Integrated models incorporating radiologic and radiomic features predict meningioma grade, local failure, and overall survival.

ABSTRACT:

Background

We investigated prognostic models based on clinical, radiologic, and radiomic feature to preoperatively identify meningiomas at risk for poor outcomes.

Methods

Retrospective review was performed for 303 patients who underwent resection of 314 meningiomas (57% World Health Organization grade I, 35% grade II, and 8% grade III) at two independent institutions, which comprised primary and external datasets. For each patient in the primary dataset, 16 radiologic and 172 radiomic features were extracted from preoperative magnetic resonance images, and prognostic features for grade, local failure (LF) or overall survival (OS) were identified using the Kaplan-Meier method, log-rank tests and recursive partitioning analysis. Regressions and random forests were used to gene

SUBMITTER: Morin O 

PROVIDER: S-EPMC6777505 | biostudies-literature | 2019 May-Dec

REPOSITORIES: biostudies-literature