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Method, device and system for simulating particle transport and calculating body dosage in radiotherapy

A technology for simulating particles and particles, which is applied in radiation therapy, X-ray/γ-ray/particle irradiation therapy, computer-aided medical procedures, etc. It can solve the problems of high calculation intensity and long time consumption, so as to improve simulation efficiency and speed up simulation speed , to reduce the effect of particle transport

Active Publication Date: 2015-07-01
SHANGHAI UNITED IMAGING HEALTHCARE
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The biggest disadvantage of the Monte Carlo method is that it is computationally intensive and takes a long time

Method used

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  • Method, device and system for simulating particle transport and calculating body dosage in radiotherapy
  • Method, device and system for simulating particle transport and calculating body dosage in radiotherapy
  • Method, device and system for simulating particle transport and calculating body dosage in radiotherapy

Examples

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Effect test

Embodiment 1

[0065] Using the Monte Carlo algorithm to simulate the particle transport process is a method that uses a large number of random samples to achieve accurate calculations. In particular, in order to meet the user's requirements for particle transport uncertainty, it is often necessary to simulate a large number of particles, which is time-consuming. characteristic.

[0066] This embodiment provides a method for simulating particle transport, which is suitable for simulating the energy distribution of particles in a cell. It can be based on the Monte Carlo simulation algorithm, which calculates the uncertainty of the geometric cell and distinguishes the It can reduce the sampling of particles and save a lot of calculation time.

[0067] refer to figure 1 , the method for simulating particle transport provided in this embodiment includes:

[0068] Step S100, estimating the number of incident particles, generating incident particles and inputting them in batches.

[0069] The i...

Embodiment 2

[0106] Based on Embodiment 1, this embodiment provides a method such as figure 2 The shown method for simulating particle transport can balance the uncertainty according to the global uncertainty of the simulation process, and dynamically adjust the number of particle samples according to the distribution of uncertainty. The method specifically includes the following steps:

[0107] Steps S100 to S103 are consistent with Embodiment 1.

[0108] When the next batch of incident particles is input, based on the transport process of the incident particles, the input particles are processed as follows:

[0109] Step S104, if the transport process of the incident particles shows that one of the incident particles in the batch of particles enters the cell with high importance from the cell with low importance, then the incident particle entering the cell with high importance is treated as Splitting with a certain probability, the transport trajectory of the split particles can copy...

Embodiment 3

[0118] Based on Embodiment 1, this embodiment provides a method such as image 3 The method for simulating particle transport shown can be based on the batch transport of particles during the simulation process. After the simulation completes the transport tracks of predetermined batches of particles, the transport tracks based on historical batches of particles are globally uncertain Dynamic noise reduction can be carried out at a high degree, thereby reducing the uncertainty of the simulated particle transport process, which helps to reduce the number of particle samples and improve the simulation efficiency. The method specifically includes the following steps:

[0119] Steps S100 to S103 are consistent with Embodiment 1.

[0120] In the process of simulating particle transportation, if the batches of particle transportation reach the predetermined number, execute:

[0121] Step S106, performing dynamic noise reduction processing on the dose distribution of the incident p...

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Abstract

The invention relates to a method, device and system for simulating particle transport and calculating body dosage in radiotherapy. The method for simulating particle transport includes the steps of recording the transport track of produced input particles; calculating the uncertainty of each lattice cell on the basis of the track of each batch of running particles, and determining that each lattice cell is a lattice cell reaching a standard when the uncertainty of the lattice cell does not exceed a first threshold value; obtaining the standard reaching rate of an area-of-interest, wherein the area-of-interest at least includes one lattice cell, and the standard reaching rate of the area-of-interest is the ratio of the standard reaching lattice cells in the area to all the lattice cells in the area; stopping continuing to input particles and outputting the transport track of the historical input particles if the standard reaching rate of the area-of-interest exceeds a second threshold value. The simulating efficiency of the particle transport process involved in the radiotherapy process can be improved.

Description

technical field [0001] The invention relates to the technical field of radiotherapy, in particular to a method and device for simulating particle transport, a method for calculating human dose in radiotherapy and a radiotherapy system. Background technique [0002] In the field of radiation therapy technology, the calculation methods of human tissue dose distribution can be roughly divided into two categories: semi-empirical analysis method and Monte Carlo method. [0003] Semi-empirical analysis methods include methods based on empirical formulas of off-axis ratio (OAR, Off Axis Ratio), and convolution / superposition methods based on Pencil Beam Kernel and Point Kernel, etc. . But semi-empirical analytical methods have limited accuracy. [0004] The Monte Carlo method has become an irreplaceable method because of its ability to deal with complex problems (complex geometry, complex radioactive source layout, etc.). Monte Carlo methods can accurately model the physical proc...

Claims

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Application Information

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IPC IPC(8): G06F19/00A61N5/10
CPCG16H50/50G16H20/40A61N5/1031A61N2005/1034A61N5/1042
Inventor 李贵唐寅叶绍强刘娟
Owner SHANGHAI UNITED IMAGING HEALTHCARE
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