Radiographic prediction of meningioma grade by semantic and radiomic features.

ABSTRACT:

Objectives

The clinical management of meningioma is guided by tumor grade and biological behavior. Currently, the assessment of tumor grade follows surgical resection and histopathologic review. Reliable techniques for pre-operative determination of tumor grade may enhance clinical decision-making.

Methods

A total of 175 meningioma patients (103 low-grade and 72 high-grade) with pre-operative contrast-enhanced T1-MRI were included. Fifteen radiomic (quantitative) and 10 semantic (qualitative) features were applied to quantify the imaging phenotype. Area under the curve (AUC) and odd ratios (OR) were computed with multiple-hypothesis correction. Random-forest classifiers were developed and validated on an independent dataset (n = 44).

Results

Twelve radiographic featur

SUBMITTER: Coroller TP 

PROVIDER: S-EPMC5690632 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature