A structural view of a disease that often hides in plain sight
Keratoconus is one of the eye conditions clinicians most want to catch early and often struggle to confirm early. In its initial stages, the cornea can still look broadly normal on routine examination even as the tissue is beginning to lose strength. That gap matters because patients being evaluated for refractive surgery may appear eligible until subtle disease is uncovered too late.
A new study highlighted by SPIE and published in Biophotonics Discovery argues that the answer may lie in looking beyond corneal shape alone. The research combined polarization-sensitive optical coherence tomography, or PS-OCT, with artificial intelligence to identify structural changes inside the cornea that conventional imaging can miss when disease is still subclinical.
Why current screening tools miss early cases
Today’s mainstream screening systems, including tools that map corneal curvature and thickness, are effective once keratoconus is established. They measure the overall geometry of the cornea and can flag steepening, thinning, and surface irregularities. The problem is that these are often late-emerging signs. In the earliest phase, the tissue may not yet be visibly deformed even though the underlying collagen framework is already changing.
That creates a familiar diagnostic dilemma. Some patients have naturally thin corneas but no disease, while others have early biomechanical disruption that shape-based scans do not confidently separate from normal variation. The researchers set out to tackle that distinction directly by measuring tissue organization rather than relying on thickness alone.
