Abstract

To investigate the beam delivery time (BDT) reduction due to the improvement of machine parameters for Hitachi synchrotron-based proton PBS system. BDTs for representative treatment plans were calculated to quantitatively estimate the BDT improvement from our 2015 system at Mayo Clinic in Arizona to our system to be implemented in 2025 at Mayo Clinic in Florida, and to a hypothetical future system. To specifically assess how each incremental improvement in the operating parameters reduced the total BDT, for each plan, we simulated the BDT 10,368 times with various settings of the nine different operating parameters. The effect of each operating parameter on BDT reduction and its correlation with treatment plan characteristics were analyzed. The optimal number of multiple energy extraction (MEE) layers per spill for different systems was also investigated. The median (range) decrease in BDT was 60% (56%-70%) from the 2015 to the 2025 system. The following incremental improvement in parameters of the 2015 system for the 2025 system played an important role in this decreased BDT: beam intensity (8 to 20 MU/s), recapture efficiency (50% to 80%), number of MEE layers per spill (4 to 8), scanning magnet preparation and verification time (1.9 to 0.95 msec), and MEE layer switch time (200 to 100 msec). Reducing the total spill change time and scanning magnet preparation and verification time from those of the 2025 system further reduced BDT in the hypothetical future system. 8 MEE layers per spill is optimal for a system with 50% recapture efficiency; 16 MEE layers per spill is optimal for a system with 80% recapture efficiency; and more than 16 MEE layers per spill is beneficial only for a system close to 100% recapture efficiency. We systematically studied the effect of each machine operating parameter on the reduction in total BDT and its correlation with treatment plan characteristics. Our findings will aid new and existing synchrotron-based proton beam therapy centers to make balanced decisions on BDT benefits vs. costs when considering machine upgrade or new system selection.

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