A radiomics model for preoperative prediction of brain invasion in meningioma non-invasively based on MRI: A multicentre study.

ABSTRACT:

Background

Prediction of brain invasion pre-operatively rather than postoperatively would contribute to the selection of surgical techniques, predicting meningioma grading and prognosis. Here, we aimed to predict the risk of brain invasion in meningioma pre-operatively using a nomogram by incorporating radiomic and clinical features.

Methods

In this case-control study, 1728 patients from Beijing Tiantan Hospital (training cohort: n = 1070) and Lanzhou University Second Hospital (external validation cohort: n = 658) were diagnosed with meningiomas by histopathology. Radiomic features were extracted from the T1-weighted post-contrast and T2-weighted magnetic resonance imaging. The least absolute shrinkage and selection operator was used to select the most informative features

SUBMITTER: Zhang J 

PROVIDER: S-EPMC7393568 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature