Detection of Keratoconus in Clinically and Algorithmically Topographically Normal Fellow Eyes Using Epithelial Thickness Analysis

利用上皮厚度分析检测临床和算法地形图正常的对侧眼中的圆锥角膜

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Abstract

PURPOSE: To assess the effectiveness of a keratoconus-detection algorithm derived from Artemis very high-frequency (VHF) digital ultrasound (ArcScan Inc., Morrison, CO) epithelial thickness maps in the fellow eye from a series of patients with unilateral keratoconus. METHODS: The study included 10 patients with moderate to advanced keratoconus in one eye but a clinically and algorithmically topographically normal fellow eye. VHF digital ultrasound epithelial thickness data were acquired and a previously developed classification model was applied for identification of keratoconus to the clinically normal fellow eyes. Pentacam (Oculus Optikgeräte, Wetzlar, Germany) Belin-Ambrósio Enhanced Ectasia Display "D" score (BAD-D) data (5 of 10 eyes), and Orbscan (Bausch & Lomb, Rochester, NY) SCORE data (9 of 10 eyes) were also evaluated. RESULTS: Five of the 10 fellow eyes were classified as keratoconic by the VHF digital ultrasound epithelium model. Five of 9 fellow eyes were classified as keratoconic by the SCORE model. For the 5 fellow eyes with Pentacam and VHF digital ultrasound data, one was classified as keratoconic by the VHF digital ultrasound model, one (different) eye by a combined VHF digital ultrasound and Pentacam model, and none by BAD-D alone. CONCLUSIONS: Under the assumption that keratoconus is a bilateral but asymmetric disease, half of the 'normal' fellow eyes could be found to have keratoconus using epithelial thickness maps. The Orbscan SCORE or the combination of topographic BAD-D criteria with epithelial maps did not perform better.

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