title: Quantification of fundus autofluorescence to detect disease severity in nonexudative age-related macular degeneration.
abstract: OBJECTIVE
  Accurate assessment of disease burden and determination of disease progression are challenging in dry age-related macular degeneration (AMD). We assessed the utility of quantified fundus autofluorescence in (FAF) the evaluation and follow-up of dry AMD.
  
  
  OBJECTIVE
  To develop a method for quantitative FAF image analysis that is capable of stratifying severity of nonexudative AMD.
  
  
  METHODS
  A retrospective analysis from 2008 to 2012 at a university eye center of FAF images taken of normal and nonexudative AMD eyes compared the Index of Retinal Autofluorescence (IRA) with retinal specialists' clinical rankings of FAF images and the Age-Related Eye Disease Study (AREDS) grading scheme of corresponding color fundus photographs.
  
  
  METHODS
  Digital files of Heidelberg Spectralis FAF images taken of normal and nonexudative AMD eyes were analyzed. For each image, a unique horizontally oriented FAF signature composed of vertically averaged gray-scale values was generated through the fovea. A pairwise comparison of 2 signatures was performed using a modified difference of squares method, which generated a single quantitative value, the IRA.
  
  
  METHODS
  The effects of intersession testing, cataract extraction, pupillary dilation, focal plane, and gain settings on the IRA were assessed.
  
  
  RESULTS
  The FAF images taken of the same subjects at different times demonstrated low intersession variability of the IRA (intraclass coefficient = 0.75; 95% CI, 0.45-0.92). The IRA was affected by cataract severity, cataract extraction, small pupillary diameters (<5.5 mm), defocusing, and excessive high or low camera gain. The IRA values correlated with both subjective clinical rankings by retinal specialists (r(s) = 0.77). The IRA was positively correlated with AREDS score (r(s) = 0.73) and could statistically distinguish AREDS grades 3 and 4 (P < .001). Serial imaging demonstrated the utility of the method for identifying clinically meaningful disease progression.
  
  
  CONCLUSIONS
  The IRA method applied to FAF digital files can quantify AMD disease severity and may be helpful in identifying AMD progression.
authors.affiliation: Department of Ophthalmology and Visual Sciences, Kellogg Eye Center, University of Michigan, Ann Arbor, Michigan 48105, USA.
authors.forename: Ira H
authors.initials: IH
authors.lastname: Schachar
authors.forename: Sarwar
authors.initials: S
authors.lastname: Zahid
authors.forename: Grant M
authors.initials: GM
authors.lastname: Comer
authors.forename: Maxwell
authors.initials: M
authors.lastname: Stem
authors.forename: Asa G
authors.initials: AG
authors.lastname: Schachar
authors.forename: Stephen J
authors.initials: SJ
authors.lastname: Saxe
authors.forename: Thomas W
authors.initials: TW
authors.lastname: Gardner
authors.forename: Victor M
authors.initials: VM
authors.lastname: Elner
authors.forename: Thiran
authors.initials: T
authors.lastname: Jayasundera
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D002387:Cataract Extraction; D015350:Contrast Sensitivity; D018450:Disease Progression; D005260:Female; D005451:Fluorescein Angiography; D005500:Follow-Up Studies; D005654:Fundus Oculi; D057092:Geographic Atrophy / Q000175:diagnosis*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D019654:Lens Implantation, Intraocular; D008297:Male; D008875:Middle Aged; D011680:Pupil / Q000502:physiology; D012189:Retrospective Studies; D012720:Severity of Illness Index