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Published on: May 9, 2014
Comparison of log file-based and measurement-based QA for detecting MLC positional errors and evaluating dosimetric
Chul Hang Kim1,2, Ki Mun Kang1,3, Hoon Sik Choi1,3
1Department of Radiation Oncology, Gyeongsang National University School of Medicine, and Gyeongsang National University Changwon Hospital, Changwon, Republic of Korea.
Purpose:
This study aimed to compare the sensitivity of log file-based quality assurance (LF-QA) and measurement-based quality assurance (MB-QA) for detecting multileaf collimator (MLC) positional errors and to evaluate the dosimetric impacts of MLC mechanical drive train defects.
Methods:
Mechanical degradation of the MLC was simulated on a TrueBeam STx system by inducing three defect types: T-nut surface wear (0.5-1.2 mm), drive screw thread wear, and motor degradation. MLC positioning accuracy was assessed using a rotational Picket Fence (PF) test, and the dosimetric impacts were evaluated on clinical breast intensity‑modulated radiation therapy (IMRT) and prostate volumetric‑modulated arc therapy (VMAT) plans. LF-QA and MB-QA were performed concurrently under identical delivery conditions. Gamma passing rates (GPRs) and dose-volume histogram (DVH) analyses were compared between baseline and defective deliveries.
Results:
LF-QA detected positional deviations between baseline and defective conditions (<0.14 mm; p < 0.05) but consistently underestimated the extent of the induced defects. Correspondingly, LF-QA gamma analysis (GPRs ≈ 100%) and DVH metrics (∆D < 0.2%) showed no detectable dosimetric differences. MB-QA exhibited higher sensitivity to specific MLC defects, identifying localized fluence variations for T-nut surface wear, whereas no discernible differences were observed for drive screw thread wear or motor degradation. MB-QA gamma analysis revealed localized dose differences of up to 15% in breast IMRT and 7.4% in prostate VMAT. DVH analysis further demonstrated clinically relevant dose variations in organs at risk (OARs), including the contralateral breast (ΔDmean: 5.52%) and right lung (ΔD1: 4.50%) in breast IMRT, and the penile bulb (ΔD99: 1.55%) in prostate VMAT.
Conclusion:
LF-QA showed limited sensitivity to sub-millimeter MLC errors and did not capture clinically meaningful dosimetric deviations under mechanically degraded conditions. MB-QA enabled superior error detection and clinically relevant dosimetric verification. These findings indicate that LF-QA alone may be insufficient for patient-specific QA and that incorporating MB-QA is essential for ensuring reliable dosimetric verification.
