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Radiotherapy dose prediction method and device

A dose prediction and dose technology, applied in radiation therapy, X-ray/γ-ray/particle irradiation therapy, treatment, etc., can solve the problems of difficult dose calculation and optimization, long time, etc.

Active Publication Date: 2021-11-05
BEIHANG UNIV
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Problems solved by technology

However, Monte Carlo simulation takes a long time and is difficult to be directly applied in clinical practice for dose calculation and optimization
Therefore, the current dose calculation method is difficult to achieve high precision and high efficiency at the same time

Method used

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  • Radiotherapy dose prediction method and device
  • Radiotherapy dose prediction method and device
  • Radiotherapy dose prediction method and device

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Effect test

no. 1 example 1

[0023] figure 1 It is a schematic flowchart of a radiotherapy dose prediction method according to the first embodiment of the present invention, as shown in figure 1 As shown, the method includes the following three steps.

[0024] Step S101: Preprocessing the training data. According to the patient's medical image, the patient phantom is established; the dose distribution H of radioactive particles in the patient phantom is calculated using the first calculation method of radiotherapy dose; the dose distribution L1 in the uniform water phantom is calculated using the TG-43 method, and the tissue difference is used The qualitative correction method corrects the dose distribution L1 to obtain the dose distribution L of radioactive particles in the patient phantom; the position of the radioactive particles is modified several times, and the dose distributions H and L are recalculated each time the position is modified.

[0025] Exemplarily, the patient phantom may be three-dim...

no. 1 example

[0032] figure 2 It is a schematic diagram of dose distribution of a radiotherapy dose prediction method according to the first embodiment of the present invention. Such as figure 2 as shown, figure 2 (a) is a schematic diagram of the dose distribution of radioactive particles in the water model calculated by the TG-43 method; figure 2 (b) is figure 2 (a) Schematic diagram of dose distribution after dose distribution correction. Since the TG-43 method directly obtains the radioactive particles in the uniform water model, therefore figure 2 The dose distribution 1 in (a) is a uniform circle, and the dose distribution after heterogeneity correction is as follows figure 2 The dose distribution in (b) is shown in 2.

[0033] In an optional embodiment, the first calculation method of the radiotherapy dose is a Monte Carlo simulation method. Monte Carlo simulation calculates the dose distribution based on the computer simulation of the physical process of the particles ...

Embodiment 2

[0041] The embodiment of the present invention provides a radiotherapy dose prediction device, which is mainly used to implement the radiotherapy dose prediction method provided in the above-mentioned content of the embodiment of the present invention. The radiotherapy dose prediction device provided by the embodiment of the present invention will be described in detail below.

[0042] image 3 It is a structural schematic diagram of a radiotherapy dose prediction device according to the second embodiment of the present invention. Such as image 3 As shown, the radiotherapy dose prediction device 200 includes the following modules:

[0043] Preprocessing module 201, which is used to establish a patient phantom according to the patient's medical image; calculate the dose distribution H of radioactive particles in the patient phantom by using the first calculation method of radiotherapy dose; use the TG-43 method to calculate the dose distribution H in the uniform water phantom...

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Abstract

The invention discloses a radiotherapy dose prediction method, which comprises the following steps of: preprocessing: establishing a patient model body according to the medical image of a patient; calculating the dose distribution H of radioactive particles in the patient model body by using a first calculation method of a radiotherapy dose; using a TG-43 method and a tissue heterogeneity correction method to obtain the dose distribution L of the radioactive particles in the patient model body; carrying out model training: taking multiple times of dose distribution L and the medical image of the patient as input, taking multiple times of dose distribution H as output, and sending into a deep learning neural network for training to obtain a radiotherapy dose prediction network; carrying out dose prediction: sending the medical image of any patient into the input end of the radiotherapy dose prediction network, and obtaining dose distribution L * by using the TG-43 method and the tissue heterogeneity correction method; and obtaining the dose distribution H *, which is predicted by the output end of the radiotherapy dose prediction network, of any one patient model body. According to the technical scheme disclosed by the invention, the technical effect of predicting the output result of a high-precision algorithm by using a low-precision algorithm is achieved.

Description

technical field [0001] The invention relates to the technical field of radiotherapy dose calculation, in particular to a radiotherapy dose prediction method. Background technique [0002] As a type of radiation therapy, brachytherapy refers to a treatment method in which sealed radioactive particles are placed in human tissues, cavities or skin surfaces for radiation therapy. In the treatment of head and neck tumors, pelvic tumors, prostate tumors and other tumors, brachytherapy has shown positive and effective therapeutic effects. When making a radiotherapy plan, it is necessary to simulate and evaluate the treatment effect based on the dose distribution generated by the particles. When calculating the particle dose distribution, most of the calculation formulas and parameters recommended by the American Association of Physicists in Medicine TG-43 report can be used to quickly calculate the dose distribution. TG-43 does not consider the impact of heterogeneous media such ...

Claims

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Application Information

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IPC IPC(8): A61N5/10G16H20/40
CPCA61N5/1001A61N5/1031A61N5/1048G16H20/40A61N2005/1092
Inventor 刘博熊天宇周付根
Owner BEIHANG UNIV
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