Correlation of phantom‐based and log file patient‐specific QA with complexity scores for VMAT

The motivation for this study was to reduce physics workload relating to patient‐specific quality assurance (QA). VMAT plan delivery accuracy was determined from analysis of pre‐ and on‐treatment trajectory log files and phantom‐based ionization chamber array measurements. The correlation in this combination of measurements for patient‐specific QA was investigated. The relationship between delivery errors and plan complexity was investigated as a potential method to further reduce patient‐specific QA workload. Thirty VMAT plans from three treatment sites — prostate only, prostate and pelvic node (PPN), and head and neck (H&N) — were retrospectively analyzed in this work. The 2D fluence delivery reconstructed from pretreatment and on‐treatment trajectory log files was compared with the planned fluence using gamma analysis. Pretreatment dose delivery verification was also carried out using gamma analysis of ionization chamber array measurements compared with calculated doses. Pearson correlations were used to explore any relationship between trajectory log file (pretreatment and on‐treatment) and ionization chamber array gamma results (pretreatment). Plan complexity was assessed using the MU/ arc and the modulation complexity score (MCS), with Pearson correlations used to examine any relationships between complexity metrics and plan delivery accuracy. Trajectory log files were also used to further explore the accuracy of MLC and gantry positions. Pretreatment 1%/1 mm gamma passing rates for trajectory log file analysis were 99.1% (98.7%–99.2%), 99.3% (99.1%–99.5%), and 98.4% (97.3%–98.8%) (median (IQR)) for prostate, PPN, and H&N, respectively, and were significantly correlated to on‐treatment trajectory log file gamma results ([Formula: see text]). Pretreatment ionization chamber array (2%/2 mm) gamma results were also significantly correlated with on‐treatment trajectory log file gamma results ([Formula: see text]). Furthermore, all gamma results displayed a significant correlation with MCS ([Formula: see text]), but not with MU/arc. Average MLC position and gantry angle errors were [Formula: see text] and [Formula: see text] over all treatment sites and were not found to affect delivery accuracy. However, variability in MLC speed was found to be directly related to MLC position accuracy. The accuracy of VMAT plan delivery assessed using pretreatment trajectory log file fluence delivery and ionization chamber array measurements were strongly correlated with on‐treatment trajectory log file fluence delivery. The strong correlation between trajectory log file and phantom‐based gamma results demonstrates potential to reduce our current patient‐specific QA. Additionally, insight into MLC and gantry position accuracy through trajectory log file analysis and the strong correlation between gamma analysis results and the MCS could also provide further methodologies to both optimize the VMAT planning and QA process. PACS number: 87.53.Bn, 87.55.Kh, 87.55.Qr