Work

Design an open‐access dynamic spot‐scanning proton arc system controller for quantitative and comprehensive investigation of delivery efficiency

Year: 2025

Type: article

Abstract: BACKGROUND: Proton arc therapy enables continuous treatment delivery while rotating the gantry. One of the key components in the proton arc system is the controller's design, which determines the irradiation sequence and gantry mechanical rotation. PURPOSE: ) and comprehensively investigates the treatment delivery time in a relationship of different mechanical parameters. METHOD: applied control theory to iteratively optimize and calculate the irradiation sequence across the control points to ensure an efficient treatment delivery while meeting the mechanical constraints. The calculation considers the parameters such as tolerance window, buffer window, and maximum acceleration and deceleration speed of the gantry. Five different disease sites, e.g., liver, head, and neck, intracranial, lung, and prostate cancer cases were used for testing purposes. Various parameters and settings were used to quantitatively investigate the dynamic spot-scanning proton arc (SPArc) treatment delivery time and total momentum changes. RESULT: The result indicates that the significant impact of dynamic treatment delivery time comes from the buffer window setting relative to the tolerance window, in which a large buffer leads to a slower delivery process. On the other hand, the maximum acceleration and deceleration speed plays an important role in the treatment delivery efficiency if the buffer window occupies large portion of each tolerance window. Additionally, the buffer window setting also impacts the total momentum changes during the dynamic treatment delivery. CONCLUSION: for dynamic treatment delivery simulation, allowing clinical users or investigators to adjust various machine parameters for testing purposes. This platform could serve as a foundation for testing future advancements in the dynamic SPArc technology, including hardware, system controller, and treatment planning optimization algorithm design.

Source: Medical Physics

DOI: 10.1002/mp.70213