A Direct Machine-Specific Parameters Incorporated Spot-Scanning Proton Arc (SPArc) Algorithm

Abstract

To address the challenges of generating a deliverable and efficient spot-scanning proton arc (SPArc) plan for a proton therapy system. We developed a novel SPArc optimization algorithm (SPArcDMSP) by directly incorporating the machine-specific parameters such as mechanical constraints and delivery sequence.A SPArc delivery sequence model (DSMarc) was built based on the machine-specific parameters of the prototype arc delivery system. The SPArcDMSP resamples and adjusts each control point's delivery speed based on the DSMarc calculation through the iterative approach. Users could set the expected arc delivery time and gantry max acceleration as a mechanical constraint during the SPArcDMSP optimization. Four cases (brain, liver, head neck, liver, and lung cancer) were selected to test SPArcDMSP. Two kinds of SPArc plans were generated using the same planning objective functions: (1) SPArcDMSP plan meeting the maximum allowable gantry acceleration speed (0.6deg/s2); (2) SPArcDMSP-user-speed plan with a user pre-defined delivery time and acceleration speed < 0.1 deg/s2. Arc delivery sequence such as gantry speed, delivery time was simulated based on the DSMarc and was compared.With a similar objective value, number of energy layers and spots, both SPArcDMSP and SPArcDMSP-user-speed plans could be delivered continuously within the ± 1 degree tolerance window (Table 1). The SPArcDMSP-user-speed plan could minimize the gantry momentum change based on clinical users input compared to the SPArcDMSP, which could help relieve mechanical challenge to accelerate or decelerate the hundreds of tons of gantry.For the first time, clinical users not only could generate a SPArc plan meeting the mechanical constraint of their proton system but also directly controlled the arc treatment speed and momentum changes of the gantry during the plan optimization. This work paved the roadmap for the clinical implementation of proton arc therapy in the treatment planning system.