Purpose: Measurement-based QA identifies large deviations between planned and delivered dose, but subtle—yet clinically unacceptable—deviations can pass through the conventional QA process unnoticed. Incorporating logfile-based information into pre-treatment QA should result in more robust QA overall, provided such information is stable across the entire treatment course. We present here a case-study of logfile stability to investigate the potential of logfiles as useful adjuncts in the QA process.
Methods: We analyzed logfiles from six fractions of a VMAT plan delivered on an Elekta Infinity linac with an Agility MLC. To simplify the analysis, we considered a single 52 control point VMAT field, which delivered 92 cGy in 294.5 MU between gantry angles of 182° and 30°. We used the first treatment logfile as the reference logfile and compared subsequent treatment fractions to it. As most parameters change during a VMAT control point, we focused the numerical results on the values at the beginning of each control point. We report day-to-day RMS differences in gantry angle, diaphragm position, MU/rate, MU delivered, and MLC leaf positions.
Results: Day-to-day deviations between logfile parameters at the start of each control point existed but on average fell within TG-142 established limits. The maximum deviation of gantry position of any control in any treatment session was 1.4° with an RMS average of 0.4° over all control points. Other parameters (MAX, RMS): Diaphragm position (0.5 mm, 0.13 mm), MU/rate (47 MU/min, 11.2 MU/min) , MU (0.4 MU, 0.12 MU), and MLC position (2.0 mm, 0.14 mm).
Conclusion: In this case, the small per-fraction differences indicate that logfile information was representative enough of future machine performance to have been useful in pre-treatment QA. However, notable outliers suggest that a broad survey of VMAT logfiles is required to firmly establish conditions under which logfile stability most suffers.