Journal
PLOS ONE
Volume 14, Issue 8, Pages -Publisher
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0221707
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Categories
Funding
- European Union [709104]
- Fondation de l'Avenir pour la recherche medicale
- LabEx PALM
- Marie Curie Actions (MSCA) [709104] Funding Source: Marie Curie Actions (MSCA)
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Loss of corneal transparency, as occurs with various pathologies, infections, immune reactions, trauma, aging, and surgery, is a major cause of visual handicap worldwide. However, current means to assess corneal transparency are extremely limited and clinical and eye-bank practice usually involve a subjective and qualitative observation of opacities, sometimes with comparison against an arbitrary grading scale, by means of slit-lamp biomicroscopy. Here, we describe a novel objective optical data analysis-based method that enables quantifiable and standardized characterization of corneal transparency from depth-resolved corneal images, addressing the demand for such a means in both the laboratory and clinical ophthalmology setting. Our approach is based on a mathematical analysis of the acquired optical data with respect to the light attenuation from scattering processes in the corneal stroma. Applicable to any depth-resolved corneal imaging modality, it has been validated by means of full-field optical coherence tomographic microscopy (FF-OCT or FF-OCM). Specifically, our results on ex-vivo corneal specimens illustrate that 1) in homogeneous tissues, characterized by an exponential light attenuation with stromal depth (z), the computation of the scattering mean-free path (l(s)) from the rate of exponential decay allows quantification of the degree of transparency; 2) in heterogeneous tissues, identified by significant deviations from the normal exponential z -profile, a measure of exponential-decay model inadequacy (e.g., by computation of the Birge ratio) allows the estimation of severity of stromal heterogeneity, and the associated depth-dependent variations around the average l(s) enables precise localization of the pathology.
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