iLIGN - Artificial Intelligence Driven Strabismus Pre-Screening System

SUMMARY The overall goal of this project is to develop a rapid, non-invasive, accurate, and low-cost smartphone application (app), called iLIGN, to perform automated pre-screening using artificial intelligence for diagnosing ocular misalignment (Strabismus) by individuals without specialty expertise or training. Strabismus, commonly referred to as "crossed eyes" or "squint," is an ocular condition whereby the eyes are not properly aligned. The worldwide estimated prevalence in children is ~2%, being higher in underdeveloped countries (5.7%) than developed countries (1.3%). In adults, the lifetime risk of being diagnosed with new-onset strabismus is approximately 1-in-25 subjects. To prevent irreversible vision loss, it is critical to evaluate children of all populations for ocular alignment as early as possible. Poor academic performance, diminished workplace achievement, esthetic dissatisfaction, low self-esteem, delayed developmental milestones, and familial and societal low acceptance are well-known outcomes. Therefore, early diagnosis and therapy restores binocular vision, eliminates permanent vision loss, and lessens the need for repeated lifetime treatments. Once diagnosed, therapy can be as simple as prescribing glasses and covering the normal eye with a patch while the weaker eye improves, or for severe cases surgical correction and re-alignment. Even in developed nations, strabismus screening requires not only qualified healthcare professionals but also specialized devices. The American Academy of Pediatrics recommends a visual acuity screen for 4- and 5- year-olds and cooperative 3-year-olds. Traditional eye charts can detect visual impairments from ages 3 to 5 but with limitations. These are often tedious and result in inaccurate findings. Due to this reason, instrument-based screening can be utilized for children up until 5 years of age. The American Academy of Pediatrics and American Academy of Ophthalmology currently recommended photo-screening for children under 3 years old. All current methods require qualified healthcare personnel as operators. A mobile app is in development for strabismus screening but, again, for use only by trained technicians. Our solution will utilize AI models on current photos to identify strabismus without the requirement for specialists with specialized training. In Aim 1 we will develop an image capture protocol and data curation and in Aim 2 we will develop an automated image analysis software for deep learning-based strabismus diagnosis. iLIGN’s key innovation is in allowing untrained end-users with automated software assessment to diagnose and thereby prevent a condition which often geos undiagnosed without requisite specialty training and healthcare resources, and untreated carries enormous financial and societal impact. The expected outcome of this project is a software platform (smartphone app), iLIGN, a paradigm shift in the pre-screening of vision-threatening strabismus, which is a leading cause of preventable blindness in children and a major contributor to morbidity in adults.