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Radiotherapy reverse optimization method and device in combination with Monte Carlo, and storage medium

A reverse optimization and Monte Carlo technology, applied in radiation therapy, X-ray/γ-ray/particle irradiation therapy, treatment, etc., can solve the problems of complex calculation process and time-consuming, and achieve high calculation accuracy, taking into account calculation accuracy, Guarantee the effect of computing speed

Active Publication Date: 2019-12-13
BEIJING LINKING MEDICAL TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, its calculation process is complicated, and it is very time-consuming on the CPU computing platform, so it is rarely used clinically at present, and it is still in the stage of extensive research and continuous development.

Method used

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  • Radiotherapy reverse optimization method and device in combination with Monte Carlo, and storage medium
  • Radiotherapy reverse optimization method and device in combination with Monte Carlo, and storage medium
  • Radiotherapy reverse optimization method and device in combination with Monte Carlo, and storage medium

Examples

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Effect test

Embodiment 1

[0039] A hybrid Monte Carlo reverse optimization method for radiotherapy, suitable for execution in computing equipment, such as figure 1 Shown includes the following steps:

[0040] (1) Input patient data and radioactive source parameters, or import radiotherapy plan 210;

[0041] The imported radiotherapy plan includes patient data, radioactive source parameters, and radiation field parameters. In this embodiment, the patient data preferably includes patient images, segmentation positions of target areas and organs at risk, and doctor order data; patient images include CT images and MRI images. One or a combination of; the outlined organs and tissues include normal organs and tissues, the shape and location of the target area; the medical order data (may also be set by the physicist) includes one of the target radiation dose, DVH curve, and the radiation dose constraint value of each organ Type or combination; radioactive source parameters include one or a combination of the type...

Embodiment 2

[0089] A hybrid Monte Carlo reverse optimization method for radiotherapy, suitable for execution in computing equipment, such as image 3 Shown includes the following steps:

[0090] (1) Input patient data and radioactive source parameters, or import radiotherapy plan 310;

[0091] The imported radiotherapy plan includes patient data, radioactive source parameters, and radiation field parameters. Preferably, the patient data includes patient images, segmentation positions of target areas and organs at risk, and doctor order data; patient images include one of CT images, nuclear magnetic images, or Combination; the outlined organs and tissues include normal organs and tissues, the shape and location of the target area; the medical order data includes one or a combination of target radiation dose, DVH curve, and radiation dose constraint values ​​for each organ; radioactive source parameters include the type and shape of the radioactive source One or a combination of, position, energ...

Embodiment 3

[0140] A hybrid Monte Carlo reverse optimization method for radiotherapy, suitable for execution in computing equipment, such as Figure 4 Shown includes the following steps:

[0141] (1) Input patient data and radioactive source parameters, or import radiotherapy plan 610;

[0142] The imported radiotherapy plan includes patient data, radioactive source parameters, and radiation field parameters. Preferably, the patient data includes patient images, segmentation positions of target areas and organs at risk, and doctor order data; patient images include one of CT images, nuclear magnetic images, or Combination; the outlined organs and tissues include normal organs and tissues, the shape and location of the target area; the medical order data includes one or a combination of target radiation dose, DVH curve, and radiation dose constraint values ​​for each organ; radioactive source parameters include the type and shape of the radioactive source One or a combination of, position, ener...

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Abstract

The invention belongs to the technical field of radiotherapy dose calculation and relates to a radiotherapy reverse optimization method and device in combination with Monte Carlo, and a storage medium. The method includes the following steps: inputting patient data and radioactive source parameters, or importing a historical radiotherapy plan, wherein the imported historical radiotherapy plan includes the patient data, the radioactive source parameters, and radiation field parameters; determining, by using an analytical algorithm, the added position of the Monte Carlo algorithm, continuing tooptimize the Monte Carlo two-dimensional flux grid weights, and stopping the calculation until the second accuracy is satisfied. The method determines the added position of the Monte Carlo dose calculation by setting the accuracy threshold to be achieved by analytical calculation, so as to avoid the oscillation of a dose calculation result caused by the early added Monte Carlo dose calculation dueto a large error of an analytical algorithm calculation result and avoid meaninglessness of the addition of the Monte Carlo.

Description

Technical field [0001] The invention belongs to the technical field of radiotherapy dose calculation, and relates to a radiotherapy reverse optimization method, equipment and storage medium. Background technique [0002] The fundamental purpose of radiotherapy is to strive to increase the gain ratio of radiotherapy, that is, to maximize the dose of radiation in the target area to kill the tumor, so that the normal tissues or organs around the lesion are less exposed to or protected from radiation. To achieve this goal, the dose distribution of the target area must be accurately calculated before radiotherapy. [0003] In the prior art, the commonly used dose calculation methods mainly include analytical algorithms and Monte Carlo (Monte Carlo) algorithms. The analytical algorithms include pencil beam model (PBM), convolution algorithms, etc. The PBM dose calculation method can be used The dose calculation of the non-uniform phantom and the fast calculation speed is currently the m...

Claims

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Application Information

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IPC IPC(8): G16H20/40A61N5/10
CPCG16H20/40A61N5/103A61N5/1031A61N5/1048A61N2005/1034
Inventor 李贵刘娟
Owner BEIJING LINKING MEDICAL TECH CO LTD
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