Feature-based Response Prediction to Immunotherapy of late-stage Melanoma Patients Using PET/MR Imaging

Abstract

The treatment of malignant melanoma with immunotherapy is a promising approach to treat advanced stages of the disease. However, the treatment can cause serious side effects and not every patient responds to it. This means, crucial time may be wasted on an ineffective treatment. Assessment of the possible therapy response is hence an important research issue. The research presented in this study focuses on the investigation of the potential of medical imaging and machine learning to solve this task. To this end, we extracted image features from multi-modal images and trained a classifier to differentiate non-responsive patients from responsive ones.