Osteosarcoma Clinical Trials

Objective: * Define the frequency of replanning necessary to ensure tumor coverage never falls below 95% (or 5% drop) of the prescribed daily dose in participants with intact (gross) tumors to keep the tumor control optimal throughout the multi-week treatment regimen. * Define the frequency of replanning necessary to ensure organs-at-risk (critical organs) do not deviate by more than 10% of the initially approved dose constraints to keep the normal tissue complication minimal throughout the multi-week treatment regimen. Secondary Objectives * Establish a cone beam CT (CBCT)-based framework for quantifying body surface changes throughout the treatment course. This goal will be achieved by developing a novel algorithm that detects and tracks external anatomical variations longitudinally, without requiring CBCT image enhancement, enabling precise assessment of daily participant setup consistency and anatomical stability. * Overcome daily CBCT quality limitations by generating synthetic CT images that accurately represent daily anatomy and support proton dose recalculation or verification planning. This goal will be achieved by developing a hybrid pipeline that integrates deep learning models with the deformable image registration algorithm, trained and validated on disease site-specific data. This will enable precise dose mapping and tissue density estimation, directly supporting adaptive planning decisions without the need of diagnostic- quality CT images.