Background/aims: Endoscopic ultrasonography (EUS) is a strongly operator-dependent method. Mathematical algorithms in image-analysis are likely to enhance diagnostic accuracy. Incomplete eradication of esophageal varices can be demonstrated with EUS. The presence of paraesophageal varices, visible only with EUS, has been recently identified as a predictor of recurrence. The object of this study was to evaluate the usefulness of fractal-geometry-algorithms for the interpretation of EUS images and their impact on treatment decisions.
Methodology: EUS was performed in 5 consecutive patients in order to detect the presence of paraesophageal varices after complete eradication of esophageal varices with elastic banding. Static images were analyzed and the fractal dimension was calculated. Follow-up ranged from 8-12 months.
Results: Fractal dimension was related to a) the presence and size of paraesophageal varices b) Child-Pugh Score c) rebleeding rate. Patients with a fractal dimension > 1.5 rebled.
Conclusions: The use of mathematical algorithms derived from fractal geometry enhances interpretation in endosonographic imaging, increases the diagnostic yield and may prove helpful in making individual-tailored treatment decisions.