Radiomics and Qualitative Features From Multiparametric MRI Predict Molecular Subtypes in Patients With Lower-Grade Glioma

Radiomics and Qualitative Features From Multiparametric MRI Predict Molecular Subtypes in Patients With Lower-Grade Glioma

BackgroundIsocitrate dehydrogenase (IDH) mutation and 1p19q codeletion status have been identified as significant markers for therapy and prognosis in lower-grade glioma (LGG). The current study aimed to construct a combined machine learning-based model for predicting the molecular subtypes of LGG,...

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Bibliographic Details
Main Authors: Chen Sun, Liyuan Fan, Wenqing Wang, Weiwei Wang, Lei Liu, Wenchao Duan, Dongling Pei, Yunbo Zhan, Haibiao Zhao, Tao Sun, Zhen Liu, Xuanke Hong, Xiangxiang Wang, Yu Guo, Wencai Li, Jingliang Cheng, Zhicheng Li, Xianzhi Liu, Zhenyu Zhang, Jing Yan
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-01-01
Series:Frontiers in Oncology
Subjects:
lower-grade glioma
radiomics
Visually Accessible Rembrandt Images
molecular subtypes
machine learning
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2021.756828/full

Internet

https://www.frontiersin.org/articles/10.3389/fonc.2021.756828/full

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