Brain glioma molecular marker nondestructive prediction method and prediction system based on radiomics

Abstract

The invention belongs to the technical field of computer-aided diagnosis, and specifically relates to a brain glioma molecular marker nondestructive prediction method and a prediction system based on radiomics. The method comprises the following steps: adopting a three-dimensional magnetic resonance image automatic segmentation method based on a convolution neural network; registering a tumor obtained from segmentation to a standard brain atlas, and acquiring 116 position features of tumor distribution; getting 21 gray features, 15 shape features and 39 texture features through calculation; carrying out three-dimensional wavelet decomposition on the gray features and the texture features to get 480 wavelet features of eight sub-bands; acquiring 671 high-throughput features from the three-dimensional T2-Flair magnetic resonance image of each case; using a feature screening strategy combining p-value screening and a genetic algorithm to get 110 features highly associated with IDH1; and using a support vector machine and an AdaBoost classifier to get a classification of which the IDH1 prediction accuracy is 80%. As a novel method of radiomics, the method provides a nondestructive prediction scheme of important molecular markers for clinical diagnosis of gliomas.

Description

technical field [0001] The invention belongs to the technical field of computer-aided diagnosis, in particular to a radiomics-based nondestructive prediction method and a prediction system for molecular markers of brain glioma. Background technique [0002] Glioma is the most common brain malignancy, and about 30% of them are low-grade gliomas (LGG, WHO grades I and II). Although low-grade gliomas have a relatively good prognosis, almost all low-grade gliomas will develop into high-grade gliomas with high mortality. Compared with glioblastoma (GBM, WHO grade IV), research on gene expression analysis and understanding of LGG is relatively lacking. [0003] IDH1 (isocitrate dehydrogenase 1) has significant diagnostic, prognostic, and predictive values, and is the most important molecular marker in glioma [1]. Most lower-grade gliomas (WHO grades II and III) and secondary GBMs have IDH1 mutations, while IDH1 mutations are rarely observed in primary GBMs; IDH1 is independent o...

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Problems solved by technology

Gene expression analysis and understanding of LGG is relatively understudied compared to glioblastoma (GBM, WHO grade IV)

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