Unknown

Dataset Information

Radiogenomic modeling predicts survival-associated prognostic groups in glioblastoma.


ABSTRACT:

Background

Combined whole-exome sequencing (WES) and somatic copy number alteration (SCNA) information can separate isocitrate dehydrogenase (IDH)1/2-wildtype glioblastoma into two prognostic molecular subtypes, which cannot be distinguished by epigenetic or clinical features. The potential for radiographic features to discriminate between these molecular subtypes has yet to be established.

Methods

Radiologic features (n = 35 340) were extracted from 46 multisequence, pre-operative magnetic resonance imaging (MRI) scans of IDH1/2-wildtype glioblastoma patients from The Cancer Imaging Archive (TCIA), all of whom have corresponding WES/SCNA data. We developed a novel feature selection method that leverages the structure of extracted MRI features to mitigat

SUBMITTER: Nuechterlein N 

PROVIDER: S-EPMC7883769 | biostudies-literature | 2021 Jan-Dec

REPOSITORIES: biostudies-literature