Improved outcome prediction of oropharyngeal cancer by combining clinical and MRI features in machine learning models

Highlights: • Clinical and MRI features predict treatment outcome in oropharyngeal cancer. • MRI features improve performance of models based on clinical variables. • Future research is recommended in outcome prediction for HPV tumor subgroups. • Rounder and homogenous tumors are associated with a more favourable outcome. New markers are required to predict chemoradiation response in oropharyngeal squamous cell carcinoma (OPSCC) patients. This study evaluated the ability of magnetic resonance (MR) radiomics to predict locoregional control (LRC) and overall survival (OS) after chemoradiation and aimed to determine whether this has added value to traditional clinical outcome predictors.