Visualization and evaluation of the quality variations of EBT4 Gafchromic film using multidimensional scaling and Lie derivative image analysis.

Film-specific uniformity variations in packages are known to significantly diminish the effectiveness of the one-scan protocol, a commonly used film dosimetry method. This method universally adopts the reference dose-response with rescaling linearly from the relationship of the known dose and the unexposed state. This study aims to visualize and quantify the variation in unexposed film-specific uniformity in a package to evaluate the suitability of the reference dose response using machine-learning method. Fourteen EBT4 films (#00-#13) were selected from two lot packages. Nine grid-spaced 100 × 100 pixel (72 dpi) patches were obtained from the color images of EBT4 film sheet using a single scanner with landscape (scan A) and portrait (scan B) scan orientations. The reference patch was set at the center of film #00. For this study, multidimensional scaling (MDS) and Lie derivative image analysis (LDIA) were applied to the patch data with respect to the red (R)/green (G)/blue (B) channels. MDS is a suitable method for analyzing non-linear data with similarity, which provides a map of data objects according to a distance metric. LDIA directly detects the deviation vector field between image gradients. The film-specific uniformity was measured at 1/10000 scaled pixel value as a scalar distribution. The image flow field was obtained as a negative gradient of the scalar distribution. Two similarity metrics were defined for comparison with the reference patch: (1) MDSr (the distance parameter in the MDS map from the origin) and (2) Stot (summed S-value in each patch, where S-value represents the vorticity of the deviation vector field obtained via the Lie derivative). MDSr highly correlated with the absolute pixel value difference from the reference patch except for the blue channel in which a favorable package was detected for the reference dose response. Stot quantified the film-uniformity variation from the reference, independent of the dataset, and detected the unfavorable film state as Stot < 0.8 in the blue channel. We visualized and quantified the variation in film-specific uniformity in a lot package using MDS and LDIA, thereby quantitatively determining the unfavorable condition for applying the reference dose-response.