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Brain tumor radiotherapy mode intelligent selection method, system, equipment and medium

An intelligent selection, brain tumor technology, applied in medical image analysis technology and application fields, can solve the problems of not paying attention to the impact of the treatment effect and survival prognosis of brain tumor patients, ignoring the importance of precise radiotherapy, etc., to achieve clinical precise radiotherapy, Realize the effect of rational distribution and high clinical application value

Pending Publication Date: 2022-03-11
INST OF MODERN PHYSICS CHINESE ACADEMY OF SCI
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] However, many previous researchers applied radiomics methods to target delineation and plan design during radiotherapy [Brouwer CL, Dinkla AM, Vandewinckele L, et al. Machine learning applications in radiation oncology: Current use and needs to support clinical implementation.Physics and Imaging in Radiation Oncology.2020; 16:144-148.], focusing on the relationship between radiotherapy dose, radiotherapy time and curative effect, but did not pay attention to the effect of radiotherapy on the treatment effect and The impact of survival and prognosis, ignoring the importance of individualized selection of radiotherapy methods for precise radiotherapy

Method used

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  • Brain tumor radiotherapy mode intelligent selection method, system, equipment and medium
  • Brain tumor radiotherapy mode intelligent selection method, system, equipment and medium
  • Brain tumor radiotherapy mode intelligent selection method, system, equipment and medium

Examples

Experimental program
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Embodiment 1

[0056] like figure 1 As shown, this embodiment provides a method for intelligently selecting a brain tumor radiotherapy method based on machine learning, including the following steps:

[0057] 1) Construct a multimodal MRI brain tumor segmentation model with adaptive parameter optimization, and use the multimodal MRI images of brain tumor patients before and after radiotherapy in the brain tumor radiotherapy database as input for brain tumor ROI segmentation to obtain paired brain tumors Regional ROI before radiotherapy Pre-RT and residual region ROI after radiotherapy residual ;

[0058] 2) Construct an intelligent non-invasive brain tumor diagnosis and prognosis model, with an effective feature vector E RT As input, the prediction results of pathological grade and radiotherapy prognosis are obtained; among them, the effective feature vector E RT Regional ROIs before radiotherapy for paired brain tumors Pre-RT and residual region ROI after radiotherapy residual extract...

Embodiment 2

[0118] like Figure 4 As shown, this embodiment intelligently selects the radiotherapy method for a brain tumor patient who is provided with multimodal MRI, and the specific implementation steps are as follows:

[0119] (1) Obtain the multimodal MRI data of the patient, perform image preprocessing on the multimodal MRI, and input the preprocessed image to the trained U 2 -Net network segmentation model, get the segmented ROI Pre-RT ;

[0120] (2) Using the pre-trained multi-channel convolutional neural network model to ROI Pre-RT Perform feature extraction to obtain deep learning features D Pre-RT ;

[0121] (3) The deep learning feature D Pre-RT Input multiple classifiers to classify and predict IDH-wild type, IDH-mutant, MGMT promoter methylation status, 1p / 19q deletion and other genotypes, and obtain molecular typing prediction results, that is, gene characteristics;

[0122] (4) Integrate and screen the predicted gene features and deep learning features to obtain an ...

Embodiment 3

[0128] Embodiment 1 above provides a method for intelligently selecting a radiotherapy mode for brain tumors. Correspondingly, this embodiment provides a system for intelligently selecting radiotherapy modes for brain tumors. The identification system provided in this embodiment can implement the brain tumor radiotherapy mode intelligent selection system in Embodiment 1, and the system can be realized by software, hardware or a combination of software and hardware. For example, the system may include integrated or separate functional modules or functional units to execute corresponding steps in the methods of Embodiment 1. Since the identification system of this embodiment is basically similar to the method embodiment, the description process of this embodiment is relatively simple. For relevant parts, please refer to the part of the description of Embodiment 1. The embodiment of the system of this embodiment is only schematic .

[0129] A brain tumor radiotherapy mode intell...

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Abstract

The invention relates to a brain tumor radiotherapy mode intelligent selection method, system and device and a medium, and the method comprises the steps: constructing a multi-mode MRI brain tumor segmentation model, carrying out the brain tumor ROI segmentation of a multi-mode MRI image before and after radiotherapy of a patient, and obtaining a brain tumor pre-radiotherapy region and a brain tumor post-radiotherapy residual region which are paired; constructing a brain tumor diagnosis prognosis model, and taking the effective feature vectors as input to obtain prediction results of pathological grading and radiotherapy prognosis; constructing a brain tumor radiotherapy mode intelligent selection model, and taking image gene features and radiotherapy sensitive features before radiotherapy as input to obtain an optimal radiotherapy mode; and constructing a brain tumor radiotherapy curative effect visual model, and obtaining a predicted post-radiotherapy MRI image by taking the brain tumor MRI image of the patient before radiotherapy, the prediction results of pathological grading and radiotherapy prognosis and the optimal radiotherapy mode as input. The method can be widely applied to the medical image analysis technology and the application field.

Description

technical field [0001] The present invention relates to the field of medical image analysis technology and application, in particular to a machine learning-based intelligent selection method, system, equipment and medium for brain tumor radiotherapy. Background technique [0002] Brain tumors include primary brain tumors originating from intracranial cells and metastatic brain tumors transferred from other organs, more than half of which are malignant tumors. Brain tumors have the characteristics of fast growth, high recurrence rate and high disability rate. characteristics, seriously threatening human life and health. Radiation therapy is an important treatment for brain tumors, which can improve the survival rate and quality of life of patients with brain tumors. [0003] With the continuous updating of radiotherapy technology and equipment, conventional radiotherapy, stereotactic radiotherapy (SRT), helical tomotherapy (TOMO), gamma knife, brachytherapy, proton radiother...

Claims

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Application Information

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IPC IPC(8): G16H20/40G06V10/26G06V10/82G06N3/04
CPCG16H20/40G06N3/045
Inventor 李佳昕陈卫强于泽宽李强耿道颖杜鹏
Owner INST OF MODERN PHYSICS CHINESE ACADEMY OF SCI
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