Feasibility of prompt gamma verification for cone-beam computed tomography-based online adaptive proton therapy.

BACKGROUND AND PURPOSE: Prompt-gamma based in vivo treatment verification, such as prompt-gamma imaging (PGI), is crucial for detecting anatomical changes and serving as safety net during proton therapy treatments. This is especially important in an online-adaptive setting, when imaging will be based on cone-beam computed tomography (CBCT). This study investigated whether PGI, proven effective to detect relevant anatomical changes in clinical settings, can also verify treatment plans adapted on CBCTs, particularly the reliability of CBCT-based PGI-simulations of expected prompt-gamma distributions, a key requirement for PGI-based verification. MATERIAL AND METHODS: For a homogeneous and anthropomorphic phantom, a fan-beam computed tomography (CT) and a CBCT were acquired. Corrected CBCT and virtual CT datasets were generated. PGI simulations and independent dose calculations were performed on the different CBCT datasets and compared to the fan-beam CT, extracting PGI-based and integrated-depth-dose (IDD)-based range-shifts. For three head-and-neck cancer patients, PGI-based shifts between the fan-beam CT and a synthetic CT (from a daily CBCT) were compared to line-dose-based shifts from clinical dose calculations. RESULTS: For the homogeneous phantom, all CBCT datasets enabled adequate PGI simulations, with PGI-based shifts correlating very closely with IDD-based shifts. For the anthropomorphic phantom and the three patient datasets, observed PGI-based shifts were correlated to IDD-based shifts. CONCLUSIONS: For phantom and patient data, PGI simulations depended mainly on the reliability of depth-dose distributions on the planning image with negligible uncertainties from PG emission. For CBCT-based OAPT, correct depth-dose distributions are required. Hence, PGI is also a promising treatment verification tool for CBCT-based OAPT.