Artificial Intelligence-Derived Biomechanical Index for Early Corneal Ectasia Detection: Advancing Beyond Tomography.
Hazem Abdelmotaal, Suphi Taneri, Ramin Salouti, M Hossein Nowroozzadeh, Ali H Al-Timemy, Alexandru Lavric, Mostafa El Habib Daho, Hidenori Takahashi, Rossen Mihaylov Hazarbassanov, Siamak Yousefi
Abstract
Open AccessPurpose: To develop and evaluate a novel artificial intelligence (AI)-derived metric for detection of early ectasia (E) by leveraging spatiotemporal biomechanical data derived from dynamic cornea videos only. Design: Multicenter cross-sectional case-control retrospective study. Participants: A total of 451 eyes from 451 patients from 2 centers with both Scheimpflug tomography and dynamic corneal deformation examinations. Methods: The training data set included 167 normal (N) patients with stable eyes postlaser vision correction, 83 NT eyes with VAE (VAE-NT), and better eyes from 64 patients with bilateral keratoconus (ie, mild KC [MKC]). The external validation data set included 68, 33, and 36 patients from the N, VAE-NT, and MKC groups, respectively. Extensive spatial and temporal pixel-level analysis of corneal displacement, stromal gray scale changes, and thickness variations from Corvis ST video frames was performed to identify a novel risk score with best detection of early E (combined VAE-NT and MKC). Findings were further validated using various approaches based on the external data set. Main Outcome Measures: Area under the receiver operating characteristics curve (AUC), accuracy, specificity, and sensitivity for detecting early E. Results: The novel AI-derived index achieved an AUC of 0.995 with accuracy, sensitivity, and specificity of 96%, 97%, and 96%, respectively, outperforming all Scheimpflug tomographic and dynamic deformation combined indices such as Belin/Ambrósio Enhanced Ectasia Display, Corvis Biomechanical Index (CBI), and Tomographic and Biomechanical Index (TBI). Conclusions: The AI-derived index based on spatiotemporal corneal biomechanical data outperformed existing instrument's topographic, tomographic, and biomechanical indices, in detecting E. This novel metric offers a clinically meaningful enhancement in early diagnosis and management of corneal E disease. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.