Bernardo T Lopes1, Isaac C Ramos2, Marcella Q Salomão3, Frederico P Guerra2, Steve C Schallhorn4, Julie M Schallhorn5, Riccardo Vinciguerra6, Paolo Vinciguerra7, Francis W Price8, Marianne O Price9, Dan Z Reinstein10, Timothy J Archer11, Michael W Belin12, Aydano P Machado13, Renato Ambrósio3. 1. Department of Ophthalmology of Federal University of São Paulo, São Paulo, Brazil; Rio de Janeiro Corneal Tomography and Biomechanical Study Group, Rio de Janeiro, Brazil; Instituto de Olhos Renato Ambrósio, Rio de Janeiro, Brazil; School of Engineering, University of Liverpool, Liverpool, United Kingdom. Electronic address: blopesmed@gmail.com. 2. Rio de Janeiro Corneal Tomography and Biomechanical Study Group, Rio de Janeiro, Brazil. 3. Department of Ophthalmology of Federal University of São Paulo, São Paulo, Brazil; Rio de Janeiro Corneal Tomography and Biomechanical Study Group, Rio de Janeiro, Brazil; Instituto de Olhos Renato Ambrósio, Rio de Janeiro, Brazil. 4. Department of Ophthalmology, University of California, San Francisco, San Francisco, California, USA; Optical Express, Glasgow, United Kingdom. 5. Department of Ophthalmology, University of California, San Francisco, San Francisco, California, USA; Optical Express, Glasgow, United Kingdom; F.I. Proctor Foundation, University of California, San Francisco, San Francisco, California, USA. 6. Department of Surgical Sciences, Division of Ophthalmology, University of Insubria, Varese, Italy; Department of Corneal and External Eye Diseases, St. Paul's Eye Unit, Royal Liverpool University Hospital, Liverpool, United Kingdom. 7. The Eye Center, Humanitas Clinical and Research Center, Rozzano, Italy; Vincieye Clinic, Milan, Italy. 8. Price Vision Group, Indianapolis, Indiana, USA. 9. Cornea Research Foundation of America, Indianapolis, Indiana, USA. 10. London Vision Clinic, London, United Kingdom; Department of Ophthalmology, Columbia University Medical Center, New York, New York, USA; Centre Hospitalier National d'Ophtalmologie, Paris, France; Biomedical Science Research Institute, Ulster University, Coleraine, United Kingdom. 11. London Vision Clinic, London, United Kingdom. 12. Department of Ophthalmology and Visual Science, College of Medicine, The University of Arizona, Tucson, Arizona, USA; and Institute of Computing of Federal University of Alagoas, Maceió, Brazil. 13. Department of Ophthalmology of Federal University of São Paulo, São Paulo, Brazil.
Abstract
PURPOSE: To improve the detection of corneal ectasia susceptibility using tomographic data. DESIGN: Multicenter case-control study. METHODS: Data from patients from 5 different clinics from South America, the United States, and Europe were evaluated. Artificial intelligence (AI) models were generated using Pentacam HR (Oculus, Wetzlar, Germany) parameters to discriminate the preoperative data of 3 groups: stable laser-assisted in situ keratomileusis (LASIK) cases (2980 patients with minimum follow-up of 7 years), ectasia susceptibility (71 eyes of 45 patients that developed post-LASIK ectasia [PLE]), and clinical keratoconus (KC; 182 patients). Model accuracy was independently tested in a different set of stable LASIK cases (298 patients with minimum follow-up of 4 years) and in 188 unoperated patients with very asymmetric ectasia (VAE); these patients presented normal topography (VAE-NT) in 1 eye and clinically diagnosed ectasia in the other (VAE-E). Accuracy was evaluated with ROC curves. RESULTS: The random forest (RF) provided highest accuracy among AI models in this sample with 100% sensitivity for clinical ectasia (KC+VAE-E; cutoff 0.52), being named Pentacam Random Forest Index (PRFI). Considering all cases, the PRFI had an area under the curve (AUC) of 0.992 (94.2% sensitivity, 98.8% specificity; cutoff 0.216), being statistically higher than the Belin/Ambrósio deviation (BAD-D; AUC = 0.960, 87.3% sensitivity, 97.5% specificity; P = .006, DeLong's test). The optimized cutoff of 0.125 provided sensitivity of 85.2% for VAE-NT and 80% for PLE, with 96.6% specificity. CONCLUSION: The PRFI enhances ectasia diagnosis. Further integrations with corneal biomechanical parameters and with the corneal impact from laser vision correction are needed for assessing ectasia risk.
PURPOSE: To improve the detection of corneal ectasia susceptibility using tomographic data. DESIGN: Multicenter case-control study. METHODS: Data from patients from 5 different clinics from South America, the United States, and Europe were evaluated. Artificial intelligence (AI) models were generated using Pentacam HR (Oculus, Wetzlar, Germany) parameters to discriminate the preoperative data of 3 groups: stable laser-assisted in situ keratomileusis (LASIK) cases (2980 patients with minimum follow-up of 7 years), ectasia susceptibility (71 eyes of 45 patients that developed post-LASIK ectasia [PLE]), and clinical keratoconus (KC; 182 patients). Model accuracy was independently tested in a different set of stable LASIK cases (298 patients with minimum follow-up of 4 years) and in 188 unoperated patients with very asymmetric ectasia (VAE); these patients presented normal topography (VAE-NT) in 1 eye and clinically diagnosed ectasia in the other (VAE-E). Accuracy was evaluated with ROC curves. RESULTS: The random forest (RF) provided highest accuracy among AI models in this sample with 100% sensitivity for clinical ectasia (KC+VAE-E; cutoff 0.52), being named Pentacam Random Forest Index (PRFI). Considering all cases, the PRFI had an area under the curve (AUC) of 0.992 (94.2% sensitivity, 98.8% specificity; cutoff 0.216), being statistically higher than the Belin/Ambrósio deviation (BAD-D; AUC = 0.960, 87.3% sensitivity, 97.5% specificity; P = .006, DeLong's test). The optimized cutoff of 0.125 provided sensitivity of 85.2% for VAE-NT and 80% for PLE, with 96.6% specificity. CONCLUSION: The PRFI enhances ectasia diagnosis. Further integrations with corneal biomechanical parameters and with the corneal impact from laser vision correction are needed for assessing ectasia risk.
Authors: Cristina Ariadna Nicula; Adriana Elena Bulboacă; Dorin Nicula; Ariadna Patricia Nicula; Karin Ursula Horvath; Sorana D Bolboacă Journal: Front Med (Lausanne) Date: 2022-05-26
Authors: Mahsaw N Motlagh; Majid Moshirfar; Michael S Murri; David F Skanchy; Hamed Momeni-Moghaddam; Yasmyne C Ronquillo; Phillip C Hoopes Journal: Med Hypothesis Discov Innov Ophthalmol Date: 2019
Authors: Marcella Q Salomão; Ana Luisa Hofling-Lima; Louise Pellegrino Gomes Esporcatte; Bernardo Lopes; Riccardo Vinciguerra; Paolo Vinciguerra; Jens Bühren; Nelson Sena; Guilherme Simões Luz Hilgert; Renato Ambrósio Journal: Int J Environ Res Public Health Date: 2020-03-23 Impact factor: 3.390