An MRI-based radiomics method combined with clinic-radiological characteristics for the prediction of survival in aggressive spinal tumor

Motivation: Treatment options for spinal tumors are challenging. Goal(s): To predict the progression-free survival (PFS) of aggressive spinal tumors based on MRI combined with clinical features to aid early personalized treatment decisions. Approach: Clinical, pathological and imaging data of 211 patients underwent spinal tumor surgery at two research centers were retrospectively analyzed. Tumoral and peritumoral features were extracted from T1WI and T2WI images. Clinical-radiomics nomogram was developed by radiomics signatures and the predictive clinical parameters. Results: The integrative model showed best performance in PFS evaluation for the prediction of postoperative PFS, with the AUC was 0.86 and 0.81 in the training and test cohort. Impact: Rad-score is an independent factor for PFS after resection for spinal tumor. The nomogram established in this study could be an effective tool for the clinical prediction of PFS after surgery.