title: Assessing ocular bulbar redness: a comparison of methods.
abstract: OBJECTIVE
  We consider whether quantification of ocular bulbar redness, using image processing of relative Red-channel activity (Red-value), can be applied to a clinical sample and how this approach compares to an automated bulbar redness grading technique (Oculus Keratograph 5M, R-scan).
  
  
  METHODS
  Red-values from dry eye patients (n = 25) were determined using image processing of digital photographs over the nasal bulbar conjunctiva. Red-values were compared with subjective grades from six clinicians who graded the images using the IER scale. We considered the level of agreement between the Red-value and automated bulbar redness scores from the commercial instrument (R-scan). Scoring variability for each technique was assessed using the geometric coefficient of variation (gCoV, %). Agreement between techniques was considered with Bland-Altman analyses.
  
  
  RESULTS
  Red-values showed a strong linear relationship (R(2) = 0.99) to the R-scan. The Red-value had least variability (gCoV = 0.97%, 95% CI: 0.76-1.35%). The IER grade showed a linear relationship with Red-value (R(2) = 0.99), bound by a floor effect; it did not discriminate changes in redness below a threshold of 1.75 units (Red-value = 33.0%), after which it paralleled the redness returned by the R-scan. Intra-method variability for the redness returned by the R-scan (gCoV = 9.84%, 95% CI: 7.60-13.94%) and IER grades (gCoV = 7.30%, 95% CI: 1.73-10.31%) was similar (p > 0.05). Bland-Altman analysis showed the R-scan was consistently biased towards lower absolute redness scores than the IER.
  
  
  CONCLUSIONS
  Digital imaging processing, using relative Red-channel activity, was the least variable of the three techniques. The R-scan and IER showed similar intra-observer variability. The linear relationship between R-scan and Red-value suggests that the R-scan could be derived using similar methods.
authors.affiliation: Department of Optometry and Vision Sciences, University of Melbourne, Parkville, Australia.
authors.forename: Laura E
authors.initials: LE
authors.lastname: Downie
authors.affiliation: Department of Optometry and Vision Sciences, University of Melbourne, Parkville, Australia.
authors.forename: Peter R
authors.initials: PR
authors.lastname: Keller
authors.affiliation: Department of Optometry and Vision Sciences, University of Melbourne, Parkville, Australia.
authors.forename: Algis J
authors.initials: AJ
authors.lastname: Vingrys
mesh_terms: D000328:Adult; D000368:Aged; D003228:Conjunctiva / Q000473:pathology*; D003941:Diagnostic Techniques, Ophthalmological; D015352:Dry Eye Syndromes / Q000473:pathology*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D008875:Middle Aged; D015588:Observer Variation; D010781:Photography / Q000379:methods*; D012720:Severity of Illness Index; D055815:Young Adult
keywords: automated grading; bulbar redness; conjunctiva; dry eye; grading scale