An interpretable radiomics model to select patients for radiotherapy after surgery for WHO grade 2 meningiomas.

ABSTRACT:

Objectives

This study investigated whether radiomic features can improve the prediction accuracy for tumor recurrence over clinicopathological features and if these features can be used to identify high-risk patients requiring adjuvant radiotherapy (ART) in WHO grade 2 meningiomas.

Methods

Preoperative magnetic resonance imaging (MRI) of 155 grade 2 meningioma patients with a median follow-up of 63.8 months were included and allocated to training (n = 92) and test sets (n = 63). After radiomic feature extraction (n = 200), least absolute shrinkage and selection operator feature selection with logistic regression classifier was performed to develop two models: (1) a clinicopathological model and (2) a combined clinicopathological and radiomic model. The probability of recurre

SUBMITTER: Park CJ 

PROVIDER: S-EPMC9396861 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature