Comparison of 3D and 2D gamma passing rate criteria for detection sensitivity to IMRT delivery errors

摘要

This study compared three‐dimensional (3D) and two‐dimensional (2D) percentage gamma passing rates (%GPs) for detection sensitivity to IMRT delivery errors and investigated the correlation between two kinds of %GP. Eleven prostate IMRT cases were selected, and errors in multileaf collimator (MLC) bank sag, MLC leaf traveling, and machine output were simulated by recalculating the dose distributions in patients. 2D doses were extracted from the 3D doses at the isocenter position. The 3D and 2D %GPs with different gamma criteria were then obtained by comparing the recalculated and original doses in specific regions of interest (ROI), such as the whole body, the planning target volume (PTV), the bladder, and the rectum. The sensitivities to simulated errors of the two types of %GP were compared, and the correlation between the 2D and 3D %GPs for different ROIs were analyzed. For the whole‐body evaluation, both the 2D and 3D %GPs with the 3%/3 mm criterion were above 90% for all tested MLC errors and for MU deviations up to 4%, and the 3D %GP was higher than the 2D % style="fixed-case">GP. In organ‐specific evaluations, the style="fixed-case">PTV‐specific 2D and 3D % style="fixed-case">GP gradients were −4.70% and −5.14% per millimeter of the style="fixed-case">MLC traveling error, and −17.79% and −20.50% per percentage of style="fixed-case">MU error, respectively. However, a stricter criterion (2%/1 mm) was needed to detect the tested style="fixed-case">MLC sag error. The Pearson correlation analysis showed a significant strong correlation (r > 0.8 and P < 0.001) between the 2D and 3D % style="fixed-case">GPs in the whole body and style="fixed-case">PTV‐specific gamma evaluations. The whole‐body % style="fixed-case">GP with the 3%/3 mm criterion was inadequate to detect the tested style="fixed-case">MLC and style="fixed-case">MU errors, and a stricter criterion may be needed. The style="fixed-case">PTV‐specific gamma evaluation helped to improve the sensitivity of the error detection, especially using the 3D style="fixed-case">GP%.