Unifying gamma passing rates in patient-specific QA for VMAT lung cancer treatment based on data assimilation

• Published in: Physical and engineering sciences in medicine 2024-12, Vol.47 (4), p.1337-1348
• Main Authors: Ono, Tomohiro, Adachi, Takanori, Hirashima, Hideaki, Iramina, Hiraku, Kishi, Noriko, Matsuo, Yukinori, Nakamura, Mitsuhiro, Mizowaki, Takashi
• Format: Article
• Language: English
• Subjects: Aged; Algorithms; Biological and Medical Physics; Biomedical and Life Sciences; Biomedical Engineering and Bioengineering; Biomedicine; Biophysics; Female; Gamma Rays; Humans; Lung Neoplasms - diagnostic imaging; Lung Neoplasms - radiotherapy; Male; Medical and Radiation Physics; Middle Aged; Quality Assurance, Health Care; Radiotherapy Dosage; Radiotherapy Planning, Computer-Assisted; Radiotherapy, Intensity-Modulated; Scientific Paper
• ISSN: 2662-4729; 2662-4737; 2662-4737
• DOI: 10.1007/s13246-024-01448-3

This study aimed to identify systematic errors in measurement-, calculation-, and prediction-based patient-specific quality assurance (PSQA) methods for volumetric modulated arc therapy (VMAT) on lung cancer and to standardize the gamma passing rate (GPR) by considering systematic errors during data assimilation. This study included 150 patients with lung cancer who underwent VMAT. VMAT plans were generated using a collapsed-cone algorithm. For measurement-based PSQA, ArcCHECK was employed. For calculation-based PSQA, Acuros XB was used to recalculate the plans. In prediction-based PSQA, GPR was forecasted using a previously developed GPR prediction model. The representative GPR value was estimated using the least-squares method from the three PSQA methods for each original plan. The unified GPR was computed by adjusting the original GPR to account for systematic errors. The range of limits of agreement (LoA) were assessed for the original and unified GPRs based on the representative GPR using Bland–Altman plots. For GPR (3%/2 mm), original GPRs were 94.4 ± 3.5%, 98.6 ± 2.2% and 93.3 ± 3.4% for measurement-, calculation-, and prediction-based PSQA methods and the representative GPR was 95.5 ± 2.0%. Unified GPRs were 95.3 ± 2.8%, 95.4 ± 3.5% and 95.4 ± 3.1% for measurement-, calculation-, and prediction-based PSQA methods, respectively. The range of LoA decreased from 12.8% for the original GPR to 9.5% for the unified GPR across all three PSQA methods. The study evaluated unified GPRs that corrected for systematic errors. Proposing unified criteria for PSQA can enhance safety regardless of the methods used.