Advances in diagnostic techniques for early keratoconus
Keratoconus is a leading cause of corneal blindness worldwide.Early diagnosis is challenging due to the lack of typical symptoms,often resulting in delayed treatment and severe disease progression necessitating corneal transplantation.The scarcity of corneal donors in China further complicates patient outcomes.Recent advancements in ophthalmic devices,such as corneal topography,corneal biomechanics,optical coherence tomography(OCT)of the anterior segment,and corneal confocal microscopy(CCM),along with artificial intelligence(AI)technologies,have significantly improved the efficiency of early keratoconus diagnosis.These diagnostic tools provide comprehensive corneal parameters including morphology,biomechanics,corneal thickness,and cell structures.AI can integrate these parameters to assist in the efficient diagnosis of early keratoconus,demonstrating high clinical utility.Early diagnostic techniques for keratoconus offer crucial insights for timely intervention and treatment,aiding in the preservation of patient vision.
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