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John D. Rodriguez, Keith J. Lane, George W. Ousler, III, Endri Angjeli, Lisa M. Smith, Mark B. Abelson; Automated Grading System for Evaluation of Superficial Punctate Keratitis Associated With Dry Eye. Invest. Ophthalmol. Vis. Sci. 2015;56(4):2340-2347. doi: 10.1167/iovs.14-15318.
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© ARVO (1962-2015); The Authors (2016-present)
To develop an automated method of grading fluorescein staining that accurately reproduces the clinical grading system currently in use.
From the slit lamp photograph of the fluorescein-stained cornea, the region of interest was selected and punctate dot number calculated using software developed with the OpenCV computer vision library. Images (n = 229) were then divided into six incremental severity categories based on computed scores. The final selection of 54 photographs represented the full range of scores: nine images from each of six categories. These were then evaluated by three investigators using a clinical 0 to 4 corneal staining scale. Pearson correlations were calculated to compare investigator scores, and mean investigator and automated scores. Lin's Concordance Correlation Coefficients (CCC) and Bland-Altman plots were used to assess agreement between methods and between investigators.
Pearson's correlation between investigators was 0.914; mean CCC between investigators was 0.882. Bland-Altman analysis indicated that scores assessed by investigator 3 were significantly higher than those of investigators 1 and 2 (paired t-test). The predicted grade was calculated to be: Gpred = 1.48log(Ndots) − 0.206. The two-point Pearson's correlation coefficient between the methods was 0.927 (P < 0.0001). The CCC between predicted automated score Gpred and mean investigator score was 0.929, 95% confidence interval (0.884–0.957). Bland-Altman analysis did not indicate bias. The difference in SD between clinical and automated methods was 0.398.
An objective, automated analysis of corneal staining provides a quality assurance tool to be used to substantiate clinical grading of key corneal staining endpoints in multicentered clinical trials of dry eye.
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