Clinical Impact of Using Real-Time Image-Processing Algorithms (Comb Removal and Image Sharpening) in...

Background/Objectives: Lacrimal passage intubation is commonly used to treat lacrimal duct obstruction. However, conventional dacryoendoscopes, which are limited by their low resolution and comb-structure artifacts, pose challenges for visualization. Two novel image processing algorithms-comb removal and image sharpening-have been developed to enhance visibility, and this study aimed to evaluate the clinical effects of these algorithms on the outcomes of dacryoendoscopic surgery. Methods: A retrospective study was conducted on 121 sides of 84 patients (mean age, 72.3 ± 10.5 years) who had undergone lacrimal passage intubation. The patients were categorized into comb-removal and image-sharpening groups according to the algorithm used during the procedure. The clinical parameters of pain score, endoscopy duration, irrigation fluid volume, and irrigation fluid flow rate were compared between the groups using the linear mixed-effects model, and recurrence rates were evaluated using Kaplan-Meier analysis. Results: The image-sharpening algorithm was associated with a significant reduction in irrigation fluid usage (β = -1.34 mL, SE = 0.52, p = 0.012), with the pain score (β = -1.71, SE = 0.93, p = 0.069) and endoscopy duration (β = -0.50 min, SE = 0.39, p = 0.199) also showing reduction trends, but these did not reach statistical significance. The comb-removal algorithm showed no significant associations with any evaluated outcome. Recurrence rates were similar between the groups. Conclusions: Real-time image sharpening was associated with improved procedural efficiency during dacryoendoscopic surgery, while clinical outcomes showed favorable trends that did not reach statistical significance. These findings suggest a potential supportive role of these algorithms in intraoperative handling; however, whether this translates into clinically meaningful benefits requires further investigation.