Statistical process control of CBCT density gamma analysis as a clinical trigger for offline adaptive radiotherapy

<i>Objective.</i>Adaptive radiotherapy aimed to account for inter- and intra-fractional anatomical changes to improve target coverage and spare normal tissues. Commercial softwares could quantify anatomical and setup differences between planning computed tomography (pCT) and image-guidance cone-beam computed tomography (CBCT) using density gamma passing rate (dGPR). This study evaluated the utility of dGPR as an automated, site-specific trigger for offline adaptive workflows, using statistical process control (SPC) to define tolerance thresholds and correlating dGPR with setup errors, planning target volume (PTV) coverage, and longitudinal stability.<i>Approach.</i>240 patients across six anatomical sites were retrospectively analysed. First-fraction CBCTs were compared to pCTs using MobiusCB to compute dGPR. SPC analysis was performed to establish site-specific tolerance limits. Rigid phantom studies were conducted to quantify dGPR sensitivity to setup errors. Correlation between dGPR and PTV<i>V</i>_100%was assessed in patients with repeat CTs, and longitudinal stability of dGPR across fractions was evaluated.<i>Main results.</i>SPC-derived lower action limits (Al) ranged from 97.3% (brain) to 82.2% (breast), reflecting site-specific anatomical variability and imaging protocols. Phantom studies verified dGPR sensitivity due to rigid shifts, with head dGPR decreasing to as low as 83.5% at 8 mm translation, while pelvis dGPR remained above 93.2% for the same shift, reflecting greater tolerance due to its larger volume. In head-and-neck patients, dGPR correlated moderately with changes in PTV<i>V</i>_100%(<i>r</i>= 0.56), with no coverage losses >10% observed when dGPR exceeded 90%. Longitudinal analysis showed stable dGPR for most sites, but gradual declines in head-and-neck patients, with some values falling below SPC-derived threshold of 94.3% towards the end of treatment.<i>Significance.</i>dGPR offered a practical, automated, and site-specific metric for detecting anatomical changes and setup errors during radiotherapy. SPC-derived thresholds provided robust action levels tailored to each site, and MobiusCB enabled automated alerts when thresholds were exceeded, reducing reliance on subjective image inspection.