Proton therapy’s ability to spare normal tissue generally lowers complications, making it an attractive treatment option for head and neck (HN) cancer. Yet, oral mucositis, one of the most frequent and clinically relevant toxicities, occurs in approximately 6...
Author profile
Francesco Giuseppe Cordoni
University of Trento
External Validation of a Machine Learning Model for Oral Mucositis Prediction In Proton Therapy
Poster Program · Therapy Physics
Machine Learning-Based Beam Delivery Time Model for Mevion S250i with Hyperscan Technology
Accurate prediction of beam delivery time (BDT) is essential for operational efficiency, 4D dose calculations, and advanced proton therapy techniques such as proton arc therapy. Despite its importance, no machine-specific BDT model currently exists for Mevion...
Poster Program · Therapy Physics
Moving Beyond a Generic Rbe: Experimental Validation of GSM2 for Clinical Proton Therapy
Proton therapy plans are optimized by relating the delivered dose to an equivalent photon dose using the Relative Biological Effectiveness (RBE). Clinically, a constant RBE of 1.1 is assumed, despite evidence that RBE varies along the proton beam path. Accura...
Poster Program · Therapy Physics