CN115497599A

CN115497599A - Particle source model training method and dose distribution determining method of radiation therapy system

Info

Publication number: CN115497599A
Application number: CN202211192042.0A
Authority: CN
Inventors: 施智; 李江峰
Original assignee: Shanghai United Imaging Healthcare Co Ltd
Current assignee: Shanghai United Imaging Healthcare Co Ltd
Priority date: 2022-09-28
Filing date: 2022-09-28
Publication date: 2022-12-20

Abstract

The application relates to a particle source model training method and a dose distribution determining method of a radiation therapy system, wherein the method comprises the steps of obtaining a percentage depth calculation curve and an off-axis ratio calculation curve corresponding to a particle source based on input energy and a preset source model; acquiring a percentage depth measurement curve, an off-axis ratio measurement curve and an output factor measurement value of the radiotherapy system under the action of input energy; adjusting the correlation parameters determining the distribution of the particle sources in the preset source model according to the difference between the percent depth calculation curve and the percent depth measurement curve and the difference between the off-axis ratio calculation curve and the off-axis ratio measurement curve until the differences are within a preset error range; determining a correction factor of the output factor based on the output factor measured value and the adjusted preset source model; and correcting the adjusted preset source model based on the correction factor to obtain a particle source model. And the influence of a percent depth curve and an off-axis ratio curve is avoided based on the adjustment lag of the output factor, and the modeling speed and accuracy are improved.

Description

Particle source model training method and dose distribution determining method of radiation therapy system

Technical Field

The present application relates to the field of radiotherapy technology, and in particular, to a method for training a particle source model and a method for determining dose distribution of a radiotherapy system.

Background

Radiation therapy is one of the important means for treating malignant tumors. During radiation therapy, it is a critical issue to quickly and accurately determine the dose distribution in a patient.

Currently, methods for determining dose distribution are mainly classified into analytical methods and monte carlo methods. The analytic method has high calculation speed but poor calculation accuracy. The Monte Carlo method can accurately simulate the transport process of electrons and photons in the treatment head and the body of a patient, and has higher calculation accuracy.

However, in the implementation process, the applicant finds that, in the implementation scheme of the radiation therapy system simulated by adopting the monte carlo algorithm at present, different methods or source models are mostly used for simulating the radiation therapy system in the photon and electron irradiation modes, so that the modeling difficulty is increased, and the modeling speed is reduced.

Disclosure of Invention

In view of the above, it is necessary to provide a particle source model training method and a dose distribution determining method for an emission therapy system in a unified photon-electron irradiation mode, which are simple in modeling and fast in modeling speed.

In a first aspect, the present application provides a method for training a particle source model of a radiation therapy system, the method comprising:

acquiring a percentage depth calculation curve and an off-axis ratio calculation curve corresponding to a particle source based on input energy and a preset source model;

acquiring a percentage depth measurement curve, an off-axis ratio measurement curve and an output factor measurement value of a radiotherapy system under the action of input energy;

adjusting the correlation parameters determining the distribution of the particle sources in the preset source model according to the difference between the percent depth calculation curve and the percent depth measurement curve and the difference between the off-axis ratio calculation curve and the off-axis ratio measurement curve until the differences are within a preset error range;

determining a correction factor of the output factor based on the output factor measured value and the adjusted preset source model;

and correcting the adjusted preset source model based on the correction factor to obtain a particle source model.

In one embodiment, the particle source comprises a primary sub-source, a secondary sub-source, and a pollutant source.

In one embodiment, adjusting the correlation parameter determining the distribution of the particle source in the preset source model according to the difference between the depth-percentage calculation curve and the depth-percentage measurement curve and the difference between the off-axis ratio calculation curve and the off-axis ratio measurement curve includes:

and adjusting the weight of the percent depth curve in the preset source model based on the difference between the percent depth calculation curve and the percent depth measurement curve, so that the difference between the percent depth calculation curve and the percent depth measurement curve obtained based on the adjusted preset source model is within a first preset error range.

In one embodiment, the contaminated electron source comprises a contaminated photon source and/or a contaminated electron source, and the adjusting of the correlation parameter determining the distribution of the particle source in the preset source model according to the difference between the percent depth calculation curve and the percent depth measurement curve and the difference between the off-axis ratio calculation curve and the off-axis ratio measurement curve comprises:

for the condition that the radiotherapy system works in a photon irradiation mode, based on the difference between the built-up area of the percent depth calculation curve and the built-up area of the percent depth measurement curve, adjusting the weight of a polluted electron source and the size of the polluted electron source in a preset source model, and enabling the difference between the built-up area of the percent depth calculation curve and the built-up area of the percent depth measurement curve obtained based on the adjusted preset source model to be within a first preset area error range; and/or the presence of a gas in the gas,

and for the condition that the radiotherapy system works in the electronic irradiation mode, based on the difference between the polluted photon tail of the percentage depth calculation curve and the polluted photon tail of the percentage depth measurement curve, adjusting the weight of a polluted photon source and the size of a polluted photon source in the preset source model, so that the difference between the polluted photon tail of the percentage depth calculation curve and the polluted photon tail of the percentage depth measurement curve obtained based on the adjusted preset source model is in a second preset region error range.

and adjusting the size of a primary sub-source in the preset source model based on the difference between the penumbra region of the off-axis ratio calculation curve and the penumbra region of the off-axis ratio measurement curve, so that the error between the three-dimensional dose information of the penumbra region of the off-axis ratio calculation curve and the three-dimensional dose information of the penumbra region of the off-axis ratio measurement curve obtained based on the adjusted preset source model is within a preset dose error range.

In one embodiment, adjusting the correlation parameter determining the distribution of the particle source in the preset source model according to the difference between the percent depth calculation curve and the percent depth measurement curve and the difference between the off-axis ratio calculation curve and the off-axis ratio measurement curve includes:

and adjusting model parameters used for determining probability densities at different off-axes in the preset source model based on the difference between the off-axis ratio calculation curve in the field and the off-axis ratio measurement curve in the field, so that the difference between the off-axis ratio calculation curve in the field and the off-axis ratio measurement curve in the field obtained based on the adjusted preset source model is in a second preset error range.

In one embodiment, adjusting the model parameters in the preset source model for determining probability densities at different off-axes based on the difference between the off-axis ratio calculation curve in the field and the off-axis ratio measurement curve in the field comprises:

adjusting the correlation parameter of the probability density distribution function on the first sampling plane in the preset source model based on the difference between the off-axis ratio calculation curve in the field and the off-axis ratio measurement curve in the field; the first sampling plane is a sampling plane that reflects the distribution of radiation projected by the radiation therapy system in the selected irradiation mode.

In one embodiment, the probability density distribution function is a multi-segment linear distribution function, and adjusting parameters of the probability density distribution function on a first sampling plane in the preset source model includes:

and adjusting parameters of the multi-segment linear distribution function on a first sampling plane in the preset source model.

In one embodiment, adjusting the correlation parameters determining the distribution of the particle source in the preset source model according to the difference between the percent depth calculation curve and the percent depth measurement curve and the difference between the off-axis ratio calculation curve and the off-axis ratio measurement curve until the differences are within the preset error range includes:

and adjusting the size of a secondary sub source in the preset source model based on the difference between the off-axis ratio calculation curve in the field of radiation and the off-axis ratio measurement curve in the field of radiation, so that the difference between the off-axis ratio calculation curve in the field of radiation and the off-axis ratio measurement curve in the field of radiation obtained based on the adjusted preset source model is within a third preset error range.

In a second aspect, a dose distribution determination method for a radiation therapy system is provided, the method comprising:

acquiring energy to be input of a radiotherapy system;

determining a percentage depth calculation curve, an off-axis ratio calculation curve and an output factor calculation value of the radiotherapy system based on the energy to be input and a particle source model of the radiotherapy system;

wherein the particle source model is generated by performing the steps of the particle source model training method of the radiation therapy system.

The particle source model training method and the dose distribution determining method of the radiation therapy system at least have the following beneficial effects:

the particle source model of the radiotherapy system is obtained by adjusting the correlation parameters determining the distribution condition of each particle source in the preset source model until the difference between the calculated curve (the percent depth calculated curve and the off-axis ratio calculated curve) and the measured curve is within a preset error range, determining a correction factor based on the difference between the measured value of the output factor and the calculated value determined based on the adjusted preset source model at the moment, and correcting and optimizing the previously adjusted preset source model based on the correction factor.

The energy distribution condition in the radiotherapy system is represented by only defining the particle source, and the correlation parameters determining the particle source distribution condition in the preset source model are quickly adjusted by utilizing the difference between the calculated value and the actual measured value of the percent depth calculation curve and the off-axis ratio calculation curve, so that the modeling difficulty is reduced, and the modeling speed is increased. And considering that the adjustment of the output factor can influence the calculation curve of the percent depth and the calculation curve of the off-axis ratio, the adjustment of the preset source model is firstly carried out based on the difference between the calculation value and the measurement value of the calculation curve of the percent depth and the calculation curve of the off-axis ratio, and finally the adjusted preset source model is further adjusted based on the correction factor of the output factor, so that the modeling speed is increased, and the precision of the source model of the radiotherapy system is improved.

In addition, the probability density distribution function on the second sampling plane in the preset source model adopts a multi-section linear distribution function, so that the modeling difficulty of the radiotherapy system can be effectively reduced, and the modeling accuracy is improved. In addition, the number of probability density sections can be arbitrarily given to adapt to the off-axis ratio calculation curve characteristics of the accelerators of different manufacturers.

Drawings

FIG. 1 is a diagram of an exemplary embodiment of a method for training a particle source model and a method for determining a dose distribution of a radiation therapy system;

FIG. 2 is a schematic flow chart diagram of a method for training a particle source model of a radiation therapy system in one embodiment;

FIG. 3 is a schematic diagram of an accelerator treatment head according to an embodiment;

FIG. 4 is a schematic view of a field, penumbra region of an embodiment;

FIG. 5 is a block diagram of a particle source model training apparatus of the radiation therapy system in one embodiment;

FIG. 6 is a block diagram of a dose distribution determining apparatus of the radiation therapy system in one embodiment;

FIG. 7 is a diagram illustrating an internal structure of a computer device according to an embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of and not restrictive on the broad application.

The source model training method of the radiation therapy system provided by the embodiment of the application can be applied to the application environment shown in fig. 1. Wherein the radiation therapy system 102 communicates with the server 104 over a network. The data storage system may store data that the server 104 needs to process. The data storage system may be integrated on the server 104 or may be placed on the cloud or other network server. The server obtains measured data of the radiotherapy system under different input energies, including but not limited to a percent depth measurement curve, an off-axis ratio measurement curve and an output factor measurement value, and in addition, the server 104 can determine a percent depth calculation curve and an off-axis ratio calculation curve corresponding to the particle source according to the input energy and a preset source model, and the difference between the percent depth calculation curve and the percent depth measurement curve and the difference between the off-axis ratio calculation curve and the off-axis ratio measurement curve, adjust a correlation parameter determining the distribution of the particle source in the preset source model until the differences are within a preset error range, and then further correct the adjusted preset source model based on a correction factor to obtain the particle source model for subsequent dose distribution determination. When the subsequent radiotherapy system 102 works, energy to be input can be sent to the server 104, the server 104 can determine a dose distribution calculation curve and an output factor calculation value of the radiotherapy system according to the energy to be input and the particle source model, and a worker can know parameters such as energy, position, speed and direction of emergent particles in advance to provide data basis for accurate radiotherapy. The radiation therapy system 102 may include, among other things, an accelerator treatment head. The server 104 may be implemented as a stand-alone server or a server cluster comprised of multiple servers.

In one embodiment, as shown in fig. 2, a method for training a particle source model of a radiation therapy system is provided, which is illustrated by applying the method to the server in fig. 1, and includes the following steps:

s202, acquiring a percentage depth calculation curve and an off-axis ratio calculation curve corresponding to a particle source based on input energy and a preset source model; the particle source is used to simulate the energy variation of the input energy in the radiation therapy system. The percentage depth curve, also called PDD (percent depth dose) curve, refers to the percentage of the dose at any depth to the dose at a reference depth along the central axis of the ray beam, and is a physical quantity describing the relative dose distribution at different depths of the central axis of the ray. The off-axis ratio curve, also called Profile, is used for representing the relationship between the position deviating from the central axis and the dose, is used for describing the energy deposition characteristics in the longitudinal direction of the ray bundle, and can reflect the flatness and symmetry of the dose distribution. PDD reflects longitudinal dose distribution characteristics, and Profile reflects transverse dose distribution characteristics. And the percent depth calculation curve and the off-axis ratio calculation curve are input by taking the input energy as a preset source model, and the obtained theoretical results of the percent depth curve and the off-axis ratio curve under the input energy are output of the preset source model. If the output and the actually measured percent depth measurement curve and the off-axis ratio measurement curve meet the constraint condition of the preset error range, the preset source model is in accordance with the expectation, and the output and the actually measured percent depth measurement curve and the actually measured off-axis ratio measurement curve can be used as a model for determining the dose distribution and can be used for determining the dose distribution of input energy in the using process of the radiation therapy system. If not, the model needs to be trained to obtain a particle source model of which the difference between the calculation result and the actual measurement result conforms to the preset error range constraint.

And S204, acquiring a percentage depth measurement curve, an off-axis ratio measurement curve and an output factor measurement value of the radiotherapy system under the action of input energy. A three-dimensional waterbox system may be employed to measure the central axis percent depth measurement profile of the radiation therapy system under the influence of input energy. The detector can be brought to a certain depth in a three-dimensional water tank and then moved from one side of the tank to the other to make a dose measurement, and the measured point dose is divided by the central axis dose to obtain an off-axis ratio measurement curve for this depth. The measurement implementations are not exhaustive here. The output factor, also called as a field output factor, is a ratio of an output dose rate of a field in a phantom to an output dose rate of a reference field in the phantom. The output factor measurement may be determined from a measurement of the output dose. For example, in one example, the Source Skin Distance (SSD, the Distance from the center of the radiation Source to the center of the irradiation field on the body surface Skin) is 100cm, dose data of fields with different sizes are acquired at 10cm under water, the reference field is 10cmx10cm, and the output factors of different fields can be determined according to the dose data of different fields and the dose data of the reference field.

And S206, adjusting the correlation parameters determining the distribution of the particle sources in the preset source model according to the difference between the percent depth calculation curve and the percent depth measurement curve and the difference between the off-axis ratio calculation curve and the off-axis ratio measurement curve until the differences are within a preset error range. The difference between the upper limit and the lower limit of the preset error range may be set based on the requirement of the precision required by the user, and in one embodiment, the upper limit and the lower limit of the preset error range may be equal, and in this case, it should be understood that the end condition of the training process is the difference between the percent depth calculation curve and the percent depth measurement curve, and the difference between the off-axis ratio calculation curve and the off-axis ratio measurement curve is equal to the upper limit (or the lower limit) of the preset error range. In one embodiment, the upper limit value and the lower limit value of the preset error range may be both 0, and in this case, the calculation results and the measurement results of the percent depth curve and the off-axis ratio curve are consistent, which is an ideal state. Of course, the user can set the predetermined error range according to the requirement for the accuracy of the dose distribution determination. It should be noted that, the difference between the percent depth calculation curve and the percent depth measurement curve, and the difference between the off-axis ratio calculation curve and the off-axis ratio measurement curve are within a preset error range, and may be that the difference between the percent depth calculation curve and the percent depth measurement curve is within a first preset error range, and the difference between the off-axis ratio calculation curve and the off-axis ratio measurement curve is within a second preset error range, and the first preset error range and the second preset error range may be the same or different.

And S208, determining a correction factor of the output factor based on the measured value of the output factor and the adjusted preset source model. Considering that the calculation result of the correction factor is influenced when the correlation parameters of the percent depth curve and the off-axis ratio curve in the model are determined, the correlation parameters of the curve are determined, then the correction factor is calculated, and the correction factor of the output factor is determined by utilizing the measured value of the output factor and the adjusted preset source model and is used for guiding the further correction of the source model.

In one embodiment, the step S208 of determining the correction factor of the output factor based on the measured value of the output factor and the adjusted preset source model includes:

acquiring an output factor calculation value of the radiotherapy system based on the particle source and the adjusted preset source model; at this time, a calculated value of the output factor based on the adjusted preset source model may be obtained.

A correction factor for the output factor is determined based on the output factor measurement and the output factor calculation. In one embodiment, the correction factor = output factor measurement/output factor calculation for a given location. For example, the given position is a position having a depth of 5 cm.

And S210, correcting the adjusted preset source model based on the correction factor to obtain a particle source model. In steps S202 to S208, the shapes of the calculation curve and the measurement curve determined based on the adjusted preset source model may be relatively consistent. The adjusted predetermined model is further modified by a correction factor such that the absolute magnitude of the measured value and the calculated value determined based on the corrected particle source model are consistent.

Specifically, the energy distribution condition inside the radiotherapy system is represented by only defining the particle source, and the correlation parameters determining the particle source distribution condition in the preset source model are quickly adjusted by utilizing the difference between the calculated values and the actual measured values of the percent depth calculation curve and the off-axis ratio calculation curve, so that the modeling difficulty is reduced, and the modeling speed is increased. And the calculation result of the correction factor is influenced when the correlation parameters of the percent depth curve and the off-axis ratio curve in the model are determined, so that the preset source model is adjusted based on the difference between the calculated value and the measured value of the percent depth calculation curve and the off-axis ratio calculation curve, and finally the adjusted preset source model is further adjusted based on the correction factor of the output factor, so that the modeling speed is increased, and the accuracy of the source model of the radiotherapy system is improved.

In one embodiment, the particle source comprises a primary sub-source, a secondary sub-source, and a pollutant source. By dividing the particle source into a virtual primary sub source, a virtual secondary sub source and a virtual pollutant sub source, the particle source distribution condition of most radiotherapy systems can be simulated, the model can be simplified, and the modeling speed and efficiency can be improved. For example, when the radiotherapy system works in an electronic irradiation mode, compared with a mode of adopting four to five virtual sources or even more virtual sources in the traditional technology, the particle source model training method provided by the application can greatly reduce the number of sub sources without reducing the accuracy of an algorithm, reduce the modeling difficulty and reduce the water tank curve required by modeling. Meanwhile, scattering kernel data calculated by aiming at light limiting cylinders of different models do not need to be read in advance like an electronic ray algorithm in other radiotherapy systems, so that the execution speed of modeling is further improved, the storage space is saved, the limitation of the models of accelerators and light limiting cylinders of different manufacturers is avoided, and the application range is expanded.

It should be noted that the particle source model training method provided in the embodiments of the present application is applicable to all radiation therapy systems having a photon source and/or an electron source emission function, for example, an accelerator therapy head (as shown in fig. 3). The three sub-sources (primary sub-source, secondary sub-source and pollutant sub-source) refers to that all accelerator treatment heads with the emission function of the electron source and/or the photon source are approximately considered to only comprise three parts, namely the primary sub-source, the secondary sub-source and the pollutant sub-source in the source model. For a treatment head emitting electrons, the three electron sources include a primary electron source, a secondary electron source, and a source of contaminating photons; for a treatment head emitting photons, the three sub-sources include a primary photon source, a secondary photon source, and a source of contaminated electrons.

The percentage depth curve corresponding to one input energy comprises a plurality of monoenergetic percentage depth dose curves corresponding to the monoenergetics, and the adjustment of the weight of the percentage depth curve in the preset source model refers to the adjustment of the weight of each monoenergetic curve, and the adjustment of the weight can be realized through an ant colony algorithm, a simulated annealing algorithm and other algorithms. For example, the preset source model is a neural network model, and the network weight of each neuron is updated by using a simulated annealing algorithm for the network, so as to determine the weight of the depth-percentage curve.

The first predetermined error range may be configured in advance, depending on the requirements for accuracy of dose distribution determination. The difference between the percent depth calculation curve and the percent depth measurement curve is within a first preset error range, which can be understood as that the corresponding difference on the curve falls within the first preset error range, and at this time, the shapes of the percent depth calculation curve and the percent depth measurement curve are considered to be consistent.

and for the condition that the radiotherapy system works in the photon irradiation mode, based on the difference between the built-up area of the percentage depth calculation curve and the built-up area of the percentage depth measurement curve, adjusting the weight of the polluted electron source and the size of the polluted electron source in the preset source model, and enabling the difference between the built-up area of the percentage depth calculation curve and the built-up area of the percentage depth measurement curve obtained based on the adjusted preset source model to be within the error range of a first preset area.

The established region is a region from zero depth to the maximum dose depth, and the zero depth can be understood as the body surface position. The built-up area is associated with a secondary electron source, and when the X-rays strike the body surface, the X-rays ionize the secondary electron source, which carries energy that continues to rush forward until the energy is consumed, thereby reaching a depth below the body surface. Therefore, the built-up area can characterize the deposition of the energy of the beam (particle source). The higher the energy of the X-ray is, the lower the dosage on the body surface is, the deeper the depth of the maximum dosage point is, so that the weight of the pollution sub-source and the size of the pollution sub-source in the model are adjusted through the difference between the calculation result and the measurement result of the built-up area, so that the adjusted preset source model can accurately predict the built-up area and provide a data basis for determining the dosage distribution. Similar to the explanation of the first preset error range in the above embodiment, the first preset area error range may also be configured in advance, and the user may set the first preset area error range according to the required dose determination accuracy. The difference of the built-up areas within the first preset area error range can be understood as the shape of the percent depth calculation curve and the percent depth measurement curve in the built-up areas are consistent.

The contaminating photon tail is a long low-dose bremsstrake (contamination zone) of bremsstrahlung from PDD after high-dose plateau and dose-drop. The second predetermined zone error range may also be configured in advance as desired.

It should be noted that, in the case that the radiation therapy system supports only the photon irradiation mode, the pollution electron source includes the pollution electron source, and in the model training process, the step of adjusting the weight and the size of the pollution electron source based on the constraint condition that the difference between the calculation result and the measurement result of the PDD built-up area is within the error range of the first preset area may be performed only.

In the case where the radiation therapy system supports only the electron irradiation mode, the contamination photon source comprises a contamination photon source, and in this case, the step of adjusting the weight and size of the contamination photon source based on the constraint that the difference between the calculation result and the measurement result of the PDD contamination photon tail is within the second preset region error range may be performed only.

In the case that the radiation therapy system supports both the photon irradiation mode and the electron irradiation mode, the contamination electron source includes a contamination photon source and a contamination electron source, and in this case, the training process of the particle source model includes a step of adjusting the weight and the size of the contamination electron source, and also includes a step of adjusting the weight and the size of the contamination photon source.

The penumbra area can be understood as shown in fig. 4, if the difference between the calculation result and the measurement result of the penumbra area is too large, it indicates that the current preset source model cannot be accurately used for determining the off-axis ratio measurement curve, and at this time, the difference between the calculation result and the measurement result of the penumbra area is constrained within the preset dose error range by adjusting the size of the primary sub source in the source model.

If the difference between the calculation result and the measurement result of the off-axis ratio curve is not within the second preset error range, the current preset source model cannot accurately reflect the distribution condition of the particles, and based on the difference, model parameters for determining probability densities at different off-axes in the preset source model, such as coefficients of a probability density distribution function, are adjusted according to the difference. Until the difference between the off-axis ratio calculation curve and the measurement curve determined based on the adjusted preset source model is constrained within a second preset error range.

The radiation therapy system works in a photon or electron irradiation mode, and the particle source model provided by the application comprises two sampling planes:

for the photon irradiation mode, the positions of the first sampling planes defining the primary photon source, the secondary photon source and the contamination electron source are all located at the lower surface of the beam limiting device (multi-page grating or secondary collimator) as shown in fig. 3. The second sampling plane defining the primary photon source is located in the target as shown in figure 3 and the second sampling planes of the secondary photon source and the source of contaminant electrons are located in the homogenizer.

For the electron irradiation mode, a first sampling plane defining the primary electron source, the secondary electron source and the polluted photon source is positioned on the lower surface of the electron light limiting barrel, and if the electron light limiting barrel is not arranged, the first sampling plane is positioned on the lower surface of the beam limiting device. A second sampling plane defining the primary electron source is located on the primary scattering foil and the secondary electron source and a second sampling plane of the polluting electron source are located on the secondary scattering foil.

Wherein the first sampling plane has considered a different configuration of the accelerator treatment head, etc. radiation therapy system. Taking the accelerator treatment head as an example, the structural difference of the accelerator treatment head on the market at present is mainly the position relationship between the beam limiting device, i.e. the secondary collimator and the multi-page grating as shown in fig. 3. At this time, the first sampling plane is located on the lower surface of the multi-page raster. And for another treatment head with a multipage grating above the secondary collimator, the first sampling plane is the lower surface position of the secondary collimator. In summary, the first sampling plane can be defined as the lower surface of the beam limiting means. The first sampling plane is selected according to the actual physical position of the accelerator treatment head structure.

If two planes are arbitrarily selected as the sampling planes, which may cause the result of model calculation to be inconsistent with the actual measurement result, the positions of the two sampling planes need to be adjusted as separate parameters, thereby increasing the complexity of modeling. According to the particle source model training method provided by the embodiment of the application, the first sampling plane is defined as the sampling plane capable of reflecting the distribution condition of the radioactive rays projected by the radiotherapy system, for example, the lower surface of the beam limiting device of the accelerator treatment head can directly determine the projection direction, speed and other characteristics of the emergent particles, only the parameters of the probability density distribution function on the first sampling plane can be adjusted, unnecessary parameter adjustment is reduced, and the modeling difficulty is reduced.

In one embodiment, adjusting parameters of the piecewise linear distribution function at the first sampling plane in the predetermined source model may include:

adjusting at least one of a slope parameter or an intercept parameter in the following expression:

wherein y (x) represents the probability density at an off-axis distance x on the first sampling plane, x represents the off-axis distance, a _n Denotes the distance from the axis at x _n-1 To x _n Slope parameter of the linear distribution of probability density in between, b _n At an off-axis distance of x _n-1 To x _n The intercept parameter of the linear distribution of probability density in between. And adjusting the probability density values of different off-axis positions in the model to enable the off-axis ratio calculation curve and the off-axis ratio measurement curve to be within a second preset error range.

The positions (i.e. distribution) of the particles on the first sampling plane and the second sampling plane are obtained by random sampling on the first sampling plane and the second sampling plane respectively, then the moving direction of the particles is determined according to the connection line of the positions of the single particles on the two planes, and the energy of the particles is obtained by random sampling of the energy spectrum.

The probability density distribution of photons and electrons on the first sampling plane adopts a multi-section linear probability density distribution form, so that the modeling difficulty can be reduced, and the modeling accuracy is improved. In addition, the first sampling plane adopts a multi-section linear probability density distribution form, the number of probability density sections can be given at will, the characteristics of accelerator off-axis ratio curves (profiles) of different manufacturers can be adapted, and the application range is expanded.

and adjusting the size of a secondary sub-source in the preset source model based on the difference between the off-axis ratio calculation curve in the field of radiation and the off-axis ratio measurement curve in the field of radiation, so that the difference between the off-axis ratio calculation curve in the field of radiation and the off-axis ratio measurement curve in the field of radiation obtained based on the adjusted preset source model is in a third preset error range.

After the probability density distribution is adjusted, the difference between the off-axis ratio calculation curve in the field of projection and the off-axis ratio measurement curve in the field of projection is adjusted by further adjusting the size of a secondary sub-source in the preset source model, so that the difference is within a third preset error range, and the adjustment of the curve correlation parameters in the model is completed.

In order to better explain the implementation of the method for training the particle source model of the radiation therapy system provided in the embodiments of the present application, a process for determining the particle source model of the linear accelerator in the radiation therapy system is taken as an example. When the energy level is selected to be 6MV photon irradiation mode:

(1) The size of the radiation field can be set to be 10cm × 10cm, the percentage depth calculation curves of different single-energy photons are calculated based on a preset source model, and the weight of the percentage depth calculation curves of the single-energy photons is adjusted to enable the percentage depth calculation curves to be consistent with the percentage depth measurement curves within a given difference range (a first preset error range), so that the energy spectrums of the primary photon source and the secondary photon source are obtained.

Then, the weight and the source size of the pollution electron source are adjusted so that the built-up area of the depth-percentage calculation curve and the built-up area of the depth-percentage measurement curve are consistent within a given range (a first preset area error range) to determine the energy spectrum of the pollution electron source.

(2) Adjusting parameters such as the size of a primary photon source and the position of a first sampling plane (as shown in fig. 3) and the like, comparing penumbra regions of an off-axis ratio calculation curve and an off-axis ratio measurement curve, when the two have a difference, adjusting the radius of the primary photon source, wherein the radius is larger, the penumbra is larger, and vice versa, the radius is smaller, the penumbra is smaller, and after adjusting the radius of the primary photon source in a preset source model, recalculating the three-dimensional dose based on the adjusted preset source model until the difference between the calculated value and the measured value of the three-dimensional dose in the penumbra region is within a preset dose error range.

(3) And adjusting the probability density value of the off-axis ratio curve of the large field (for example, adjusting the off-axis ratio curve to 30cm by 30cm) so that the off-axis ratio calculation curve is consistent with the measured value of the off-axis ratio measurement curve in a given error threshold range (a second preset error range) in the field.

(4) The size of the secondary sub-source is adjusted so that the off-axis ratio calculation curve can be consistent with the off-axis ratio measurement curve within a given error threshold range (second preset error range) outside the field (which can be understood in conjunction with fig. 4). The secondary source size refers to the secondary source radius, which is a parameter in the particle source model related to the secondary source size. For understanding in the field, taking a field of 10cm × 10cm as an example, the size of the isocenter plane (usually SSD =100 cm) is defined as X =10cm, y =10cm, and the portion beyond 10cm is defined as the field. Instead of isocentric planes, e.g., SSD =110cm, the size of the 10cm × 10cm field should be 10cm × 110cm/100cm, i.e., 11cm, and the portion beyond 11cm should be the field.

(5) And finally, calculating a correction factor of the output factor according to the output factors measured by different fields. And (4) further correcting the preset source model adjusted in the steps (1) to (4) based on the correction factor to obtain a particle source model.

The particle source model of the electron source is established by similar steps to photons, for example, the energy level is selected to be 12MeV electron irradiation mode:

(1) The size of the light limiting cylinder is selected to be 10cm x10cm, PDDs of different single-energy electrons are calculated based on a preset source model, and the weight of the PDDs of the single-energy electrons is adjusted to enable a depth-percentage calculation curve and a depth-percentage measurement curve to be consistent in a given difference range (a first preset error range) so as to obtain energy spectrums of a primary electron source and a secondary electron source; and adjusting the weight and the source size of the polluted photon source to ensure that the polluted photon tails of the percentage depth calculation curve and the percentage depth measurement curve are consistent within a given range (a second preset region error range), so as to ensure that the adjusted preset source model can be used for accurately determining the energy spectrum of the polluted photon source.

(2) And adjusting parameters such as the size and the position of the primary electron source, and comparing the calculated and measured Profile penumbra area, so that the error between the Profile calculated based on the adjusted preset source model and the Profile penumbra area measured by the accelerator is within a preset dose error range.

(3) The probability density values of the off-axis ratio curves of a large field (e.g., a 25cm x 25cm size light limiting cylinder) in the preset source model are adjusted so that the calculated Profile is consistent with the measured Profile within a given threshold range (preset dose error range) within the field.

(4) And adjusting the size of a secondary source (secondary source radius) in the preset source model so that the calculated electronic Profile is consistent with the measured Profile in a given error threshold range (preset dose error range) outside the field.

(5) And finally, calculating the correction factor of the output factor according to the output factor measured by the light limiting cylinders with different sizes. And (5) further correcting the preset source model adjusted in the steps (1) - (4) based on the correction factor to obtain a particle source model.

Therefore, the particle source model training method provided by the embodiment of the application is suitable for a photon source and an electron source, and simulates a radiation therapy system (an accelerator therapy head) under photon and electron irradiation modes by using the same particle source model. By using the particle source training method provided by the application, the modeling difficulty of the photon-electron source model can be reduced, the modeling speed is increased, the algorithm accuracy can be improved, and the application range of the algorithm is expanded.

It should be noted that the sequence between steps (1) - (4) may be changed, and is not limited to the sequence given herein, but step (5) is necessarily after steps (1) - (4), for the reasons described in the above embodiments, the calculation result of the correction factor may be affected during the adjustment process of the associated parameters of PDD and Profile in the model.

The embodiment of the application also provides a dose distribution determining method of a radiation therapy system, which comprises the following steps:

acquiring energy to be input of a radiotherapy system;

During the use of the radiotherapy system, the percentage depth calculation curve of energy to be input, the off-axis ratio calculation curve and the output factor calculation value can be determined based on the trained particle source model so as to know whether the distribution condition of the particle source is in accordance with the expectation, and if not, the dose distribution parameters of the percentage depth calculation curve, the off-axis ratio calculation curve and the output factor calculation value can be in accordance with the expectation by increasing or reducing the energy to be input.

It should be understood that, although the steps in the flowcharts related to the embodiments as described above are sequentially displayed as indicated by arrows, the steps are not necessarily performed sequentially as indicated by the arrows. The steps are not limited to being performed in the exact order illustrated and, unless explicitly stated herein, may be performed in other orders. Moreover, at least a part of the steps in the flowcharts related to the embodiments described above may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the execution order of the steps or stages is not necessarily sequential, but may be performed alternately or alternately with other steps or at least a part of the steps or stages in other steps.

Based on the same inventive concept, the embodiment of the present application further provides a particle source model training apparatus for a radiation therapy system, which is used for implementing the above-mentioned particle source model training method for the radiation therapy system. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme described in the above method, so specific limitations in one or more embodiments of the particle source model training device for a radiation therapy system provided below can be referred to the above limitations on the particle source model training method for a radiation therapy system, and are not described herein again.

In one embodiment, as shown in fig. 5, there is provided a particle source model training apparatus of a radiation therapy system, the apparatus comprising: a distribution curve calculation module 502, a measurement parameter acquisition module 504, a first adjustment module 506, a correction factor determination module 508, and a particle source model determination module 510. Wherein:

a distribution curve calculation module 502, configured to obtain a percentage depth calculation curve and an off-axis ratio calculation curve corresponding to a particle source based on input energy and a preset source model;

a measurement parameter obtaining module 504, configured to obtain a percentage depth measurement curve, an off-axis ratio measurement curve, and an output factor measurement value of the radiotherapy system under the action of input energy;

a first adjusting module 506, configured to adjust a correlation parameter determining distribution of the particle source in the preset source model according to a difference between the percent depth calculation curve and the percent depth measurement curve and a difference between the off-axis ratio calculation curve and the off-axis ratio measurement curve until the differences are within a preset error range;

a correction factor determining module 508, configured to determine a correction factor of the output factor based on the output factor measurement value and the adjusted preset source model;

and a particle source model determining module 510, configured to correct the adjusted preset source model based on the correction factor to obtain a particle source model.

In one embodiment, the particle source includes a primary sub-source, a secondary sub-source, and a pollutant sub-source.

In one embodiment, the first adjustment module 506 includes:

and the depth percentile dose weight adjusting unit is used for adjusting the weight of the depth percentile curve in the preset source model based on the difference between the depth percentile calculation curve and the depth percentile measurement curve so as to enable the difference between the depth percentile calculation curve and the depth percentile measurement curve obtained based on the adjusted preset source model to be within a first preset error range.

In one embodiment, the contaminant source comprises a contaminated photon source and/or a contaminated electron source, and the first conditioning module 506 comprises:

the polluted electron source adjusting unit is used for adjusting the weight of a polluted electron source and the size of the polluted electron source in a preset source model based on the difference between the built-up area of the percent depth calculation curve and the built-up area of the percent depth measurement curve under the condition that the radiotherapy system works in a photon irradiation mode, so that the difference between the built-up area of the percent depth calculation curve and the built-up area of the percent depth measurement curve obtained based on the adjusted preset source model is in a first preset area error range; and/or the presence of a gas in the gas,

and the polluted photon source adjusting unit is used for adjusting the weight of a polluted photon source and the size of a polluted photon source in the preset source model based on the difference between the polluted photon tail of the percentage depth calculation curve and the polluted photon tail of the percentage depth measurement curve under the condition that the radiotherapy system works in an electronic irradiation mode, so that the difference between the polluted photon tail of the percentage depth calculation curve and the polluted photon tail of the percentage depth measurement curve obtained based on the adjusted preset source model is in a second preset region error range.

In one embodiment, the first adjustment module 506 includes:

and the primary sub-source adjusting unit is used for adjusting the size of the primary sub-source in the preset source model based on the difference between the penumbra region of the off-axis ratio calculation curve and the penumbra region of the off-axis ratio measurement curve, so that the error between the three-dimensional dose information of the penumbra region of the off-axis ratio calculation curve and the three-dimensional dose information of the penumbra region of the off-axis ratio measurement curve obtained based on the adjusted preset source model is within a preset dose error range.

In one embodiment, the first adjustment module 506 includes:

and the probability density adjusting unit is used for adjusting model parameters used for determining probability densities at different off-axes in the preset source model based on the difference between the off-axis ratio calculation curve in the field and the off-axis ratio measurement curve in the field, so that the difference between the off-axis ratio calculation curve in the field and the off-axis ratio measurement curve in the field obtained based on the adjusted preset source model is in a second preset error range.

In one embodiment, the probability density adjusting unit includes:

the correlation parameter adjusting unit is used for adjusting the correlation parameters of the probability density distribution function on the first sampling plane in the preset source model based on the difference between the off-axis ratio calculation curve in the field and the off-axis ratio measurement curve in the field; the first sampling plane is a sampling plane that reflects the distribution of radiation projected by the radiation therapy system in the selected irradiation mode.

In one embodiment, the probability density distribution function is a multi-segment linear distribution function, and the correlation parameter adjusting unit includes:

and the linear parameter adjusting unit is used for adjusting parameters of the multi-segment linear distribution function on the first sampling plane in the preset source model.

In one embodiment, the first adjustment module 506 includes:

and the secondary sub-source adjusting unit is used for adjusting the size of the secondary sub-source in the preset source model based on the difference between the off-axis ratio calculation curve in the field of radiation and the off-axis ratio measurement curve in the field of radiation, so that the difference between the off-axis ratio calculation curve in the field of radiation and the off-axis ratio measurement curve in the field of radiation obtained based on the adjusted preset source model is in a third preset error range.

In one embodiment, the linear parameter adjustment unit includes:

a slope intercept adjustment unit for adjusting at least one of a slope parameter or an intercept parameter in the following expression:

wherein y (x) represents the probability density at an off-axis distance x on the first sampling plane, x represents the off-axis distance, a _n Denotes the distance from the axis at x _n-1 To x _n Linear density of probability betweenSlope parameter of the distribution, b _n At an off-axis distance of x _n-1 To x _n The intercept parameter of the linear distribution of probability density in between. And adjusting the probability density values of different off-axis positions in the model to enable the off-axis ratio calculation curve and the off-axis ratio measurement curve to be within a second preset error range.

Based on the same inventive concept, the embodiment of the present application further provides a dose distribution determining apparatus of a radiation therapy system for implementing the above-mentioned dose distribution determining method of the radiation therapy system. The implementation scheme for solving the problem provided by the apparatus is similar to the implementation scheme described in the above method, so the specific limitations in the apparatus embodiments of one or more radiation therapy system dose distribution determination methods provided below can be referred to the limitations on the radiation therapy system dose distribution determination method in the above, and are not described herein again.

In one embodiment, as shown in fig. 6, there is provided a dose distribution determining apparatus of a radiation therapy system, the apparatus including: a pending energy acquisition module 602 and a dose profile determination module 604. Wherein:

an energy to be input acquisition module 602, configured to acquire energy to be input of the radiotherapy system;

a dose distribution determination module 604, configured to determine a dose distribution calculation curve and an output factor calculation value of the radiation therapy system based on the energy to be input and a particle source model of the radiation therapy system;

The various modules in the above-described apparatus may be implemented in whole or in part by software, hardware, and combinations thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.

In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 7. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operating system and the computer program to run on the non-volatile storage medium. The database of the computer equipment is used for storing data such as the trained particle source model. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of particle source model training and a method of dose distribution determination for a radiation therapy system.

Those skilled in the art will appreciate that the architecture shown in fig. 7 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.

In an embodiment, a computer device is provided, comprising a memory having a computer program stored therein and a processor that, when executing the computer program, performs the steps of any of the method embodiments described above.

In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which, when being executed by a processor, carries out the steps of any of the method embodiments.

In an embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, performs the steps of any of the method embodiments described above.

It should be noted that, the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, presented data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above may be implemented by hardware instructions of a computer program, which may be stored in a non-volatile computer-readable storage medium, and when executed, may include the processes of the embodiments of the methods described above. Any reference to memory, databases, or other media used in the embodiments provided herein can include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high-density embedded nonvolatile Memory, resistive Random Access Memory (ReRAM), magnetic Random Access Memory (MRAM), ferroelectric Random Access Memory (FRAM), phase Change Memory (PCM), graphene Memory, and the like. Volatile Memory can include Random Access Memory (RAM), external cache Memory, and the like. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others. The databases referred to in various embodiments provided herein may include at least one of relational and non-relational databases. The non-relational database may include, but is not limited to, a block chain based distributed database, and the like. The processors referred to in the various embodiments provided herein may be, without limitation, general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, or the like.

All possible combinations of the technical features in the above embodiments may not be described for the sake of brevity, but should be considered as being within the scope of the present disclosure as long as there is no contradiction between the combinations of the technical features.

The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, and these are all within the scope of protection of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.

Claims

1. A method of particle source model training for a radiation therapy system, the method comprising:

acquiring a percentage depth calculation curve and an off-axis ratio calculation curve corresponding to the particle source based on input energy and a preset source model;

acquiring a percentage depth measurement curve, an off-axis ratio measurement curve and an output factor measurement value of the radiotherapy system under the action of the input energy;

and correcting the adjusted preset source model based on the correction factor to obtain the particle source model.

2. A method according to claim 1, wherein the particle sources comprise a primary sub-source, a secondary sub-source and a pollutant sub-source.

3. The method of claim 1, wherein the adjusting the associated parameters determining the distribution of the particle source in the preset source model according to the difference between the percent depth calculation curve and the percent depth measurement curve and the difference between the off-axis ratio calculation curve and the off-axis ratio measurement curve comprises:

4. The method of claim 2, wherein the contaminant source comprises a contaminant photon source and/or a contaminant electron source, and wherein adjusting the correlation parameter determining the distribution of the particle source in the preset source model based on the difference between the depth percentile calculation curve and the depth percentile measurement curve and the difference between the off-axis ratio calculation curve and the off-axis ratio measurement curve comprises:

for the condition that the radiotherapy system works in a photon irradiation mode, based on the difference between the built-up area of the percentage depth calculation curve and the built-up area of the percentage depth measurement curve, adjusting the weight of the polluted electron source and the size of the polluted electron source in the preset source model, and enabling the difference between the built-up area of the percentage depth calculation curve and the built-up area of the percentage depth measurement curve obtained based on the adjusted preset source model to be within a first preset area error range; and/or the presence of a gas in the gas,

and for the condition that the radiotherapy system works in an electronic irradiation mode, based on the difference between the polluted photon tail of the percentage depth calculation curve and the polluted photon tail of the percentage depth measurement curve, adjusting the weight of the polluted photon source and the size of the polluted photon source in the preset source model, so that the difference between the polluted photon tail of the percentage depth calculation curve and the polluted photon tail of the percentage depth measurement curve obtained based on the adjusted preset source model is within a second preset region error range.

5. The method of claim 2, wherein the adjusting the correlation parameter determining the distribution of the particle source in the preset source model according to the difference between the depth percentile calculation curve and the depth percentile measurement curve and the difference between the off-axis ratio calculation curve and the off-axis ratio measurement curve comprises:

and adjusting the size of the primary sub-source in the preset source model based on the difference between the penumbra region of the off-axis ratio calculation curve and the penumbra region of the off-axis ratio measurement curve, so that the error between the three-dimensional dose information of the penumbra region of the off-axis ratio calculation curve and the three-dimensional dose information of the penumbra region of the off-axis ratio measurement curve obtained based on the adjusted preset source model is within a preset dose error range.

6. The method of claim 1, wherein the adjusting the associated parameters determining the distribution of the particle source in the preset source model according to the difference between the percent depth calculation curve and the percent depth measurement curve and the difference between the off-axis ratio calculation curve and the off-axis ratio measurement curve comprises:

and adjusting model parameters used for determining probability densities at different off-axis positions in the preset source model based on the difference between the off-axis ratio calculation curve in the field and the off-axis ratio measurement curve in the field, so that the difference between the off-axis ratio calculation curve in the field and the off-axis ratio measurement curve in the field obtained based on the adjusted preset source model is in a second preset error range.

7. The method of claim 6, wherein adjusting model parameters in the preset source model for determining probability densities at different off-axes based on a difference between the off-axis ratio calculation curve in the field and the off-axis ratio measurement curve in the field comprises:

adjusting the correlation parameter of the probability density distribution function on the first sampling plane in the preset source model based on the difference between the off-axis ratio calculation curve in the field and the off-axis ratio measurement curve in the field; the first sampling plane is a sampling plane capable of reflecting the distribution of the radiation projected by the radiation therapy system under the selected irradiation mode.

8. The method of claim 7, wherein the probability density distribution function is a multi-segment linear distribution function, and wherein the adjusting the parameters of the probability density distribution function at the first sampling plane in the preset source model comprises:

and adjusting parameters of the multi-section linear distribution function on the first sampling plane in the preset source model.

9. The method of claim 2, wherein the adjusting the associated parameters determining the distribution of the particle source in the preset source model according to the difference between the percent depth calculation curve and the percent depth measurement curve and the difference between the off-axis ratio calculation curve and the off-axis ratio measurement curve until the differences are within a preset error range comprises:

and adjusting the size of the secondary sub source in the preset source model based on the difference between the off-axis ratio calculation curve in the shooting field and the off-axis ratio measurement curve in the shooting field, so that the difference between the off-axis ratio calculation curve in the shooting field and the off-axis ratio measurement curve in the shooting field obtained based on the adjusted preset source model is in a third preset error range.

10. A method of dose distribution determination for a radiation therapy system, the method comprising:

acquiring energy to be input of the radiotherapy system;

wherein the particle source model is generated by performing the steps of the particle source model training method of the radiation therapy system of any one of claims 1-9.