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Radiomic profiles in diffuse glioma reveal distinct subtypes with prognostic value.

Authors :
Lin, Peng
Peng, Yu-ting
Gao, Rui-zhi
Wei, Yan
Li, Xiao-Jiao
Huang, Su-Ning
Fang, Ye-Ying
Wei, Zhu-Xin
Huang, Zhi-Guang
Yang, Hong
Chen, Gang
Source :
Journal of Cancer Research & Clinical Oncology; May2020, Vol. 146 Issue 5, p1253-1262, 10p
Publication Year :
2020

Abstract

Purpose: To evaluate a radiomic approach for the stratification of diffuse gliomas with distinct prognosis and provide additional resolution of their clinicopathological and molecular characteristics. Methods: For this retrospective study, a total of 704 radiomic features were extracted from the multi-channel MRI data of 166 diffuse gliomas. Survival-associated radiomic features were identified and submitted to distinguish glioma subtypes using consensus clustering. Multi-layered molecular data were used to observe the different clinical and molecular characteristics between radiomic subtypes. The relative profiles of an array of immune cell infiltrations were measured gene set variation analysis approach to explore differences in tumor immune microenvironment. Results: A total of 6 categories, including 318 radiomic features were significantly correlated with the overall survival of glioma patients. Two subgroups with distinct prognosis were separated by consensus clustering of radiomic features that significantly associated with survival. Histological stage and molecular factors, including IDH status and MGMT promoter methylation status were significant differences between the two subtypes. Furthermore, gene functional enrichment analysis and immune infiltration pattern analysis also hinted that the inferior prognosis subtype may more response to immunotherapy. Conclusion: A radiomic model derived from multi-parameter MRI of the gliomas was successful in the risk stratification of diffuse glioma patients. These data suggested that radiomics provided an alternative approach for survival estimation and may improve clinical decision-making. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01715216
Volume :
146
Issue :
5
Database :
Complementary Index
Journal :
Journal of Cancer Research & Clinical Oncology
Publication Type :
Academic Journal
Accession number :
142632041
Full Text :
https://doi.org/10.1007/s00432-020-03153-6