T2-FLAIR, DWI and DKI radiomics satisfactorily predicts histological grade and Ki-67 proliferation index in gliomas.

ABSTRACT:

Objective

To build highly predictive performance models for glioma stratification with radiomics features from non-invasive MRI.

Methods

T2-weighted fluid-attenuated inversion recovery (T2-FLAIR) imaging, diffusion-weighted MRI and diffusion kurtosis imaging were retrospectively collected for 139 glioma cases (2 with grade I, 67 with grade II, 36 with grade III and 34 with grade IV disease). Multi-parameter maps, including the apparent diffusion coefficient (ADC), mean diffusion coefficient (Dmean), fractional anisotropy (FA), and mean kurtosis (MK), were co-registered to T2-FLAIR, and 431 radiomics features for each were extracted within manually segmented tumour regions. Partial correlation analysis revealed correlations between radiomics features and glioma stratification

SUBMITTER: Su C 

PROVIDER: S-EPMC8430185 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature