Radiomic features of contralateral and ipsilateral hemispheres for prediction of glioma genetic markers

Purpose: Radiomic features of gliomas are often used to predict genetic markers from radiological studies. Radiomic features were extracted from the contralateral brain to test if tumor texture is driving the predictive power of machine learning models. Ideally, these contralateral models would be a negative control for tumor radiomics models, since many studies use contralateral normal appearing white matter for normalization. This study used those features to attempt to predict IDH mutation status, MGMT promoter methylation, TERT promoter mutation, and ATRX mutation status with random forests.