Renato Ambrósio, Aydano P Machado, Edileuza Leão, João Marcelo G Lyra, Marcella Q Salomão, Louise G Pellegrino Esporcatte, João B R da Fonseca Filho, Erica Ferreira-Meneses, Nelson B Sena, Jorge S Haddad, Alexandre Costa Neto, Gildasio Castelo de Almeida, Cynthia J Roberts, Ahmed Elsheikh, Riccardo Vinciguerra, Paolo Vinciguerra, Jens Bühren, Thomas Kohnen, Guy M Kezirian, Farhad Hafezi, Nikki L Hafezi, Emilio A Torres-Netto, Nanji Lu, David Sung Yong Kang, Omid Kermani, Shizuka Koh, Prema Padmanabhan, Suphi Taneri, William Trattler, Luca Gualdi, José Salgado-Borges, Fernando Faria-Correia, Elias Flockerzi, Berthold Seitz, Vishal Jhanji, Tommy C Y Chan, Pedro Manuel Baptista, Dan Z Reinstein, Timothy J Archer, Karolinne M Rocha, George O Waring, Ronald R Krueger, William J Dupps, Ramin Khoramnia, Hassan Hashemi, Soheila Asgari, Hamed Momeni-Moghaddam, Siamak Zarei-Ghanavati, Rohit Shetty, Pooja Khamar, Michael W Belin, Bernardo T Lopes
PURPOSE: To optimize artificial intelligence (AI) algorithms to integrate Scheimpflug-based corneal tomography and biomechanics to enhance ectasia detection. DESIGN: Multicenter cross-sectional case-control retrospective study. METHODS: A total of 3886 unoperated eyes from 3412 patients had Pentacam and Corvis ST (Oculus Optikgeräte GmbH) examinations. The database included 1 eye randomly selected from 1680 normal patients (N) and from 1181 "bilateral" keratoconus (KC) patients, along with 551 normal topography eyes from patients with very asymmetric ectasia (VAE-NT), and their 474 unoperated ectatic (VAE-E) eyes...
July 2023: American Journal of Ophthalmology