Semiautomatic Segmentation of Rim Area Focal Hyperautofluorescence Predicts Progression of Geographic Atrophy Due to Dry Age-Related Macular Degeneration.

Journal Article (Journal Article)

PURPOSE: To develop image analysis software usable by nonexpert graders to segment geographic atrophy (GA) from dry AMD and to quantify rim area focal hyperautofluorescence (RAFH) surrounding GA on fundus autofluorescence (FAF) images. To compare the GA progression predictions based on RAFH with those of a validated qualitative classification system. METHODS: Retrospective analysis of serial FAF images from 49 eyes of 30 subjects with GA was performed using MATLAB-based software (MathWorks, Natick, MA, USA). Correlation between RAFH and progression of GA was analyzed using Spearman correlation. Comparisons of lesion growth rate between RAFH tertiles used generalized estimating equations and Kruskal-Wallis testing. Interobserver variability in lesion size, growth rate and RAFH were compared between two expert and one nonexpert grader using Bland-Altman statistics. RESULTS: Rim area focal hyperautofluorescence was positively correlated with GA progression rate (ρ = 0.49, P < 0.001). Subjects in the middle or highest RAFH tertile were at greater risk of progression (P = 0.005 and P = 0.001, respectively). Mean difference in RAFH was 0.012 between expert and -0.005 to 0.017 between expert and nonexperts. Mean difference in lesion size (mm2) was 0.11 between expert and -0.29 to 0.41 between expert and nonexperts. Mean difference in lesion growth rate (mm2/mo) was 0.0098 between expert and -0.027 to 0.037 between expert and nonexperts. Risk stratification based on RAFH tertile was 96% identical across all graders. CONCLUSIONS: Our semiautomated image analysis software facilitates stratification of progression risk based on RAFH and enabled a nonexpert grader with minimal training to obtain results comparable to expert graders. Predictions based on RAFH were similar to those of a validated qualitative classification system.

Full Text

Duke Authors

Cited Authors

  • Allingham, MJ; Nie, Q; Lad, EM; Izatt, DJ; Mettu, PS; Cousins, SW; Farsiu, S

Published Date

  • April 1, 2016

Published In

Volume / Issue

  • 57 / 4

Start / End Page

  • 2283 - 2289

PubMed ID

  • 27127926

Pubmed Central ID

  • PMC5221410

Electronic International Standard Serial Number (EISSN)

  • 1552-5783

Digital Object Identifier (DOI)

  • 10.1167/iovs.15-19008


  • eng

Conference Location

  • United States