Computational quantification of complex fundus phenotypes in age-related macular degeneration and Stargardt disease

Gwenole Quellec; Stephen R Russell; Todd E Scheetz; Edwin M Stone; Michael D Abràmoff

doi:10.1167/iovs.10-6232

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Computational quantification of complex fundus phenotypes in age-related macular degeneration and Stargardt disease

Journal article

Open access

Peer reviewed

Computational quantification of complex fundus phenotypes in age-related macular degeneration and Stargardt disease

Gwenole Quellec, Stephen R Russell, Todd E Scheetz, Edwin M Stone and Michael D Abràmoff

Investigative ophthalmology & visual science, Vol.52(6), pp.2976-2981

05/06/2011

DOI: 10.1167/iovs.10-6232

PMCID: PMC3109011

PMID: 21310908

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Abstract

To describe an automated method of quantification of specific fundus phenotypes and evaluate its performance in differentiating drusen, the hallmark lesions of age-related macular degeneration (AMD), from similar-looking bright lesions, the pisciform deposits or flecks typical of Stargardt disease (SD). Fundus macular images of 30 eyes of 30 subjects were studied. Fifteen subjects had a clinical diagnosis of AMD with at least 10 intermediate and/or 1 large drusen, and the other 15 had SD. As a test of bright-lesion separation, AMD and SD subjects were chosen from the heterogeneous phenotypes of each disorder, to be as visually similar as possible. Drusen and fleck properties were quantified from the color images by using an automated method, and a shape classifier was used to divide the images as characteristic of either AMD or SD. Image identification performance was quantified by using the area under the receiver operating characteristic curve (AUC). All SD subjects demonstrated at least one disease-associated variant of the ABCA4 gene. The method achieved an AUC of 0.936 for differentiating AMD from SD. Automated quantification of fundus phenotypes was achieved, and the results show that the method can differentiate AMD from SD, two distinctly different genetically associated disorders, by quantifying the properties of the bright lesions (drusen and flecks) in their fundus images, even when the images were visually selected to be similar. Quantification of fundus phenotypes may allow recognition of new phenotypes, correlation with new genotypes and may measure disease-specific biomarkers to improve management of patients with AMD or SD.

Computational Biology

Photography

Phenotype

Humans

Middle Aged

Image Interpretation, Computer-Assisted

Macular Degeneration - diagnosis

Retinal Drusen - diagnosis

ATP-Binding Cassette Transporters - genetics

Macular Degeneration - genetics

ROC Curve

Retrospective Studies

Fundus Oculi

Details

Title: Subtitle: Computational quantification of complex fundus phenotypes in age-related macular degeneration and Stargardt disease
Creators: Gwenole Quellec - Department of Ophthalmology and Visual Sciences, University of Iowa Hospitals and Clinics, Iowa City, Iowa, USA
Stephen R Russell
Todd E Scheetz
Edwin M Stone
Michael D Abràmoff
Resource Type: Journal article
Publication Details: Investigative ophthalmology & visual science, Vol.52(6), pp.2976-2981
DOI: 10.1167/iovs.10-6232
PMID: 21310908
PMCID: PMC3109011
NLM abbreviation: Invest Ophthalmol Vis Sci
ISSN: 0146-0404
eISSN: 1552-5783
Publisher: United States
Grant note: R01 EY017066 / NEI NIH HHS R01 EY016822 / NEI NIH HHS R01 EY011309 / NEI NIH HHS R01 EY16822 / NEI NIH HHS R01 EY11309 / NEI NIH HHS R01 EY016822-07 / NEI NIH HHS
Language: English
Date published: 05/06/2011
Academic Unit: Roy J. Carver Department of Biomedical Engineering; Electrical and Computer Engineering; Iowa Neuroscience Institute; Ophthalmology and Visual Sciences
Record Identifier: 9983806269802771

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