Electron therapy, vital for treating skin lesions and superficial tumors, demands precise electron cutouts to ensure accurate dose delivery. Traditional manual tracing methods introduce uncertainties and inefficiencies, necessitating innovative solutions for custom block creation. To introduce and validate the Optical Automatic Contour Tracing (O-ACT) method, enhancing electron cutout generation's accuracy and efficiency through optical imaging and software automation. Utilizing a 3D-printed holder, a centrally-mounted charge-coupled device (CCD) camera on the electron applicator secured two distinct perspective images of the skin's contour at varying heights. Through image binarization and skeletonization, we identified the clinical target contour's region-of-interests (ROIs) in each setup image. Employing distances from each ROI's center, assessed at 5-degree intervals from both images, we reconstructed the target contour on the skin. The magnification factor, set at a 95cm source-to-point distance, determined the final cutout shape. We crafted an in-house software in MATLAB for camera calibration and image processing and juxtaposed our results against the standard clinical cutout from the treatment planning system (TPS) using a correlation coefficient based on masked binary images' mutual information. Additionally, we performed dosimetric evaluations using abstract shapes to compare O-ACT with other methods. Our methodology yielded cutout shapes exhibiting remarkable alignment with the TPS clinical cutout. O-ACT demonstrated superior precision in generating cutout shapes that closely align with the contours in TPS, improving upon other methods in terms of adaptability to patient body shapes and contour accuracy. Dosimetric evaluations showed minimal differences between methods, with O-ACT providing slightly more consistent results. Dose profile analyses in penumbra regions indicated O-ACT's improved accuracy compared to conventional methods. Pushing the boundaries of traditional practices, our O-ACT offers a more accurate, efficient, and reproducible method for custom electron cutout creation from clinical setup images. This innovation promises not only to streamline clinical workflow but also to potentially uplift clinical outcomes in radiation oncology by providing more accurate patient-specific treatment accessary.
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