on this, the present application provides a coefficient acquisition method for dose calculation, an electronic device, a computer-readable storage medium, a computer program product and a radiotherapy system to improve the relevant technology. Summary of the invention

[0005] The purpose of the present application is to provide a coefficient acquisition method, electronic device, computer-readable storage medium, computer program product and radiotherapy system for dose calculation, which can obtain the transport characteristics of particles in different materials in an accurate, simple and intuitive way, use reference coefficients to perform dose calculation and treatment plan formulation for radiotherapy, and improve treatment effect and safety.

[0006] The purpose of this application is achieved by the following technical solutions:

[0007] The present application provides a coefficient acquisition method for dose calculation, the method comprising:

[0008] Obtain reference dose distribution information of particles transported in target materials;

[0009] According to the particle energy from small to large, the particle energy is divided in an unequal manner to obtain multiple nodes; wherein each node corresponds to a different particle energy;

[0010] According to the reference dose distribution information, a reference expansion coefficient and a reference deflection coefficient of each node of the particle transport in the target material are obtained.

[0011] In some possible implementations, obtaining reference dose distribution information of particles transported in a target material includes:

[0012] The transport process of the particles in the target material is simulated using a Monte Carlo algorithm or a radiation transport model to obtain reference dose distribution information of the particles transported in the target material.

[0013] In some possible implementations, the number of nodes is N;

[0014] Among N nodes, the average spacing of particle energies corresponding to the first M nodes is smaller than the average spacing of particle energies corresponding to the last M nodes;

[0015] Wherein, N and M are positive integers, and N>2M.

[0016] In some possible implementations, obtaining a reference expansion coefficient and a reference deflection coefficient of each node of the particle transported in the target material according to the reference dose distribution information includes:

[0017] A statistical method or an optimization algorithm is used to obtain a reference expansion coefficient and a reference deflection coefficient of each node corresponding to the reference dose distribution information; wherein the optimization algorithm includes any one of a genetic algorithm, a particle swarm algorithm, and a simulated annealing algorithm.

[0018] In some possible implementations, obtaining a reference expansion coefficient and a reference deflection coefficient of each node of the particle transported in the target material according to the reference dose distribution information includes:

[0019] According to the reference dose distribution information, obtaining a reference expansion and contraction curve and a reference deflection curve of the particles transported in the target material;

[0020] Obtain the undetermined expansion coefficient and undetermined deflection coefficient of each node;

[0021] According to the undetermined expansion coefficient and the undetermined deflection coefficient of each node, a undetermined expansion curve and an undetermined deflection curve are calculated;

[0022] When the pending scaling curve does not match the reference scaling curve and / or the pending deflection curve does not match the reference deflection curve, the pending scaling coefficient and / or the pending deflection coefficient of one or more nodes are adjusted so that the recalculated pending scaling curve matches the reference scaling curve and the recalculated pending deflection curve matches the reference deflection curve, thereby obtaining a reference scaling coefficient and a reference deflection coefficient of each node.

[0023] In some possible implementations, obtaining the undetermined scaling coefficient and the undetermined deflection coefficient of each node includes:

[0024] Initialize and assign values ​​to the undetermined expansion coefficient and undetermined deflection coefficient of each node;

[0025] The undetermined expansion coefficient of each node is set to the inverse of the density of the target material, and the undetermined deflection coefficient of each node is set to 1.

[0026] In some possible implementations, the calculating of a pending scaling curve and a pending deflection curve according to a pending scaling coefficient and a pending deflection coefficient of each node includes:

[0027] The undetermined expansion coefficient and undetermined deflection coefficient of each discrete point between adjacent nodes are calculated by interpolation;

[0028] The undetermined expansion curve and the undetermined deflection curve are generated according to the undetermined expansion coefficient and the undetermined deflection coefficient of each discrete point between the plurality of nodes and the adjacent nodes.

[0029] In some possible implementations, the process of adjusting the undetermined scaling factor and / or the undetermined deflection factor of one or more nodes includes:

[0030] When the pending scaling curve does not match the reference scaling curve, adjusting the pending scaling coefficients of one or more nodes, and recalculating the pending scaling curve according to the pending scaling coefficient and the pending deflection coefficient of each node, so that the pending scaling curve matches the reference scaling curve;

[0031] When the pending expansion curve matches the reference expansion curve and the pending deflection curve does not match the reference deflection curve, the pending deflection coefficients of one or more nodes are adjusted, and the pending deflection curve is recalculated according to the pending expansion coefficient and the pending deflection coefficient of each node, so that the pending deflection curve matches the reference deflection curve.

[0032] In some possible implementations, the process of adjusting the undetermined scaling factor and / or the undetermined deflection factor of one or more nodes further includes:

[0033] After the pending deflection curve matches the reference deflection curve, re-detecting whether the pending expansion curve matches the reference expansion curve;

[0034] If the pending expansion curve does not match the reference expansion curve, the pending expansion coefficients of one or more nodes are adjusted again, and the pending expansion curve is calculated again according to the pending expansion coefficient and the pending deflection coefficient of each node until the pending expansion curve matches the reference expansion curve.

[0035] In some possible implementations, the particle is a proton; or,

[0036] The particles are any particles corresponding to proton therapy.

[0037] In some possible implementations, the target material is a human organ material, and the method further includes:

[0038] According to the incident information of the particle and the reference expansion coefficient and reference deflection coefficient of each node where the particle is transported in the human organ material, the transport process of the particle in the human organ is simulated to calculate the simulated dose distribution information of the particle; wherein the incident information of the particle includes the particle type, particle energy and particle incident direction.

[0039] In a second aspect, the present application provides an electronic device, the electronic device comprising a memory and at least one processor, the memory storing a computer program, and the at least one processor being configured to implement the following steps when executing the computer program:

[0040] Obtain reference dose distribution information of particles transported in target materials;

[0041] According to the particle energy from small to large, the particle energy is divided in an unequal manner to obtain multiple nodes; wherein each node corresponds to a different particle energy;

[0042] According to the reference dose distribution information, a reference expansion coefficient and a reference deflection coefficient of each node of the particle transport in the target material are obtained.

[0043] In a third aspect, the present application provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by at least one processor, it implements the steps of any of the above methods or implements the functions of any of the above electronic devices.

[0044] In a fourth aspect, the present application provides a computer program product, which includes a computer program, and when the computer program is executed by at least one processor, it implements the steps of any of the above methods or implements the functions of any of the above electronic devices.

[0045] In a fifth aspect, the present application provides a radiotherapy system, comprising:

[0046] A coefficient acquisition device, used to calculate a reference expansion coefficient and a reference deflection coefficient of each node of particle transport in a human organ material by using any of the above coefficient acquisition methods for dose calculation;

[0047] A dose calculation device, used for simulating the transport process of the particles in the human organ according to the incident information of the particles and the reference expansion coefficient and reference deflection coefficient of each node of the particles transported in the human organ material, so as to calculate the simulated dose distribution information of the particles; wherein the incident information of the particles includes the type of particles, the energy of the particles and the incident direction of the particles;

[0048] The device for determining human body dose is used to determine the dose used in radiotherapy according to the expected dose distribution information after the simulated dose distribution information of the particles matches the expected dose distribution information. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The present application is further described below in conjunction with the accompanying drawings and specific implementation methods.

[0050] Figure 1 It is a flow chart of a coefficient acquisition method for dose calculation provided in an embodiment of the present application.

[0051] Figure 2 It is a flow chart of another coefficient acquisition method for dose calculation provided in an embodiment of the present application.

[0052] Figure 3 It is a structural block diagram of an electronic device provided in an embodiment of the present application.

[0053] Figure 4 It is a structural diagram of a computer program product provided in an embodiment of the present application. DETAILED DESCRIPTION

[0054] The technical solution in the present application will be described below in conjunction with the drawings and specific implementation methods of the present application. It should be noted that, under the premise of no conflict, the various implementation methods or technical features described below can be arbitrarily combined to form a new implementation method.

[0055] In the embodiments of the present application, the words "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any implementation or design scheme described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other implementations or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0056] The first, second, etc. descriptions appearing in the embodiments of the present application are only used for illustration and distinction of the description objects. There is no order, nor does it indicate any special limitation on the quantity in the embodiments of the present application, and cannot constitute any limitation on the embodiments of the present application.

[0057] The following is a brief description of the technical field and related terms of the embodiments of the present application.

[0058] Proton therapy is a radiotherapy technique that uses high-energy proton beams to precisely treat tumors. Compared with traditional X-ray radiotherapy, proton therapy can better control the delivery of radiation doses, reduce damage to normal tissues, and improve treatment effectiveness.

[0059] The principle of proton therapy is to use the physical properties of protons, that is, after entering the human body, the proton beam will reach the maximum dose (Bragg peak) at a certain depth, and then decrease sharply until it stops. This characteristic enables the proton beam to release the maximum dose in the tumor, while reducing the dose deposition in the normal tissue behind the tumor, thereby reducing the side effects caused by treatment. Proton therapy is suitable for many types of tumors, including pediatric tumors, cranial tumors, head and neck tumors, chest tumors, abdominal tumors, bone and soft tissue tumors, etc. Proton therapy is particularly suitable for tumors around critical organs or those that are sensitive to radiation. Compared with traditional radiotherapy, proton therapy can better protect normal tissues and organs and reduce the side effects caused by treatment. Especially for pediatric patients, proton therapy can reduce long-term treatment sequelae and reduce the risk of secondary tumors. Some studies have shown that proton therapy can provide therapeutic effects comparable to traditional radiotherapy in some cases, while reducing adverse reactions.

[0060] The Monte Carlo (also translated as Monte Carlo, MC) method is known as the gold standard for particle dose calculation. Compared with traditional analytical algorithms, it has the advantages of high calculation accuracy. In clinical radiotherapy, when MC calculates the dose deposition of particles in the human body's Regions of interest (ROI), it will replace each voxel on the CT image with the corresponding real human organ material based on information such as the treatment site and CT value, thereby achieving a mapping from the virtual image to the real human body, and transporting and simulating particles in human tissues. Due to the real organ material properties, MC's transport and simulation of particles, and the interaction of particles are all considered to occur in human tissues, and the resulting dose deposition belongs to the organ (human tissue) dose.

[0061] Another dose calculation method corresponding to MC is the analytical algorithm. Due to the difference in algorithm properties, when the analytical algorithm performs dose calculation, it directly replaces the voxels on the CT image with water of different densities, and the density value is determined by the CT value at the corresponding position. Therefore, the dose calculated is considered to be the dose in water. The analytical algorithm has high computational efficiency and low requirements for computer hardware. It is currently the most widely used and common algorithm for dose calculation.

[0062] In the proton therapy system, in order to accurately calculate the dose distribution caused by protons, the Monte Carlo calculation method using the FDC (Fast Dose Calculate) method needs to know the expansion and deflection of a certain particle trajectory relative to its trajectory in water in various different substances, so that the protons can be transported in the substance with the correct range and deflection. However, the existing methods for obtaining the expansion coefficient (i.e., range coefficient) and deflection coefficient of different substances are mostly complicated and not intuitive enough, and the method for obtaining the correlation coefficient needs to be improved.

[0063] Radiation therapy is widely used in cancer treatment. Accurate calculation of the dose distribution of particles (such as protons) in target tissues is crucial for treatment planning and dose adjustment. However, it has been a challenge to obtain the transport properties of particles (such as telescope and deflection) in different materials.

[0064] The current coefficient acquisition methods have some problems, such as high complexity, unintuitive calculations, or failure to meet clinical needs. Therefore, an accurate, simple, and intuitive method is needed to obtain the expansion and deflection coefficients of particles in different substances to improve the accuracy and practicality of dose calculations.

[0065] Based on this, the present application provides a coefficient acquisition method for dose calculation, an electronic device, a computer-readable storage medium, a computer program product and a radiotherapy system to improve the relevant technology.

[0066] The solutions provided in the embodiments of the present application involve technologies such as radiotherapy and simulation, which are specifically described by the following embodiments. It should be noted that the description order of the following embodiments is not intended to limit the preferred order of the embodiments.

[0067] (Method for obtaining coefficients for dose calculation)

[0068] See also Figure 1 , Figure 1 It is a flow chart of a coefficient acquisition method for dose calculation provided in an embodiment of the present application.

[0069] The present application embodiment provides a coefficient acquisition method for dose calculation, the method comprising:

[0070] Step S101: obtaining reference dose distribution information of particles transported in a target material;

[0071] Step S102: Acquire multiple nodes;

[0072] Step S103: According to the reference dose distribution information, a reference expansion coefficient and a reference deflection coefficient of each node of the particle transport in the target material are obtained.

[0073] The embodiments of the present application do not limit the particles, which may be, for example, protons, heavy ions, X-rays, etc. Protons are one of the most common particles and are widely used in radiotherapy in the medical field. Heavy ions include alpha particles, carbon ions, O-16, Ne-20, Fe-56, etc., which have higher mass and energy and can produce more complex interactions and energy deposition patterns in tissues.

[0074] The target material is not limited in the present embodiment, and it may be, for example, organ material, water, space suit material, spacecraft material, etc. The organ material has the element composition (or element components) of human organs.

[0075] The reference dose distribution information refers to the reference information of the dose distribution after the particles are transported in the target material.

[0076] Node refers to the node divided in dose calculation.

[0077] The stretch factor and deflection factor refer to the coefficients used to calculate the range stretch and deflection of a particle in a target material. These coefficients reflect the transport properties of a particle in a target material relative to its range in a reference material (usually water). For example, the stretch factor can represent the scaling ratio of a particle's range in a target material relative to its range in water.

[0078] Reference stretch coefficients and reference deflection coefficients can be applied as reference values ​​to the transport of particles in the target material. These reference coefficients are used to adjust the range and deflection of particles in the target material to match the reference dose distribution information.

[0079] In some embodiments, the transport process of particles in the target material is simulated according to the pending stretch coefficient and the pending deflection coefficient of each node to obtain the pending dose distribution information; when the pending dose distribution information matches the reference dose distribution information, the "pending stretch coefficient and pending deflection coefficient of each node corresponding to the pending dose distribution information" is used as the "reference stretch coefficient and reference deflection coefficient of each node corresponding to the reference dose distribution information", thereby obtaining the reference stretch coefficient and reference deflection coefficient of the corresponding node of the particle transported in the target material.

[0080] Thus, first, obtain the reference dose distribution information of the particles transported in the target material. By using relevant dose calculation methods (such as Monte Carlo simulation), obtain the reference dose distribution information of the particles when transported in the target material. This information describes the reference dose distribution of the particles in the target material. Secondly, obtain multiple nodes. The target material is divided into multiple nodes, and the number of nodes, node spacing, and node positions are determined according to specific needs. By dividing the nodes, the transport process of particles in the target material can be described more finely. After that, for each node, determine the corresponding reference telescopic coefficient and reference deflection coefficient. These coefficients reflect the reference range and reference deflection of the particles at the corresponding nodes. On this basis, reference coefficients (including reference telescopic coefficients and reference deflection coefficients) can be applied. The calculated reference telescopic coefficient and reference deflection coefficient are used as the reference telescopic coefficient and reference deflection coefficient of the corresponding node when the particles are transported in the target material. These reference coefficients are used for dose calculation to ensure that the dose calculation results are more accurate and precise.

[0081] The advantage of this is that this method can improve the accuracy and precision of dose calculation. By referring to parameters such as the telescopic coefficient and the reference deflection coefficient, the transport characteristics of particles in the target material (such as telescopic and deflection) can be better described, and the dose distribution of particles can be more accurately predicted and calculated. The calculation process is simplified. This method divides the target material into multiple nodes and calculates the reference range coefficient and reference deflection coefficient corresponding to each node, thereby simplifying the dose calculation process and determining the reference coefficient when calculating the actual dose without complicated calculation steps. The practicality and feasibility are improved. This method provides an accurate, feasible and practical way to obtain the transport characteristics of particles in the target material. By using reference dose distribution information and reference coefficients, the dose calculation and treatment plan formulation of radiotherapy can be better guided, thereby improving the treatment effect and safety. In summary, this coefficient acquisition method can be applied in radiotherapy dose calculation, providing an effective solution for accurate and reliable dose calculation.

[0082] In some embodiments, obtaining reference dose distribution information of particles transported in a target material includes:

[0083] The transport process of the particles in the target material is simulated using a Monte Carlo algorithm or a radiation transport model to obtain reference dose distribution information of the particles transported in the target material.

[0084] Therefore, in order to obtain the dose distribution of particles in the target material, the Monte Carlo algorithm (MC) or the radiation transport model is used to simulate the transport process of particles in the target material. These simulation methods are based on physical principles and numerical calculations. By simulating the movement of a large number of particles in the target material, the dose distribution information of the particles is obtained. The Monte Carlo algorithm is a simulation method based on probability statistics. By randomly sampling the transport path of particles in the target material, the dose contribution of the particles at each point is calculated, and the overall dose distribution is obtained statistically. This method can simulate the transport behavior of particles in complex geometric structures and material compositions. The radiation transport model is a simulation method based on physical principles and mathematical equations. The transport process of particles in the target material is described by solving the transport equations. This model can take into account the physical processes such as particle interaction, scattering, and absorption, so as to calculate the dose distribution of particles.

[0085] The advantage of doing so is that by using the Monte Carlo algorithm or radiation transport model, the transport process of particles in the target material can be simulated more accurately, which makes the reference dose distribution information obtained more reliable and accurate, and improves the accuracy of dose calculation; Monte Carlo algorithm and radiation transport model are universal simulation methods, applicable to various particles and different target materials, whether protons, electrons or other particles, they can be transported and simulated by appropriate methods to obtain reference dose distribution information; Monte Carlo algorithm and radiation transport model are proven and widely used methods, they have a reliable physical basis and verifiability, and can provide reliable dose distribution information. In summary, by using the Monte Carlo algorithm or radiation transport model to simulate the transport process of particles in the target material, accurate and reliable reference dose distribution information of particles in the target material can be obtained, thereby improving the accuracy and credibility of dose calculation of radiotherapy.

[0086] In some embodiments, obtaining a plurality of nodes includes:

[0087] The particle energy is divided in an equidistant manner to obtain a plurality of nodes, wherein each node corresponds to a different particle energy.

[0088] That is, the distance between any two adjacent nodes is the same. For example, suppose that for proton therapy, the energy range is divided into multiple intervals in an equidistant manner, and the nodes are determined according to the maximum energy value of each interval, thus obtaining 5 nodes: 50MeV, 100MeV, 150MeV, 200MeV, and 250MeV.

[0089] In some embodiments, obtaining a plurality of nodes includes:

[0090] The particle energy is divided in an unequally spaced manner to obtain a plurality of nodes, wherein each node corresponds to a different particle energy.

[0091] That is, the spacing between at least two groups of adjacent nodes is different. For example, assuming that for proton therapy, the energy range is divided into multiple intervals in an unequal manner, and the nodes are determined according to the maximum energy value of each interval, thereby obtaining 50 nodes: 0.5MeV, 1.0MeV, 1.5MeV, 2.0MeV, 2.5MeV, 3.0MeV, 3.5MeV, 4.0MeV, 4.5MeV, 5.0MeV, 5.5MeV, 6.0MeV, 6.5MeV, 7. 0MeV, 7.5MeV, 8.0MeV, 8.5MeV, 9.0MeV, 9.5MeV, 10.0MeV, 11.0MeV, 12.0MeV, 13.0MeV, 14.0M eV, 15.0MeV, 17.0MeV, 20.0MeV, 25.0MeV, 30.0MeV, 50MeV, 100MeV, 150MeV, 200MeV, 230MeV.

[0092] The embodiments of the present application do not limit the number of nodes, which may be 2, 3, 5, 10, 30, 50, 100, 1000, 10000, etc.

[0093] Therefore, in order to obtain multiple nodes, the particle energy is divided in an unequal manner according to the particle energy from small to large. This means that the particle energy range is divided into multiple different intervals, each interval corresponds to a node (for example, the point corresponding to the maximum value, minimum value or median value of the energy interval can be determined as a node). The division method can be selected according to specific needs and the characteristics of the target material. Each node corresponds to a different particle energy, which means that the energy division of the node will cover the entire energy range required for treatment to ensure accurate modeling of the transport characteristics of particles with different energies. Each node represents a particle with a specific energy. By calculating the reference stretch coefficient and the reference deflection coefficient at different energy nodes, the differences in the transport behavior of particles of different energies can be taken into account, thereby more accurately describing the transport characteristics of particles in the target material.

[0094] The advantage of this is that by dividing the particle energy into multiple nodes with unequal energy, this method can take into account the differences in the transport behavior of particles at different energies, which helps to more comprehensively describe the expansion and deflection characteristics of particles in the target material and improve the accuracy of dose calculation; the division method of energy nodes is flexible and can be adjusted and optimized according to actual needs. By reasonably selecting the number and energy range of nodes, it can better adapt to different target materials and treatment needs and provide customized dose calculation solutions; by calculating the reference expansion coefficient and reference deflection coefficient at different energy nodes, more accurate reference range and reference deflection values ​​can be obtained, which helps to improve the accuracy and reliability of dose calculation, thereby better guiding the formulation of dose plans for radiotherapy. In summary, by dividing the particle energy into multiple nodes in an unequal manner, energy dependence can be taken into account and more accurate and flexible dose calculation can be provided, which provides a more sophisticated and comprehensive solution for modeling the transport characteristics of particles in target materials, thereby improving the accuracy and reliability of dose calculation for radiotherapy.

[0095] In some embodiments, the number of nodes is N;

[0096] Among N nodes, the average spacing of particle energies corresponding to the first M nodes is smaller than the average spacing of particle energies corresponding to the last M nodes;

[0097] Wherein, N and M are positive integers, and N>2M.

[0098] As an example, M=3, N=10; as another example, M=5, N=50; as yet another example, M=10, N=100.

[0099] Take M=5, N=50 as an example, assuming that there are 50 nodes, that is, N=50. The average spacing of the particle energy corresponding to the first M=5 nodes is smaller than the average spacing of the particle energy corresponding to the last M=5 nodes. Specifically, the energy range is divided to obtain 50 nodes, and the proton therapy process is taken as an example. Taking 5MeV as the starting energy, the following energy nodes are designed: 5MeV, 10MeV, 15MeV, 20MeV, 25MeV, ..., 50MeV, ..., 190MeV, 200MeV, 210MeV, 220MeV, 230MeV.

[0100] In this embodiment, the average energy spacing of the first five nodes (5MeV, 10MeV, 15MeV, 20MeV, 25MeV) is relatively small, and the average energy spacing of the last five nodes (190MeV, 200MeV, 210MeV, 220MeV, 230MeV) is relatively large, 10MeV. The nodes designed in this way can meet the condition that the average energy spacing of the first M nodes is smaller than the average energy spacing of the last M nodes.

[0101] Thus, the particle energy is divided into multiple intervals to obtain multiple nodes. The number of nodes is N. The N nodes include the first M nodes and the last M nodes (in addition to the first M nodes and the last M nodes mentioned above, other nodes may also be included). Moreover, the average value of the energy spacing between the first M nodes is less than the average value of the energy spacing between the last M nodes. This division method adopts a node setting method of dense front and sparse back, setting more nodes for the lower particle energy range (such as 0-10MeV) that is more concerned about radiotherapy, and setting fewer nodes for the higher particle energy range (such as 10-230MeV) that is less concerned, which helps to better consider energy dependence, especially to more accurately describe the transport characteristics of particles in different energy ranges. By adjusting the position and energy spacing of the nodes, the distribution of the nodes is optimized to ensure that the requirements of the average value of the energy spacing of the first M nodes and the last M nodes are met. This helps to better capture the transport characteristics of particles at different energies and improve the accuracy and reliability of dose calculation.

[0102] The advantage of doing this is that the first M and last M nodes are divided from N nodes, and the average energy spacing of the first M nodes is ensured to be smaller than the average energy spacing of the last M nodes, which can more reasonably consider the differences in the transport behavior of particles in different energy ranges, which helps to more accurately describe the expansion and deflection characteristics of particles in the target material; by optimizing the distribution and energy spacing of the nodes, the transport characteristics of particles at different energies can be better captured, which improves the accuracy and precision of the dose calculation and makes the dose plan more refined and reliable; by adjusting the number of nodes and the energy spacing, the method has high flexibility and can adapt to different target materials and treatment needs. Parameters can be selected according to the actual situation and the characteristics of the target material to obtain the best node distribution and provide a customized dose calculation solution.

[0103] In some embodiments, obtaining a reference expansion coefficient and a reference deflection coefficient of each node of the particle transported in the target material according to the reference dose distribution information includes:

[0104] A statistical method or an optimization algorithm is used to obtain a reference expansion coefficient and a reference deflection coefficient of each node corresponding to the reference dose distribution information; wherein the optimization algorithm includes any one of a genetic algorithm, a particle swarm algorithm, and a simulated annealing algorithm.

[0105] Therefore, firstly, the reference dose distribution information of the particles transported in the target material is obtained, which can be obtained by Monte Carlo simulation or other dose calculation methods. Statistical methods or optimization algorithms are used to obtain the reference expansion coefficient and reference deflection coefficient of each node corresponding to the reference dose distribution information.

[0106] On the one hand, statistical methods can be used to analyze and fit the reference dose distribution information to obtain reference expansion coefficients and reference deflection coefficients. Statistical methods can use probability distribution, regression analysis and other techniques to estimate reference coefficients.

[0107] Another method of obtaining the reference telescopic coefficient and the reference deflection coefficient is to use an optimization algorithm, including a genetic algorithm, a particle swarm algorithm, a simulated annealing algorithm, etc. These algorithms find the best reference coefficient through a search and optimization process. By applying an optimization algorithm to find the optimal reference range coefficient and reference deflection coefficient, for example, an optimization objective function can be defined, the dose distribution information to be determined is compared with the reference dose distribution information, and the coefficients are adjusted through iterative optimization to minimize the optimization objective function.

[0108] The advantage of doing this is that by using statistical methods or optimization algorithms to obtain reference expansion and contraction coefficients and reference deflection coefficients, the expansion and deflection characteristics of particles at different nodes can be described more accurately; by using statistical methods and optimization algorithms, appropriate methods can be flexibly selected according to actual conditions to obtain reference coefficients, making the coefficient calculation method widely applicable; optimization algorithms include genetic algorithms, particle swarm algorithms, and simulated annealing algorithms, etc., which provide the flexibility of multiple algorithm selections. According to actual conditions and needs, a suitable optimization algorithm can be selected to obtain the best unknown coefficients, further improving the accuracy and reliability of dose calculations.

[0109] In some embodiments, obtaining a reference expansion coefficient and a reference deflection coefficient of each node of the particle transported in the target material according to the reference dose distribution information includes:

[0110] According to the reference dose distribution information, obtaining a reference expansion and contraction curve and a reference deflection curve of the particles transported in the target material;

[0111] Obtain the undetermined expansion coefficient and undetermined deflection coefficient of each node;

[0112] According to the undetermined expansion coefficient and the undetermined deflection coefficient of each node, a undetermined expansion curve and an undetermined deflection curve are calculated;

[0113] When the pending scaling curve does not match the reference scaling curve and / or the pending deflection curve does not match the reference deflection curve, the pending scaling coefficient and / or the pending deflection coefficient of one or more nodes are adjusted so that the recalculated pending scaling curve matches the reference scaling curve and the recalculated pending deflection curve matches the reference deflection curve, thereby obtaining a reference scaling coefficient and a reference deflection coefficient of each node.

[0114] In some embodiments, the pending telescopic curve matches the reference telescopic curve, which means that the deviation of the two curves at multiple preset depths is less than a first preset ratio, and the pending telescopic curve does not match the reference telescopic curve, which means that the deviation of the two curves at one or more preset depths is not less than a first preset ratio;

[0115] The pending deflection curve matches the reference deflection curve, which means that the deviation of the two curves at multiple preset depths is less than a second preset ratio. The pending deflection curve does not match the reference deflection curve, which means that the deviation of the two curves at one or more preset depths is not less than a second preset ratio.

[0116] In this embodiment, the deviation between the pending curve and the reference curve at the preset depth refers to the ratio of “the absolute value of the difference between the values ​​of the two curves at the preset depth” to “the value of the reference curve at the preset depth”.

[0117] The present embodiment does not limit the first preset ratio and the second preset ratio, which may be, for example, 0.1%, 0.5%, 1%, 2%, 10%, etc.

[0118] Based on the reference dose distribution information of the particles in the target material, the reference telescopic curve and reference deflection curve of the particle transport in the target material are calculated. These curves reflect the dose distribution of the particles under different telescopic and deflection conditions, thereby providing important indicators of the particle transport characteristics. The reference telescopic curve and the reference deflection curve provide the dose distribution information of the particles at different positions and angles, which can provide an accurate basis for dose calculation and treatment planning. As an example, the reference dose distribution information can be obtained by MC calculation, for example, the reference telescopic curve is an IDD (Integrated Depth Dose) curve of the dose distribution obtained by Monte Carlo simulation, and the reference deflection curve is a Profile (transverse dose distribution) curve of the dose distribution obtained by Monte Carlo simulation.

[0119] In addition, based on the reference expansion and contraction curves and reference deflection curves of the particles in the target material, a more refined radiotherapy plan can be formulated, which enables the treatment to better target the diseased area and maximize the protection of the surrounding normal tissues. For example, based on the reference expansion and contraction curves and reference deflection curves of the particles in the target material, treatment optimization can be performed based on the individual differences of different patients (some patients have deep lesions, some have shallow lesions, some have larger lesions, and some have smaller lesions). By adjusting the range and deflection conditions, personalized dose distribution can be achieved according to the patient's specific circumstances, thereby improving treatment efficacy and reducing side effects.

[0120] Thus, firstly, a reference expansion and contraction curve and a reference deflection curve of the particle transport in the target material are obtained. These curves describe the reference range and deflection behavior of the particle in the target material, and can be obtained by experimental measurement, simulation calculation or other methods. Secondly, the corresponding undetermined expansion and contraction coefficients and undetermined deflection coefficients are obtained for each node. Afterwards, based on the undetermined expansion and contraction coefficients and undetermined deflection coefficients of each node, the undetermined expansion and contraction curves and undetermined deflection curves are calculated. These curves can be obtained, for example, by interpolating the coefficients between the nodes to obtain a more continuous and smooth curve representation. If the undetermined expansion and contraction curve does not match the reference expansion and contraction curve, or the undetermined deflection curve does not match the reference deflection curve, it is necessary to adjust the undetermined expansion and contraction coefficients and / or undetermined deflection coefficients of one or more nodes. By adjusting these coefficients, the undetermined expansion and contraction curves and undetermined deflection curves are recalculated to match the reference curves (corresponding to themselves), and the current undetermined coefficients are output as the corresponding reference coefficients.

[0121] The advantage of doing this is that by obtaining reference expansion and contraction curves and reference deflection curves that match the reference dose distribution information, the expansion and deflection behavior of particles in the target material can be described more accurately; by adjusting the unknown coefficients according to the characteristics of the target material, it has high flexibility and adaptability, and can optimize the unknown coefficients of each node according to actual conditions to adapt to different target materials and treatment needs, providing customized dose calculation solutions.

[0122] Taking proton therapy as an example, suppose it is necessary to calculate the dose distribution of protons in water, and obtain the reference telescopic coefficient and reference deflection coefficient. The reference dose distribution information of protons in water is graphically represented as a dose distribution curve. Based on the reference dose distribution information, the reference telescopic curve and reference deflection curve of proton transport in water can be calculated. These curves describe the transport characteristics of protons at different depths and lateral positions. Assume that 50 nodes are selected for calculation, corresponding to different energies of protons. For each node, it is necessary to determine a pending telescopic coefficient and a pending deflection coefficient, for example, by initialization assignment. According to the pending telescopic coefficient and pending deflection coefficient of each node, the corresponding pending telescopic curve and pending deflection curve can be calculated. By comparing the pending telescopic curve with the reference telescopic curve and the pending deflection curve with the reference deflection curve, the degree of matching can be evaluated. If one or two pending curves do not match the reference curve, adjust the pending expansion coefficient and / or pending deflection coefficient of one or more nodes, recalculate to obtain the corrected pending expansion curve and pending deflection curve, and perform curve matching, coefficient adjustment, curve correction, curve matching, coefficient adjustment, curve correction... and other steps again until the two pending curves match the corresponding reference curves respectively, and the iterative process ends. Multiple iterative adjustments can be performed according to actual needs and the degree of matching. In each iteration, the pending expansion coefficient is first adjusted to match the reference expansion curve, and then the pending deflection coefficient is adjusted to match the reference deflection curve. Such a repeated iterative process can gradually optimize the degree of matching between the pending curve and the corresponding reference curve.

[0123] Through the above process, the reference expansion coefficient and reference deflection coefficient of each node can be obtained, which can be used for subsequent dose calculation and radiotherapy planning to improve treatment accuracy and treatment effect. In terms of numerical magnitude, the order of magnitude of the reference expansion coefficient is equivalent to the order of magnitude of the inverse of the density of the target material, and the reference deflection coefficient depends on factors such as particle energy and transport distance.

[0124] In some embodiments, the curve matching method can be used in combination with an optimization algorithm. For example, an optimization objective function can be defined, including the errors obtained by comparing two undetermined curves (the undetermined telescopic curve and the undetermined deflection curve) with their corresponding reference curves, and the coefficients are adjusted by iterative optimization to minimize the optimization objective function. Different weights can be set for the two undetermined curves. For example, the weight of the telescopic error corresponding to the undetermined telescopic curve is made greater than the weight of the deflection error corresponding to the undetermined deflection curve.

[0125] In some embodiments, obtaining the undetermined scaling coefficient and the undetermined deflection coefficient of each node includes:

[0126] Initialize and assign values ​​to the undetermined expansion coefficient and undetermined deflection coefficient of each node;

[0127] The undetermined expansion coefficient of each node is set to the inverse of the density of the target material, and the undetermined deflection coefficient of each node is set to 1.

[0128] Thus, the undetermined expansion coefficient and undetermined deflection coefficient of each node are initialized and assigned. The initialization assignment can be set based on empirical values, theoretical models or other known data. This facilitates further adjustment of the undetermined expansion coefficient and undetermined deflection coefficient of each node according to actual needs and goals.

[0129] The adjustment can be based on experimental data, simulation calculation results or optimization algorithms. When adjusting the coefficient, a step adjustment method can be adopted, and the step can be set manually or obtained based on experimental data or simulation calculations.

[0130] The advantage of doing this is that by initializing and assigning values ​​to the pending expansion coefficient and the pending deflection coefficient of each node and adjusting them according to actual needs, it has high flexibility and adjustability. Subsequently, the pending coefficients (including the pending expansion coefficient and the pending deflection coefficient) can be optimized according to different materials, different treatment goals and different needs to meet specific dose calculation requirements; by initializing and assigning values ​​to the pending expansion coefficient and the pending deflection coefficient, the implementation process of the coefficient acquisition method is simplified. This simplicity helps to improve calculation efficiency and reduce the difficulty of operation in practical applications.

[0131] In some embodiments, obtaining the undetermined scaling coefficient and the undetermined deflection coefficient of each node includes:

[0132] A randomized algorithm is used to generate the undetermined expansion coefficient and undetermined deflection coefficient of each node.

[0133] In some embodiments, the step of calculating a pending scaling curve and a pending deflection curve according to a pending scaling coefficient and a pending deflection coefficient of each node includes:

[0134] The undetermined expansion coefficient and undetermined deflection coefficient of each discrete point between adjacent nodes are calculated by interpolation;

[0135] The undetermined expansion curve and the undetermined deflection curve are generated according to the undetermined expansion coefficient and the undetermined deflection coefficient of each discrete point between the plurality of nodes and the adjacent nodes.

[0136] Thus, the undetermined expansion coefficient and undetermined deflection coefficient of each discrete point between adjacent nodes (i.e., every two adjacent nodes) are calculated by interpolation. The interpolation method can be linear interpolation, spline interpolation or other interpolation methods, and an appropriate method can be selected according to actual needs. Based on the undetermined expansion coefficients and undetermined deflection coefficients of multiple nodes and the undetermined expansion coefficients and undetermined deflection coefficients of discrete points between adjacent nodes, a undetermined expansion curve and an undetermined deflection curve are generated. These curves are obtained by connecting and smoothing the undetermined coefficients of the nodes and the discrete points to obtain a continuous curve representation. Specifically, for example, the undetermined expansion curve can be generated according to the undetermined expansion coefficients and undetermined deflection coefficients of multiple nodes and the undetermined expansion coefficients and undetermined deflection coefficients of each discrete point between adjacent nodes; the undetermined deflection curve can be generated according to the undetermined expansion coefficients and undetermined deflection coefficients of multiple nodes and the undetermined expansion coefficients and undetermined deflection coefficients of each discrete point between adjacent nodes.

[0137] The advantage of doing this is that by using interpolation to calculate the unknown coefficients of discrete points between adjacent nodes, continuous and smooth unknown expansion and contraction curves and unknown deflection curves can be obtained, which helps to more accurately describe the expansion and contraction and deflection behavior of particles in the target material and improve the accuracy of dose calculation; by adjusting the interpolation method and the number of nodes of the unknown coefficients, the shape and accuracy of the unknown expansion and contraction curves and the unknown deflection curves can be flexibly adjusted according to actual needs, so that the coefficient calculation method can adapt to different materials and treatment scenarios and provide personalized dose calculation solutions.

[0138] In some embodiments, the process of adjusting the pending scaling factor and / or the pending deflection factor of one or more nodes includes:

[0139] When the pending scaling curve does not match the reference scaling curve, adjusting the pending scaling coefficients of one or more nodes, and recalculating the pending scaling curve according to the pending scaling coefficient and the pending deflection coefficient of each node, so that the pending scaling curve matches the reference scaling curve;

[0140] When the pending expansion curve matches the reference expansion curve and the pending deflection curve does not match the reference deflection curve, the pending deflection coefficients of one or more nodes are adjusted, and the pending deflection curve is recalculated according to the pending expansion coefficient and the pending deflection coefficient of each node, so that the pending deflection curve matches the reference deflection curve.

[0141] Different importance levels are set for the expansion coefficient and the deflection coefficient. Specifically, when the pending expansion curve does not match the reference expansion curve, regardless of whether the pending deflection curve matches the reference deflection curve, the pending expansion curve is corrected first (by adjusting the pending expansion coefficient of one or more nodes). When the pending expansion curve matches the reference expansion curve: if the pending deflection curve matches the reference deflection curve, the pending expansion coefficient and the pending deflection coefficient of each node are output as the reference expansion coefficient and the reference deflection coefficient; if the pending deflection curve does not match the reference deflection curve, the pending deflection curve is corrected (by adjusting the pending deflection coefficient of one or more nodes).

[0142] Thus, when the pending telescoping curve does not match the reference telescoping curve, the pending telescoping coefficient of one or more nodes is adjusted. By changing the pending telescoping coefficient, the pending telescoping curve is recalculated according to the pending deflection coefficient and the adjusted pending telescoping coefficient to match the reference telescoping curve, that is, the shape of the pending telescoping curve is changed by adjusting the coefficient size of the node. After the pending telescoping curve matches the reference telescoping curve, if the pending deflection curve does not match the reference deflection curve, the pending deflection coefficient of one or more nodes is adjusted. By changing the pending deflection coefficient, the pending deflection curve is recalculated according to the pending telescoping coefficient and the adjusted pending deflection coefficient to match the reference deflection curve, that is, the shape of the pending deflection curve is changed by adjusting the coefficient size of the node.

[0143] The advantage of doing this is that by adjusting the pending expansion coefficient and the pending deflection coefficient, the pending expansion curve can be matched with the reference expansion curve, and the pending deflection curve can be matched with the reference deflection curve. By adjusting the node coefficient, the shape and matching degree of the pending expansion curve and the pending deflection curve can be flexibly adjusted, so that the coefficient calculation method can adapt to different treatment needs and goals, and realize personalized dose calculation and optimization.

[0144] In some embodiments, the process of adjusting the pending scaling factor and / or the pending deflection factor of one or more nodes further includes:

[0145] After the pending deflection curve matches the reference deflection curve, re-detecting whether the pending expansion curve matches the reference expansion curve;

[0146] If the pending expansion curve does not match the reference expansion curve, the pending expansion coefficients of one or more nodes are adjusted again, and the pending expansion curve is calculated again according to the pending expansion coefficient and the pending deflection coefficient of each node until the pending expansion curve matches the reference expansion curve.

[0147] The pending expansion curve is jointly determined by the pending expansion coefficient and the pending deflection coefficient. Although the importance of the two is different, in terms of the impact on the pending expansion curve, the "importance score of the pending expansion coefficient to the pending expansion curve" is greater than the "importance score of the pending deflection coefficient to the pending expansion curve". In order to correct the pending deflection curve, the pending deflection coefficient is adjusted, which will cause the pending expansion curve to change. When this change is small, it may not affect the matching degree between the pending expansion curve and the reference expansion curve, that is, the pending expansion curve and the reference expansion curve remain matched. When this change is large, it may cause the pending expansion curve and the reference expansion curve to no longer match.

[0148] After the pending deflection curve matches the reference deflection curve, the matching of the pending expansion curve and the reference expansion curve is re-detected. When the correction of the pending deflection curve causes the pending expansion curve to not match the reference expansion curve, it is necessary to adjust the pending expansion coefficient of one or more nodes. By changing the pending expansion coefficient, the pending expansion curve is recalculated (or the pending expansion curve is corrected) to match the reference expansion curve. This can be achieved by adjusting the coefficient size of the node or by changing the position of the node. As needed, one-time fine-tuning or multiple iterative adjustments can be performed. In each iteration, the pending expansion curve is first corrected to match the reference expansion curve, and then the pending deflection curve is detected and corrected until the required curve matching accuracy is achieved.

[0149] The advantage of doing this is that the pending expansion curve and the pending deflection curve can be flexibly adjusted to achieve the required matching accuracy, with good adjustability and adaptability; through repeated adjustment, correction and matching processes, a reference expansion coefficient and a reference deflection coefficient that match the reference dose distribution information can be obtained, which helps to accurately calculate the transport characteristics of particles in the target material, provide accurate dose calculation results, and guide the radiotherapy process.

[0150] In some embodiments, the particle is a proton; or,

[0151] The particles are any particles corresponding to proton therapy.

[0152] Therefore, when the particles are protons, Monte Carlo simulation or radiation transport model and other methods are used to simulate the transport process of protons in the target material, and obtain reference dose distribution information of protons in the target material, and further calculate the reference expansion and contraction curve and reference deflection curve of the protons, so as to obtain the expansion and deflection coefficients of the protons in the target material.

[0153] When the particles are any type of particles corresponding to proton therapy, a similar method is used to simulate the transport process of these particles in the target material using Monte Carlo simulation or radiation transport model, and obtain corresponding reference dose distribution information, and then calculate the reference expansion and contraction curves and reference deflection curves of these particles to obtain corresponding expansion and deflection coefficients.

[0154] Particles corresponding to proton therapy may include, for example, primary particles, secondary electrons, secondary fragments, etc. Primary particles mainly lose energy through ionization interactions with matter; secondary electrons originate from ionization interactions between primary particles, secondary fragments and matter, and lose energy through ionization with matter; secondary fragments are produced by nuclear reactions between primary particles and matter, in which charged nuclear fragments (such as H-2, H-3, He-3, etc.) lose energy through ionization interactions, and uncharged fragments such as neutrons mainly lose energy through elastic and inelastic collisions with matter.

[0155] The advantage of this method is that it can be flexibly applied to protons and other particles corresponding to proton therapy. Whether it is proton particles or other particles, this method can obtain their expansion and deflection coefficients in the target material, realize accurate dose calculation, predict and control the shape and range of dose distribution, which can improve the accuracy of radiotherapy, reduce the radiation dose to normal tissues, and protect the health of patients.

[0156] In some embodiments, the target material is a human organ material, and the method further comprises:

[0157] According to the incident information of the particle and the reference expansion coefficient and reference deflection coefficient of each node where the particle is transported in the human organ material, the transport process of the particle in the human organ is simulated to calculate the simulated dose distribution information of the particle; wherein the incident information of the particle includes the particle type, particle energy and particle incident direction.

[0158] Thus, firstly, the incident information of the particles is obtained, including the type of particles, the direction of the particle incident, the incident position, the incident angle, the (incident) particle energy, etc. This information is used to determine the initial state of the particles in the target material. According to the reference expansion coefficient and the reference deflection coefficient of each node, it is applied to the dose calculation process of the particles. These reference coefficients represent the expansion and deflection characteristics of the particles at the corresponding nodes. Using the incident information and the reference expansion coefficient and the reference deflection coefficient of the node, the simulated dose distribution information of the particles in the target material (human organ material) is obtained by calculation. This process is based on the transport process of the particles and the reference coefficients applied.

[0159] The advantage of doing so is that by combining the incident information of the particles with the reference telescopic coefficient and reference deflection coefficient of the nodes for simulation calculation, more accurate simulated dose distribution information can be obtained, which helps to improve the precision and accuracy of the radiotherapy plan; based on the incident information of the particles and the reference telescopic coefficient and reference deflection coefficient of the nodes, personalized dose calculation can be performed for each patient or each treatment situation, which enables the treatment plan to better adapt to the specific needs and situations of specific patients; accurate calculation of the simulated dose distribution information of the particles helps to better grasp the shape and range of the dose distribution, and then optimize the radiotherapy plan, which can improve the effect of treatment, increase the dose received by the tumor focus (or lesion), and reduce unnecessary radiation to the surrounding healthy tissues. In summary, by performing simulation calculations based on the incident information of the particles and the reference telescopic coefficient and reference deflection coefficient of the nodes, more accurate and personalized dose calculations can be provided, thereby improving the effect and accuracy of radiotherapy.

[0160] See also Figure 2 , Figure 2 It is a flow chart of another coefficient acquisition method for dose calculation provided in an embodiment of the present application.

[0161] In a specific application scenario, an embodiment of the present application further provides a coefficient acquisition method for dose calculation, the method comprising:

[0162] S1: using a Monte Carlo algorithm or a radiation transport model to simulate the transport process of particles in a target material to obtain reference dose distribution information of the particles transported in the target material; the particles are protons; and the target material is a human organ material;

[0163] S2: Divide the particle energy in an unequal manner to obtain multiple nodes; each node corresponds to a different particle energy; the number of nodes is N; among the N nodes, the average spacing of the particle energies corresponding to the first M nodes is smaller than the average spacing of the particle energies corresponding to the last M nodes; N and M are positive integers, and N>2M.

[0164] S3: according to the reference dose distribution information, obtaining a reference expansion and contraction curve and a reference deflection curve of the particle transported in the target material; wherein the reference dose distribution information is, for example, dose distribution information calculated by Monte Carlo simulation, the reference expansion and contraction curve is, for example, an IDD curve of dose distribution obtained by Monte Carlo software simulation, and the reference deflection curve is, for example, a Profile curve of dose distribution obtained by Monte Carlo software simulation;

[0165] S4: Initializing and assigning values ​​to the undetermined expansion coefficient and the undetermined deflection coefficient of each node; wherein the undetermined expansion coefficient of each node is set to the inverse of the density of the target material, and the undetermined deflection coefficient of each node is set to 1;

[0166] S5: Calculate the undetermined expansion coefficient and undetermined deflection coefficient of each discrete point between adjacent nodes by interpolation;

[0167] S6: generating the to-be-determined expansion curve and the to-be-determined deflection curve according to the to-be-determined expansion coefficient and the to-be-determined deflection coefficient of each discrete point between the plurality of nodes and adjacent nodes;

[0168] S7: Detect whether the pending scaling curve matches the reference scaling curve; if they do not match, execute S8; if they match, execute S9;

[0169] S8: adjusting the undetermined scaling coefficient of one or more nodes to correct the undetermined scaling curve so that the undetermined scaling curve matches the reference scaling curve; executing S9;

[0170] S9: Detect whether the pending deflection curve matches the reference deflection curve; if not, execute S10; if they match, execute S13;

[0171] S10: adjusting the pending deflection coefficients of one or more nodes to correct the pending deflection curve so that the pending deflection curve matches the reference deflection curve; executing S11;

[0172] S11: re-detecting whether the pending scaling curve matches the reference scaling curve; if they do not match, executing S12; if they match, executing S13;

[0173] S12: adjusting the pending scaling coefficient of one or more nodes by a relatively small amount to correct the pending scaling curve, so that the pending scaling curve matches the reference scaling curve; executing S13; wherein the relatively small amount of adjustment refers to fine-tuning, for example, adjustment can be made by a relatively small step;

[0174] S13: outputting the undetermined expansion coefficient and the undetermined deflection coefficient of each node as the reference expansion coefficient and the reference deflection coefficient of the corresponding node;

[0175] S14: According to the incident information of the particle and the reference expansion coefficient and reference deflection coefficient of each node where the particle is transported in the human organ material, the transport process of the particle in the human organ is simulated to calculate the simulated dose distribution information of the particle; wherein the incident information of the particle includes the particle type, particle energy and particle incident direction.

[0176] In order to obtain the expansion and deflection coefficients of protons in different substances, this embodiment proposes a new method for obtaining the range expansion and deflection coefficients of protons in different substances. By adjusting the expansion and deflection coefficients under a series of energies (nodes), the calculated undetermined IDD curve and undetermined Profile curve are made to match the IDD curve and Profile curve of the dose distribution obtained by Monte Carlo software simulation, thereby obtaining the reference expansion and deflection coefficients of the energy protons in the substance, which is an accurate, simple and intuitive method for obtaining the transport characteristics of protons in different substances. In addition, through limited coefficient adjustment steps, the method of obtaining the correlation coefficient is simplified, and the corresponding effect can be intuitively seen.

[0177] In steps S7, S9, and S11, it is respectively detected whether the undetermined curve matches the reference curve corresponding to itself. In addition to the curve matching detection method based on multiple preset depths mentioned above, the method for detecting whether the two curves match can also be any of the following:

[0178] 1. Difference metric: Calculate the mean absolute error (MAE), mean square error (MSE), or root mean square error (RMSE) between the reference curve and the curve to be determined. These metrics can quantify the average difference between the two curves. For example, when the mean square error is less than the preset mean square error, it is confirmed that the curve to be determined matches the reference curve; when the mean square error is not less than the preset mean square error, it is confirmed that the curve to be determined does not match the reference curve.

[0179] 2. Curve alignment and shape analysis: This approach can provide better results in nonlinear and complex situations.

[0180] 3. Pearson correlation coefficient: This coefficient measures whether two data sets are on the same line, and the value is between -1 and 1. If the Pearson correlation coefficient of two curves is close to 1, then the two curves can be considered to match.

[0181] 4. Node sequence analysis: For node sequence data, sequence analysis methods can be used to compare the similarity of two curves, such as autocorrelation function, difference, etc.

[0182] 5. Machine learning method and deep learning method: Use machine learning algorithm or deep learning algorithm to train the initial model to obtain a similarity model, and predict the similarity of two curves through the similarity model. The initial model to be trained is, for example, a regression model, a support vector machine (SVM), a convolutional neural network (CNN), a recurrent neural network (RNN), a generative adversarial network (GAN), a residual network (ResNet), reinforcement learning (RL), transfer learning, etc. When the similarity between the curve to be determined and the reference curve is greater than the preset similarity, it is confirmed that the curve to be determined matches the reference curve; when the similarity between the curve to be determined and the reference curve is not greater than the preset similarity, it is confirmed that the curve to be determined does not match the reference curve.

[0183] According to the above method, a quantitative or qualitative evaluation can be performed to detect whether the proposed expansion curve matches the reference expansion curve, and whether the proposed deflection curve matches the reference deflection curve. When the two curves are matched, if the proposed curve does not match the reference curve, it is necessary to adjust the proposed expansion coefficient and / or the proposed deflection coefficient of one or more nodes, and recalculate the corrected proposed curve until a better matching degree is achieved.

[0184] In the embodiment of the present application, the two pending curves can be adjusted as a whole, or the two curves can be adjusted in sections based on different depths. Specifically, for each preset depth, the pending telescopic curve can be detected and corrected first, and then the pending deflection curve can be detected and corrected. After the two pending curves are corrected at the current preset depth, the two pending curves are detected and corrected for the next preset depth.

[0185] In some embodiments, obtaining a reference expansion coefficient and a reference deflection coefficient of each node of the particle transported in the target material according to the reference dose distribution information includes:

[0186] According to the reference dose distribution information, obtaining a reference expansion and contraction curve and a reference deflection curve of the particles transported in the target material;

[0187] Obtain the undetermined expansion coefficient and undetermined deflection coefficient of each node;

[0188] According to the undetermined expansion coefficient and the undetermined deflection coefficient of each node, a undetermined expansion curve and an undetermined deflection curve are calculated;

[0189] When the pending expansion curve does not match the reference expansion curve at one or more preset depths and / or the pending deflection curve does not match the reference deflection curve at one or more preset depths, adjusting the pending expansion coefficient and / or pending deflection coefficient of one or more nodes so that the recalculated pending expansion curve matches the reference expansion curve and the recalculated pending deflection curve matches the reference deflection curve, thereby obtaining a reference expansion coefficient and a reference deflection coefficient of each node;

[0190] The matching of the pending telescopic curve and the reference telescopic curve at the preset depth means that the deviation of the two curves at the preset depth is less than a first preset ratio, and the mismatch of the pending telescopic curve and the reference telescopic curve at the preset depth means that the deviation of the two curves at the preset depth is not less than a first preset ratio;

[0191] The pending deflection curve matches the reference deflection curve at the preset depth, which means that the deviation of the two curves at the preset depth is less than a second preset ratio; the pending deflection curve does not match the reference deflection curve at the preset depth, which means that the deviation of the two curves at the preset depth is not less than a second preset ratio;

[0192] The process of adjusting the undetermined expansion coefficient and / or the undetermined deflection coefficient of one or more nodes includes:

[0193] In order of preset depth from small to large, for each preset depth, perform the following processing:

[0194] When the pending telescopic curve does not match the reference telescopic curve at the preset depth, adjusting the pending telescopic coefficients of one or more nodes, and recalculating the pending telescopic curve according to the pending telescopic coefficient and the pending deflection coefficient of each node, so that the pending telescopic curve matches the reference telescopic curve at the preset depth;

[0195] When the pending telescopic curve matches the reference telescopic curve at the preset depth and the pending deflection curve does not match the reference deflection curve at the preset depth, the pending deflection coefficients of one or more nodes are adjusted, and the pending deflection curve is recalculated according to the pending telescopic coefficient and the pending deflection coefficient of each node, so that the pending deflection curve matches the reference deflection curve at the preset depth.

[0196] For example, first, for the first preset depth: detect whether the pending telescopic curve matches the reference telescopic curve at the first preset depth; if they do not match, adjust the pending telescopic coefficients of one or more nodes to correct the pending telescopic curve, so that the pending telescopic curve matches the reference telescopic curve at the first preset depth; detect whether the pending deflection curve matches the reference deflection curve at the first preset depth; if they do not match, adjust the pending deflection coefficients of one or more nodes to correct the pending deflection curve, so that the pending deflection curve matches the reference deflection curve at the first preset depth;

[0197] Secondly, for the second preset depth: detecting whether the pending telescopic curve matches the reference telescopic curve at the second preset depth; if not, adjusting the pending telescopic coefficients of one or more nodes to correct the pending telescopic curve, so that the pending telescopic curve matches the reference telescopic curve at the second preset depth; detecting whether the pending deflection curve matches the reference deflection curve at the second preset depth; if not, adjusting the pending deflection coefficients of one or more nodes to correct the pending deflection curve, so that the pending deflection curve matches the reference deflection curve at the second preset depth;

[0198] Then, for the third preset depth: detecting whether the pending telescopic curve matches the reference telescopic curve at the third preset depth; if not, adjusting the pending telescopic coefficients of one or more nodes to correct the pending telescopic curve, so that the pending telescopic curve matches the reference telescopic curve at the third preset depth; detecting whether the pending deflection curve matches the reference deflection curve at the third preset depth; if not, adjusting the pending deflection coefficients of one or more nodes to correct the pending deflection curve, so that the pending deflection curve matches the reference deflection curve at the third preset depth;

[0199] …

[0200] This process is deduced in this way until the detection and correction of the two pending curves are completed for all preset depths.

[0201] It should be noted that, under the premise of being practicable, the order of the steps in the above embodiments can be adjusted, and this application is not limited to this.

[0202] (Radiation Therapy System)

[0203] The present application also provides a radiotherapy system, including:

[0204] A coefficient acquisition device, used to calculate a reference expansion coefficient and a reference deflection coefficient of each node of particle transport in a human organ material by using any of the above coefficient acquisition methods for dose calculation;

[0205] A dose calculation device, used for simulating the transport process of the particles in the human organ according to the incident information of the particles and the reference expansion coefficient and reference deflection coefficient of each node of the particles transported in the human organ material, so as to calculate the simulated dose distribution information of the particles; wherein the incident information of the particles includes the type of particles, the energy of the particles and the incident direction of the particles;

[0206] The device for determining human body dose is used to determine the dose used in radiotherapy according to the expected dose distribution information after the simulated dose distribution information of the particles matches the expected dose distribution information.

[0207] In the radiotherapy system, the coefficient acquisition device uses one of the above-mentioned coefficient acquisition methods to calculate the reference expansion coefficient and reference deflection coefficient of each node in the target material (i.e., human organ material) where the particles are transported. These coefficients are calculation results based on the particle transport characteristics. The dose calculation device uses the incident information of the particles and the reference expansion coefficient and reference deflection coefficient of each node to calculate the simulated dose distribution information of the particles in the target material. This process is based on the simulation algorithm and the applied reference coefficients. After the simulated dose distribution information of the particles matches the expected dose distribution information, the device for determining the human body dose uses the expected dose distribution information to determine the dose used in the radiotherapy. Based on the patient's specific situation and treatment needs, the device can provide a personalized dose plan based on the simulation results.

[0208] The advantage of this is that by using the coefficient acquisition device and the dose calculation device, the system can accurately calculate the simulated dose distribution of particles in the target material, which provides accurate control and evaluation of the radiotherapy dose, ensuring the accuracy and safety of the treatment; by using the device for determining the human body dose, the system can provide a personalized dose plan based on the patient's specific situation and treatment needs, which helps to optimize the treatment plan and minimize damage to normal tissues while ensuring effective treatment of tumor tissues; the radiotherapy system can improve the effect of treatment by accurately calculating the dose distribution and providing a personalized dose plan, which helps to increase the dose received by the tumor lesion while reducing the radiation to healthy tissues, improving the success rate of treatment and the quality of life of patients. In summary, the radiotherapy system uses the coefficient acquisition device, the dose calculation device and the device for determining the human body dose to achieve accurate dose calculation and personalized treatment plans, thereby improving the effect and safety of radiotherapy.

[0209] (Electronic equipment)

[0210] The embodiment of the present application also provides an electronic device, the specific embodiment of which is consistent with the embodiment recorded in the above method embodiment and the technical effects achieved, and some contents will not be repeated here.

[0211] The electronic device comprises a memory and at least one processor, the memory stores a computer program, and the at least one processor is configured to implement the following steps when executing the computer program:

[0212] Obtain reference dose distribution information of particles transported in target materials;

[0213] Get multiple nodes;

[0214] According to the reference dose distribution information, a reference expansion coefficient and a reference deflection coefficient of each node of the particle transport in the target material are obtained.

[0215] In some embodiments, the at least one processor is configured to acquire reference dose distribution information of particles transported in the target material in the following manner when executing the computer program:

[0216] The transport process of the particles in the target material is simulated using a Monte Carlo algorithm or a radiation transport model to obtain reference dose distribution information of the particles transported in the target material.

[0217] In some embodiments, the at least one processor is configured to obtain the plurality of nodes in the following manner when executing the computer program:

[0218] The particle energy is divided in an unequally spaced manner to obtain a plurality of nodes, wherein each node corresponds to a different particle energy.

[0219] In some embodiments, the number of nodes is N;

[0220] Among N nodes, the average spacing of particle energies corresponding to the first M nodes is smaller than the average spacing of particle energies corresponding to the last M nodes;

[0221] Wherein, N and M are positive integers, and N>2M.

[0222] In some embodiments, the at least one processor is configured to acquire a reference stretch coefficient and a reference deflection coefficient of each node of the particle transport in the target material according to the reference dose distribution information in the following manner when executing the computer program:

[0223] A statistical method or an optimization algorithm is used to obtain a reference expansion coefficient and a reference deflection coefficient of each node corresponding to the reference dose distribution information; wherein the optimization algorithm includes any one of a genetic algorithm, a particle swarm algorithm, and a simulated annealing algorithm.

[0224] In some embodiments, the at least one processor is configured to acquire a reference stretch coefficient and a reference deflection coefficient of each node of the particle transport in the target material according to the reference dose distribution information in the following manner when executing the computer program:

[0225] According to the reference dose distribution information, obtaining a reference expansion and contraction curve and a reference deflection curve of the particles transported in the target material;

[0226] Obtain the undetermined expansion coefficient and undetermined deflection coefficient of each node;

[0227] According to the undetermined expansion coefficient and the undetermined deflection coefficient of each node, a undetermined expansion curve and an undetermined deflection curve are calculated;

[0228] When the pending scaling curve does not match the reference scaling curve and / or the pending deflection curve does not match the reference deflection curve, the pending scaling coefficient and / or the pending deflection coefficient of one or more nodes are adjusted so that the recalculated pending scaling curve matches the reference scaling curve and the recalculated pending deflection curve matches the reference deflection curve, thereby obtaining a reference scaling coefficient and a reference deflection coefficient of each node.

[0229] In some embodiments, the at least one processor is configured to obtain the undetermined scaling factor and the undetermined deflection factor of each node in the following manner when executing the computer program:

[0230] Initialize and assign values ​​to the undetermined expansion coefficient and undetermined deflection coefficient of each node;

[0231] The undetermined expansion coefficient of each node is set to the inverse of the density of the target material, and the undetermined deflection coefficient of each node is set to 1.

[0232] In some embodiments, the at least one processor is configured to calculate a pending scaling curve and a pending deflection curve according to a pending scaling factor and a pending deflection factor of each node in the following manner when executing the computer program:

[0233] The undetermined expansion coefficient and undetermined deflection coefficient of each discrete point between adjacent nodes are calculated by interpolation;

[0234] The undetermined expansion curve and the undetermined deflection curve are generated according to the undetermined expansion coefficient and the undetermined deflection coefficient of each discrete point between the plurality of nodes and the adjacent nodes.

[0235] In some embodiments, the at least one processor is configured to adjust the undetermined scaling factor and / or the undetermined deflection factor of one or more nodes in the following manner when executing the computer program:

[0236] When the pending scaling curve does not match the reference scaling curve, adjusting the pending scaling coefficients of one or more nodes, and recalculating the pending scaling curve according to the pending scaling coefficient and the pending deflection coefficient of each node, so that the pending scaling curve matches the reference scaling curve;

[0237] When the pending expansion curve matches the reference expansion curve and the pending deflection curve does not match the reference deflection curve, the pending deflection coefficients of one or more nodes are adjusted, and the pending deflection curve is recalculated according to the pending expansion coefficient and the pending deflection coefficient of each node, so that the pending deflection curve matches the reference deflection curve.

[0238] In some embodiments, the at least one processor is configured to, when executing the computer program, further adjust the pending scaling factor and / or the pending deflection factor of one or more nodes in the following manner:

[0239] After the pending deflection curve matches the reference deflection curve, re-detecting whether the pending expansion curve matches the reference expansion curve;

[0240] If the pending expansion curve does not match the reference expansion curve, the pending expansion coefficients of one or more nodes are adjusted again, and the pending expansion curve is calculated again according to the pending expansion coefficient and the pending deflection coefficient of each node until the pending expansion curve matches the reference expansion curve.

[0241] In some embodiments, the particle is a proton; or,

[0242] The particles are any particles corresponding to proton therapy.

[0243] In some embodiments, the target material is a human organ material, and the at least one processor is configured to further implement the following steps when executing the computer program:

[0244] According to the incident information of the particle and the reference expansion coefficient and reference deflection coefficient of each node where the particle is transported in the human organ material, the transport process of the particle in the human organ is simulated to calculate the simulated dose distribution information of the particle; wherein the incident information of the particle includes the particle type, particle energy and particle incident direction.

[0245] See also Figure 3 , Figure 3 It is a structural block diagram of an electronic device 10 provided in an embodiment of the present application.

[0246] The electronic device 10 may include, for example, at least one memory 11 , at least one processor 12 , and a bus 13 connecting different platform systems.

[0247] The memory 11 may include a (computer) readable medium in the form of a volatile memory, such as a random access memory (RAM) 111 and / or a cache memory 112, and may further include a read-only memory (ROM) 113. The memory 11 also stores a computer program, which can be executed by the processor 12, so that the processor 12 implements the steps of any of the above methods. The memory 11 may also include a utility 114 having at least one program module 115, such program module 115 includes but is not limited to: an operating system, one or more application programs, other program modules and program data, each of which or some combination thereof may include the implementation of a network environment.

[0248] Accordingly, the processor 12 may execute the above-mentioned computer program and may execute the utility 114. The processor 12 may be implemented by one or more application specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field programmable gate arrays (FPGAs), or other electronic components.

[0249] The bus 13 may be a local bus representing one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, or any of a variety of bus architectures.

[0250] The electronic device 10 may also communicate with one or more external devices such as a keyboard, a pointing device, a Bluetooth device, etc., and may also communicate with one or more devices that can interact with the electronic device 10, and / or communicate with any device (such as a router, a modem, etc.) that enables the electronic device 10 to communicate with one or more other computing devices. Such communication may be performed through an input / output interface 14. In addition, the electronic device 10 may also communicate with one or more networks (such as a local area network (LAN), a wide area network (WAN) and / or a public network, such as the Internet) through a network adapter 15. The network adapter 15 may communicate with other modules of the electronic device 10 through the bus 13. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 10 in actual applications, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms.

[0251] (Computer readable storage medium)

[0252] The embodiment of the present application also provides a computer-readable storage medium, and its specific embodiment is consistent with the embodiment recorded in the above method embodiment and the technical effects achieved, and some contents will not be repeated here.

[0253] The computer-readable storage medium stores a computer program, and when the computer program is executed by at least one processor, the steps of any of the above methods or the functions of any of the above electronic devices are implemented.

[0254] Computer readable medium can be a computer readable signal medium or a computer readable storage medium. In an embodiment of the present application, a computer readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it. Computer readable storage medium can be, for example, but not limited to, a system, device or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples (non-exhaustive list) of computer readable storage medium include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0255] The computer-readable storage medium may include a data signal propagated in a baseband or as part of a carrier wave, wherein a readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable storage medium may also be any computer-readable medium that can send, propagate, or transmit a program for use by an instruction execution system, an apparatus, or a device or used in combination with it. The program code contained on the computer-readable storage medium may be transmitted with any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the above. The program code for performing the operation of the present invention may be written in any combination of one or more programming languages, including Java, C++, Python, C#, JavaScript, PHP, Ruby, Swift, Go, Kotlin, etc. The program code may be executed entirely on a user computing device, partially on a user device, as a separate software package, partially on a user device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, the remote computing device may be connected to the user device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., through the Internet using an Internet service provider).

[0256] (Computer Program Product)

[0257] The embodiment of the present application also provides a computer program product, the specific embodiments of which are consistent with the embodiments recorded in the above method embodiments and the technical effects achieved, and some contents will not be repeated here.

[0258] The present application provides a computer program product, which includes a computer program. When the computer program is executed by at least one processor, the steps of any of the above methods or the functions of any of the above electronic devices are implemented.

[0259] See also Figure 4 , Figure 4 It is a structural diagram of a computer program product provided in an embodiment of the present application.

[0260] The computer program product is used to implement the steps of any of the above methods or to implement the functions of any of the above electronic devices. The computer program product may be a portable compact disk read-only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the computer program product of the present invention is not limited thereto, and the computer program product may be any combination of one or more computer-readable media.

[0261] This application is explained from the perspectives of purpose of use, effectiveness, progress and novelty, and has met the functional enhancement and usage requirements emphasized by the Patent Law. The above description and drawings of this application are only the preferred embodiments of this application, and are not intended to limit this application. Therefore, all structures, devices, features, etc. that are similar or identical to this application, that is, all equivalent replacements or modifications made in accordance with the scope of the patent application of this application, should fall within the scope of protection of the patent application of this application.

Claims

1. A coefficient acquisition method for dose calculation, characterized in that: The method comprises: Obtain reference dose distribution information of particles transported in target materials; According to the particle energy from small to large, the particle energy is divided in an unequal manner to obtain multiple nodes; wherein each node corresponds to a different particle energy; According to the reference dose distribution information, a reference expansion coefficient and a reference deflection coefficient of each node of the particle transport in the target material are obtained.

2. The coefficient acquisition method for dose calculation according to claim 1, characterized in that: The step of obtaining reference dose distribution information of particles transported in a target material comprises: The transport process of the particles in the target material is simulated using a Monte Carlo algorithm or a radiation transport model to obtain reference dose distribution information of the particles transported in the target material.

3. The coefficient acquisition method for dose calculation according to claim 1, characterized in that: The number of nodes is N; Among N nodes, the average spacing of particle energies corresponding to the first M nodes is smaller than the average spacing of particle energies corresponding to the last M nodes; Wherein, N and M are positive integers, and N>2M.

4. The coefficient acquisition method for dose calculation according to claim 1, characterized in that: The step of obtaining a reference expansion coefficient and a reference deflection coefficient of each node of the particle transport in the target material according to the reference dose distribution information comprises: A statistical method or an optimization algorithm is used to obtain a reference expansion coefficient and a reference deflection coefficient of each node corresponding to the reference dose distribution information; wherein the optimization algorithm includes any one of a genetic algorithm, a particle swarm algorithm, and a simulated annealing algorithm.

5. The coefficient acquisition method for dose calculation according to claim 1, characterized in that: The step of obtaining a reference expansion coefficient and a reference deflection coefficient of each node of the particle transport in the target material according to the reference dose distribution information comprises: According to the reference dose distribution information, obtaining a reference expansion and contraction curve and a reference deflection curve of the particles transported in the target material; Obtain the undetermined expansion coefficient and undetermined deflection coefficient of each node; According to the undetermined expansion coefficient and the undetermined deflection coefficient of each node, a undetermined expansion curve and an undetermined deflection curve are calculated; When the pending scaling curve does not match the reference scaling curve and / or the pending deflection curve does not match the reference deflection curve, the pending scaling coefficient and / or the pending deflection coefficient of one or more nodes are adjusted so that the recalculated pending scaling curve matches the reference scaling curve and the recalculated pending deflection curve matches the reference deflection curve, thereby obtaining a reference scaling coefficient and a reference deflection coefficient of each node.

6. The coefficient acquisition method for dose calculation according to claim 5, characterized in that: The obtaining of the undetermined expansion coefficient and the undetermined deflection coefficient of each node includes: Initialize and assign values ​​to the undetermined expansion coefficient and undetermined deflection coefficient of each node; The undetermined expansion coefficient of each node is set to the inverse of the density of the target material, and the undetermined deflection coefficient of each node is set to 1.

7. The coefficient acquisition method for dose calculation according to claim 6, characterized in that: The step of calculating the undetermined expansion curve and the undetermined deflection curve according to the undetermined expansion coefficient and the undetermined deflection coefficient of each node includes: The undetermined expansion coefficient and undetermined deflection coefficient of each discrete point between adjacent nodes are calculated by interpolation; The undetermined expansion curve and the undetermined deflection curve are generated according to the undetermined expansion coefficient and the undetermined deflection coefficient of each discrete point between the plurality of nodes and the adjacent nodes.

8. The coefficient acquisition method for dose calculation according to claim 6, characterized in that: The process of adjusting the pending expansion factor and / or the pending deflection factor of one or more nodes includes: When the pending scaling curve does not match the reference scaling curve, adjusting the pending scaling coefficients of one or more nodes, and recalculating the pending scaling curve according to the pending scaling coefficient and the pending deflection coefficient of each node, so that the pending scaling curve matches the reference scaling curve; When the pending expansion curve matches the reference expansion curve and the pending deflection curve does not match the reference deflection curve, the pending deflection coefficients of one or more nodes are adjusted, and the pending deflection curve is recalculated according to the pending expansion coefficient and the pending deflection coefficient of each node, so that the pending deflection curve matches the reference deflection curve.

9. The coefficient acquisition method for dose calculation according to claim 8, characterized in that: The process of adjusting the undetermined expansion coefficient and / or the undetermined deflection coefficient of one or more nodes further includes: After the pending deflection curve matches the reference deflection curve, re-detecting whether the pending expansion curve matches the reference expansion curve; If the pending expansion curve does not match the reference expansion curve, the pending expansion coefficients of one or more nodes are adjusted again, and the pending expansion curve is calculated again according to the pending expansion coefficient and the pending deflection coefficient of each node until the pending expansion curve matches the reference expansion curve.

10. The coefficient acquisition method for dose calculation according to any one of claims 1 to 9, characterized in that: The particle is a proton; or, The particles are any particles corresponding to proton therapy.

11. The coefficient acquisition method for dose calculation according to claim 10, characterized in that: The target material is a human organ material, and the method further comprises: According to the incident information of the particle and the reference expansion coefficient and reference deflection coefficient of each node where the particle is transported in the human organ material, the transport process of the particle in the human organ is simulated to calculate the simulated dose distribution information of the particle; wherein the incident information of the particle includes the particle type, particle energy and particle incident direction.

12. An electronic device, characterized in that: The electronic device comprises a memory and at least one processor, the memory stores a computer program, and the at least one processor is configured to implement the following steps when executing the computer program: Obtain reference dose distribution information of particles transported in target materials; According to the particle energy from small to large, the particle energy is divided in an unequal manner to obtain multiple nodes; wherein each node corresponds to a different particle energy; According to the reference dose distribution information, a reference expansion coefficient and a reference deflection coefficient of each node of the particle transport in the target material are obtained.

13. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by at least one processor, the steps of the method according to any one of claims 1 to 11 or the functions of the electronic device according to claim 12 are implemented.

14. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by at least one processor, the steps of the method according to any one of claims 1 to 11 or the functions of the electronic device according to claim 12 are implemented.

15. A radiotherapy system, characterized in that: include: A coefficient acquisition device, used to calculate the reference expansion coefficient and reference deflection coefficient of each node of particle transport in human organ material by using the coefficient acquisition method for dose calculation described in any one of claims 1 to 11; A dose calculation device, used for simulating the transport process of the particles in the human organ according to the incident information of the particles and the reference expansion coefficient and reference deflection coefficient of each node of the particles transported in the human organ material, so as to calculate the simulated dose distribution information of the particles; wherein the incident information of the particles includes the type of particles, the energy of the particles and the incident direction of the particles; The device for determining human body dose is used to determine the dose used in radiotherapy according to the expected dose distribution information after the simulated dose distribution information of the particles matches the expected dose distribution information.

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