Radiomic Immunophenotyping of GSEA-Assessed Immunophenotypes of Glioblastoma and Its Implications for Prognosis: A Feasibility Study

Radiomic Immunophenotyping of GSEA-Assessed Immunophenotypes of Glioblastoma and Its Implications for Prognosis: A Feasibility Study

Characterization of immunophenotypes in glioblastoma (GBM) is important for therapeutic stratification and helps predict treatment response and prognosis. Radiomics can be used to predict molecular subtypes and gene expression levels. However, whether radiomics aids immunophenotyping prediction is s...

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Bibliographic Details
Main Authors: Justin Bo-Kai Hsu, Gilbert Aaron Lee, Tzu-Hao Chang, Shiu-Wen Huang, Nguyen Quoc Khanh Le, Yung-Chieh Chen, Duen-Pang Kuo, Yi-Tien Li, Cheng-Yu Chen
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Cancers
Subjects:
glioblastoma
radiogenomics
immunophenotypes
first-order statistics
gray-level run length matrix
gray-level co-occurrence matrix
Online Access:https://www.mdpi.com/2072-6694/12/10/3039

Internet

https://www.mdpi.com/2072-6694/12/10/3039

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