Ophtalmological device with artificial intelligence for early detection of keratoconus using corneal measurements, Plácido Topografia and Scheimpflug Tomography

• Grant number: 19/15216-5
• Support Opportunities: Research Grants - Innovative Research in Small Business - PIPE
• Start date: September 01, 2021
• End date: August 31, 2024
• Field of knowledge: Engineering - Biomedical Engineering - Medical Engineering
• Principal Investigator: André Orlandi de Oliveira
• Grantee: André Orlandi de Oliveira
• Company: JTAG Peças e Equipamentos Médicos Ltda
• CNAE: Fabricação de aparelhos eletromédicos e eletroterapêuticos e equipamentos de irradiação
• City: São Carlos
• Associated researchers: Felipe Marques de Carvalho Taguchi ; Jarbas Caiado de Castro Neto ; Odemir Martinez Bruno ; Rogério Ferreira de Barros ; Silvio Antonio Tonissi Júnior ; Wallace Chamon Alves de Siqueira
• Associated scholarship(s): 22/09907-8 - Ophtalmological device with Artificial Intelligence for early detection of keratoconus using corneal measurements, Plácido Topografia and Scheimpflug Tomography, BP.TT; 22/00525-5 - Ophtalmological device with artificial intelligence for early detection of Keratoconus using corneal measurements, plácido topografia and Scheimpflug tomography, BP.PIPE

Abstract

The detection of mild or subclinical forms of ectatic corneal diseases has gained relevance because these cases are at high risk for developing iatrogenic progressive ectasia (keratectasia) after corneal laser vision correction. Likewise, with the growing interest in corneal cross-linking (CXL), the detection of mild ectasia and monitoring disease progression have become of utmost importance. Therefore, in parallel to advancing in the disease treatment, we must develop technologies capable of helping professionals to diagnose more precisely, reaching high successes rates in treatment procedures. Although some devices give many measurements of the eye, the early diagnosis of keratoconus demands high experience and accuracy of the healthy professional, since this disease may be asymptomatic and hard to identify. Thus, the main objective of this project is to use computer vision to enhance the diagnosis of these diseases, specially in subclinical stages. First, we will develop a device that provides an overall view of the anterior eye segment using Placido rings and Scheimpflug tomography. In conjunction with computer vision, this device will be capable of detect early ectasia with high sensitivity and specificity. As the Eyetec company already has a Placido corneal topographer, the Scheimpflug module will be added to it, using a new technique to reduce production cost. In addition, a tear film analyzer will be developed to enhance the usability of this innovative device. Finally, at the end of the project, a complete and robust equipment is expected for the detection of corneal-related diseases. (AU)