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Title
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Corneal properties of keratoconus based on scheimpflug light intensity distribution
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Author
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Abstract
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| PURPOSE. We introduce a new approach to assess the properties of corneal microstructure in vivo of healthy control and keratoconus eyes, based on statistical modeling of light intensity distribution from Scheimpflug images. METHODS. Twenty participants (10 mild keratoconus and 10 control eyes) were included in this study. Corneal biomechanics was assessed with a commercial Scheimpflug camera technology. Sets of 140 images acquired per measurement were exported for further analysis. For each image, after corneal segmentation, the stromal pixel intensities were statistically modeled, leading to parametric time-series that characterizes distributional changes during the measurement. From those time series, a set of 10 newly introduced parameters (microscopic parameters) was derived to discriminate normal from keratoconic corneas and further compared against clinical parameters available from the same measuring device, including central corneal thickness, IOP, and deformation amplitude (macroscopic parameters). RESULTS. Biomechanical microscopic parameters extracted from statistical modeling of light intensity distribution were good discriminators between mild keratoconus and control eyes (Mann-Whitney U test, P < 0.05/N [Bonferroni]). The combination of available macroscopic and novel microscopic parameters was the most successful tool to differentiate between keratoconus and control eyes with no misclassifications. CONCLUSIONS. For the first time to our knowledge, a set of parameters related to corneal microstructure, acquired from statistical modeling of light intensity distribution of dynamic Scheimpflug image acquisition was introduced. This novel approach showed the potential of combining macroscopic and microscopic corneal properties derived from a single clinical device to discriminate successfully between mild keratoconus and control eyes. |
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Language
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English
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Source (journal)
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Investigative ophthalmology and visual science. - St. Louis, Mo.
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Publication
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St. Louis, Mo.
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2019
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ISSN
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0146-0404
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DOI
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10.1167/IOVS.19-26963
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Volume/pages
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60
:8
(2019)
, p. 3197-3203
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ISI
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000478827000017
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Pubmed ID
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31335945
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Full text (Publisher's DOI)
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Full text (open access)
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