Integrating Structure Propagation Uncertainties in the Optimization of Online Adaptive Proton Therapy Plans

SIMPLE SUMMARY: The fast and accurate definition of structures is a main limiting factor in online adaptive proton therapy. In this study, different methods to include structure propagation uncertainties in the optimization were compared with adaptation using physician-drawn structures, uncorrected propagated structures, and no adaptation. While adaptation with physician-drawn structures resulted in the best adaptive plan quality and no adaptation in the worst, manual structure correction could be replaced by a fast ‘plausibility check’, and plans could be adapted with correction-free adaptation strategies. ABSTRACT: Currently, adaptive strategies require time- and resource-intensive manual structure corrections. This study compares different strategies: optimization without manual structure correction, adaptation with physician-drawn structures, and no adaptation. Strategies were compared for 16 patients with pancreas, liver, and head and neck (HN) cancer with 1–5 repeated images during treatment: ‘reference adaptation’, with structures drawn by a physician; ‘single-DIR adaptation’, using a single set of deformably propagated structures; ‘multi-DIR adaptation’, using robust planning with multiple deformed structure sets; ‘conservative adaptation’, using the intersection and union of all deformed structures; ‘probabilistic adaptation’, using the probability of a voxel belonging to the structure in the optimization weight; and ‘no adaptation’. Plans were evaluated using reference structures and compared using a scoring system. The reference adaptation with physician-drawn structures performed best, and no adaptation performed the worst. For pancreas and liver patients, adaptation with a single DIR improved the plan quality over no adaptation. For HN patients, integrating structure uncertainties brought an additional benefit. If resources for manual structure corrections would prevent online adaptation, manual correction could be replaced by a fast ‘plausibility check’, and plans could be adapted with correction-free adaptation strategies. Including structure uncertainties in the optimization has the potential to make online adaptation more automatable.