Radiomics analysis allows for precise prediction of epilepsy in patients with low-grade gliomas.

ABSTRACT:

Purpose

To investigate the association between imaging features and low-grade gliomas (LGG) related epilepsy, and to propose a radiomics-based model for the prediction of LGG-associated epilepsy.

Methods

This retrospective study consecutively enrolled 286 patients with LGGs (194 in the primary cohort and 92 in the validation cohort). T2-weighted MR images (T2WI) were used to characterize risk factors for LGG-related epilepsy: Tumor location features and 3-D imaging features were determined, following which the interactions between these two kinds of features were analyzed. Elastic net was applied to generate a radiomics signature combining key imaging features associated with the LGG-related epilepsy with the primary cohort, and then a nomogram incorporating radiomics signat

SUBMITTER: Liu Z 

PROVIDER: S-EPMC6051495 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature