Clinically oriented contour evaluation using geometric and dosimetric indices based on simple geometric transformations

Abstract Background: In radiotherapy, geometric indices are often used to evaluate the accuracy of contouring; however, the ability of geometric indices to identify the error of contouring results is limited, mainly because it does not consider any clinical background. To study the relationship between geometric indices and dosimetric indices, four different types of targets were selected to introduce the systematic and random geometric errors in the delineation process. Materials and Methods: The C-shaped target outlined in the American Association of Physicists in Medicine (AAPM) TG-119 report (The report of Task Group 119 of the AAPM) and the targets of three actual cases of oropharyngeal cancer, metastatic spine cancer, and prostate cancer were selected as the test contours that needed to be modified. Python software was used to perform translation, scaling, rotating and sine function transformation to introduce systematic and random errors into the above contours. These geometrically transformed contours were regarded as reference contours corrected by systematic and random errors. The corresponding dosimetric indices were obtained from the original dose distribution of the radiotherapy plan, and correlations (R²) between geometric and dosimetric indices were quantified through linear regression. The Wilcoxon signed rank test was used to compare the ability of spatial-direction discrimination between the geometric indices of different directions of transformations. Results: The correlations between the geometric and dosimetric indices were inconsistent for the targets. For systematic errors, except for the sine function transformation (R²: 0.023–0.04, p＞0.05), the geometric transformations of the C-shaped target’s planning target volume (C-PTV) had correlations with the dosimetric indices D98% and Dmean (R²: 0.689–0.988), 80% of which were strongly correlated (R² > 0.8). For the random errors, the correlation coefficients of the actual cases were also high, R2 > 0.384, p < 0.05. The results of Wilcoxon signed rank test showed that only the p-values of volumetric geometric indices of C-PTV were less than 0.05. Conclusions: Clinically, an assessment of the contour accuracy of the region of interest is not feasible based on geometric indices alone, and should be combined with dosimetric indices. Keywords: Contour evaluation, Geometric indices, Dosimetric indices, Geometric transformation