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Original Investigation
June 2016

Expert Diagnosis of Plus Disease in Retinopathy of Prematurity From Computer-Based Image Analysis

Author Affiliations
  • 1Department of Ophthalmology, Casey Eye Institute, Oregon Health & Science University, Portland
  • 2Cognitive Systems Laboratory, Northeastern University, Boston, Massachusetts
  • 3Department of Computer Science, Universidade da Coruña, A Coruña, Spain
  • 4Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown
  • 5Department of Ophthalmology, Weill Cornell Medical College, New York, New York
  • 6Department of Ophthalmology, Ross Eye Institute, State University of New York at Buffalo
  • 7Department of Ophthalmology, Columbia University, New York, New York
  • 8Department of Ophthalmology, Sidra Medical and Research Center, Doha, Qatar
  • 9Retina Consultants, Chicago, Illinois
  • 10Wilmer Institute, Johns Hopkins University School of Medicine, Baltimore, Maryland
  • 11Long Island Vitreoretinal Consultants, Great Neck, New York
  • 12Associated Retinal Consultants, Oakland University, Royal Oak, Michigan
  • 13Asociacion para Evitar la Ceguera en Mexico, Mexico City, Mexico
  • 14Department of Ophthalmology and Visual Sciences, Illinois Eye and Ear Infirmary, University of Illinois at Chicago
  • 15Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland
JAMA Ophthalmol. 2016;134(6):651-657. doi:10.1001/jamaophthalmol.2016.0611

Importance  Published definitions of plus disease in retinopathy of prematurity (ROP) reference arterial tortuosity and venous dilation within the posterior pole based on a standard published photograph. One possible explanation for limited interexpert reliability for a diagnosis of plus disease is that experts deviate from the published definitions.

Objective  To identify vascular features used by experts for diagnosis of plus disease through quantitative image analysis.

Design, Setting, and Participants  A computer-based image analysis system (Imaging and Informatics in ROP [i-ROP]) was developed using a set of 77 digital fundus images, and the system was designed to classify images compared with a reference standard diagnosis (RSD). System performance was analyzed as a function of the field of view (circular crops with a radius of 1-6 disc diameters) and vessel subtype (arteries only, veins only, or all vessels). Routine ROP screening was conducted from June 29, 2011, to October 14, 2014, in neonatal intensive care units at 8 academic institutions, with a subset of 73 images independently classified by 11 ROP experts for validation. The RSD was compared with the majority diagnosis of experts.

Main Outcomes and Measures  The primary outcome measure was the percentage of accuracy of the i-ROP system classification of plus disease, with the RSD as a function of the field of view and vessel type. Secondary outcome measures included the accuracy of the 11 experts compared with the RSD.

Results  Accuracy of plus disease diagnosis by the i-ROP computer-based system was highest (95%; 95% CI, 94%-95%) when it incorporated vascular tortuosity from both arteries and veins and with the widest field of view (6–disc diameter radius). Accuracy was 90% or less when using only arterial tortuosity and 85% or less using a 2– to 3–disc diameter view similar to the standard published photograph. Diagnostic accuracy of the i-ROP system (95%) was comparable to that of 11 expert physicians (mean 87%, range 79%-99%).

Conclusions and Relevance  Experts in ROP appear to consider findings from beyond the posterior retina when diagnosing plus disease and consider tortuosity of both arteries and veins, in contrast with published definitions. It is feasible for a computer-based image analysis system to perform comparably with ROP experts, using manually segmented images.