Kc App : A Novel Artificial Intelligence Based Application For Simplified Guidelines In Keratoconus Management
Published 2022 - 40th Congress of the ESCRS
Reference: FPT02.11 | Type: Free paper | DOI: 10.82333/m7bv-q894
Authors: Savitri Deval* 1 , Rohit Shetty 2 , Pooja Khamar 1 , Gairik Kundu 3
1CATARACT AND REFRACTIVE SURGERY,NARAYANA NETHRALAYA EYE HOSPITAL, BENGALURU, INDIA,BENGALURU,India, 2CATARACT, CORNEA AND REFRACTIVE SERVICES,NARAYANA NETHRALAYA EYE HOSPITAL, BENGALURU, INDIA,BENGALURU,India, 3CORNEA AND REFRACTIVE SERVICES,NARAYANA NETHRALAYA EYE HOSPITAL, BENGALURU, INDIA,BENGALURU,India
Purpose
To study the performance of AI based smart phone application in identifying keratoconus progressors and suggest an appropriate case based management.
Setting
Patients visiting Narayana Nethralaya, Bengaluru on a out-patient basis, who were diagnosed as having Keratocnus were shortlisted based on their scans and recruited in the study after obtaining well informed consent.
Methods
A total of 2500 scans of 200 eyes, having good quality were exported from Pentacam HR and were then classified as stable or progressors based on their Kmax values. Keratometry parameters, KC indices and Zernike wavefront aberrations of these eyes were then subsequently fed into the AI software. Machine learning was used to teach AI algorithm for various management options for keratoconus like Collagen Cross-linking, Intra-stromal Corneal Ring Segments (ICRS), Topography guided Custom Ablation Treatment (TCAT), Deep Lamellar Anterior Keratoplasty (DALK), Penetrating Keratoplasty (PK) and Femtosecond laser assisted Lamellar Keratoplasty. Progression and management derived data was then used to build a smart phone application.
Results
Random forest classifier - based AI model predicted the disease progression with area under the curve at 0.92, along with the sensitivity and specificity of 0.8 and 0.87 respectively. Sensitivity and specificity of the KC app in successfully identifying keratoconus progressors and suggesting a case appropriate treatment was 96.4 %.
Conclusions
KC app is the first ever AI based software for improving the predictability of keratoconus progression and deciding its management. It’s an excellent tool to sort, organize and display relevant information in a simple and accessible manner, serving as a one stop solution to clinical practitioners.