Dr.Pallak Kusumgar, Dr.Rohit Shetty
Defining disease progression and the threshold for surgical intervention in keratoconus patients remains a challenge.
We present a novel Artificial intelligence (AI) approach to estimate growth of the degraded zone in progressive keratoconus. 3D AI based model was used to calculate shape and size of the degenerate zone to design concentric treatment zones and differential energy. The delivered energy varied from 15 at the center to 3 J/cm2 at the periphery. 20 eyes were treated using AI model and refractive and keratometric data was measured pre and post surgery. Mean MRSE, flat and steep axis K values, mean and maximum keratometry were lowered 3 months after surgery. Reduction in root mean square (RMS) of lower, higher order and total aberration with normalization of spherical aberrations was seen 3 months after procedure. AI based crosslinking shows favorable refractive, keratometric and biomechanical outcomes with acceptable safety profile with no significant endothelial damage.
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