A Deep Survival Model based on MR Radiomics and EGFR status to Predict Overall Survival after Radiosurgery in Brain Metastases

Abstract

About 30% of Non-small cell lung cancer (NSCLC) patients develop brain metastases (BMs) during the course of the disease. MR radiomics and EGFR mutation status were reported with the potential to predict the local tumor control of Gamma Knife stereotactic radiosurgery (GKRS). The prediction of overall survival after GKRS can further benefit the management of BM patients. We proposed a deep learning-based model using the clinical information, EGFR mutation status, and MR radiomic features to predict the overall survival after GKRS. We suggested that pre-GKRS MRI characteristics combined with gene and clinical information can improve the prediction of overall survival.