Corneal infections are the leading cause of corneal blindness and the fifth leading cause of blindness worldwide. Despite this burden, developing better treatments has been difficult partly because doctors lack objective, precise ways to measure whether infections are improving or worsening. Traditional eye examinations rely heavily on subjective assessments that can vary between doctors and in some cases can miss important signs of disease altogether. These measurement challenges make it harder to determine whether new treatments actually work. Few new medications for corneal infections have been FDA-approved in recent decades.

Dr. Shekhawat leads METRIC (Measurement and Evaluation of Tomographic Risk in Corneal Infections), a research program using anterior segment optical coherence tomography (ASOCT) to develop quantitative imaging biomarkers (disease measurements) for corneal infections. His work evaluates whether ASOCT can objectively measure disease features that are difficult to characterize by traditional examination, ultimately improving our ability to measure disease severity, measure treatment response, and predict clinical outcomes.

This multidisciplinary work combines clinical epidemiology, quantitative analysis of longitudinal ASOCT imaging, and machine learning. Dr. Shekhawat’s group has used ASOCT to study corneal perforation, infiltrate depth and morphology, endothelial infectious and inflammatory lesions, and hypopyon, including direct comparisons with slit lamp examination. Ongoing work extends these approaches to automated lesion segmentation, textural analysis, three-dimensional volumetric reconstruction, and quantitative measurement of disease evolution over time. The long-term goal is to establish ASOCT as a quantitative biomarker platform for corneal infections, providing objective and reproducible measures of disease severity, prognosis, and treatment response to enable improved clinical care and therapeutic trials.