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Christopher L. Passaglia, Tia Arvaneh, Erin Greenberg, David Richards, Brian Madow; Automated Method of Grading Vitreous Haze in Patients With Uveitis for Clinical Trials. Trans. Vis. Sci. Tech. 2018;7(2):10. https://doi.org/10.1167/tvst.7.2.10.
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Uveitis is associated with accumulation of exudate in the vitreous, which reduces fundus visibility. The condition is assessed in patients by subjectively matching fundus photographs to a six-level (NIH) or nine-level (Miami) haze scale. This study aimed to develop an objective method of assessing vitreous haze.
An image-processing algorithm was designed that quantifies vitreous haze via high-pass filtering, entropy analysis, and power spectrum integration. The algorithm was refined using nine published photographs that represent incremental levels of fundus blur and applied without further refinement to 120 random fundus photographs from a uveitis image library. Computed scores were compared against the grades of two trained readers of vitreous haze and against acutance, a generic measure of image clarity, using Cohen's κ and Gwet's AC statistics.
Exact agreement between algorithm scores and reader grades was substantial for both NIH and Miami scales (κ = 0.61 and 0.67, AC = 0.82 and 0.92). Within-one (κ = 0.78 and 0.82) and within-two (κ = 0.80 and 0.84) levels of agreement were almost perfect. The correspondence was comparable to that between readers. Whereas, exact (κ = 0.45 and 0.44, AC = 0.73 and 0.75), within-one (κ = 0.69 and 0.68), and within-two (κ = 0.73 and 0.72) levels of agreement for the two scales were moderate to substantial for acutance calculations.
The computer algorithm produces a quantitative measure of vitreous haze that correlates strongly with the perception of expert graders.
The work offers a rapid, unbiased, standardized means of assessing vitreous haze for clinical and telemedical monitoring of uveitis patients.
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