Evidence map›Paper›PMID 27077667›Full record

ArticleJAMA ophthalmology2016

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

J Peter Campbell, Esra Ataer-Cansizoglu, Veronica Bolon-Canedo, Alican Bozkurt, Deniz Erdogmus, Jayashree Kalpathy-Cramer, Samir N Patel, James D Reynolds, Jason Horowitz, Kelly Hutcheson and 10 more

Abstract readMulticenter Study
In one paragraph

Article in JAMA ophthalmology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 69 papers.

0numbers the graph read from it
0cells of the map it votes in
69citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

69 citing papers in PubMed.

  1. Trial
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  11. Establishing an objective quantitative method for assessing the severity of plus disease in retinopathy of prematurity.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2025
    Article
  12. Review
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  17. Role of Artificial Intelligence in Retinal Diseases.Klinische Monatsblatter fur Augenheilkunde · 2024
    Review
  18. Article
  19. Article
  20. Review

9 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors.

J Peter CampbellDepartment of Ophthalmology, Casey Eye Institute, Oregon Health & Science University, Portland.
Esra Ataer-CansizogluCognitive Systems Laboratory, Northeastern University, Boston, Massachusetts.
Veronica Bolon-CanedoDepartment of Computer Science, Universidade da Coruña, A Coruña, Spain.
Alican BozkurtCognitive Systems Laboratory, Northeastern University, Boston, Massachusetts.
Deniz ErdogmusCognitive Systems Laboratory, Northeastern University, Boston, Massachusetts.
Jayashree Kalpathy-CramerAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown.
Samir N PatelDepartment of Ophthalmology, Weill Cornell Medical College, New York, New York.
James D ReynoldsDepartment of Ophthalmology, Ross Eye Institute, State University of New York at Buffalo.
Jason HorowitzDepartment of Ophthalmology, Columbia University, New York, New York.
Kelly HutchesonDepartment of Ophthalmology, Sidra Medical and Research Center, Doha, Qatar.
Michael ShapiroRetina Consultants, Chicago, Illinois.
Michael X RepkaWilmer Institute, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Phillip FerroneLong Island Vitreoretinal Consultants, Great Neck, New York.
Kimberly DrenserAssociated Retinal Consultants, Oakland University, Royal Oak, Michigan.
Maria Ana Martinez-CastellanosAsociacion para Evitar la Ceguera en Mexico, Mexico City, Mexico.
Susan OstmoDepartment of Ophthalmology, Casey Eye Institute, Oregon Health & Science University, Portland.
Karyn JonasDepartment of Ophthalmology and Visual Sciences, Illinois Eye and Ear Infirmary, University of Illinois at Chicago.
R V Paul ChanDepartment of Ophthalmology and Visual Sciences, Illinois Eye and Ear Infirmary, University of Illinois at Chicago.
Michael F ChiangDepartment of Ophthalmology, Casey Eye Institute, Oregon Health & Science University, Portland15Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland.
Imaging and Informatics in ROP (i-ROP) Research Consortium

Funding

Proteomics CoreP30EY010572 · NEI · OREGON HEALTH & SCIENCE UNIVERSITY · PI TED S ACOTT · 1995 to 2026
$19.4M
Clinical and Genetic Analysis of Retinopathy of PrematurityR01EY019474 · NEI · OREGON HEALTH & SCIENCE UNIVERSITY · PI CAMPBELL, JOHN PETER · 2010 to 2020
$7.0M
Translational Vision Science Research at Oregon Health & Science UniversityT32EY023211 · NEI · OREGON HEALTH & SCIENCE UNIVERSITY · PI Yali Jia, Kate E Keller · 2013 to 2026
$2.4M
Automated retinopathy of prematurity classification using machine learningR21EY022387 · NEI · MASSACHUSETTS GENERAL HOSPITAL · PI CHIANG, MICHAEL F., KALPATHY-CRAMER, JAYASHREE · 2013 to 2014
$482k
NEI NIH HHS P30 EY010572NEI NIH HHS R01 EY019474NEI NIH HHS R21 EY022387NEI NIH HHS T32 EY023211
6 · The paper itself

Abstract

importancePublished 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.

objectiveTo identify vascular features used by experts for diagnosis of plus disease through quantitative image analysis. DESIGN, SETTING, AND

participantsA 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.

resultsAccuracy 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.

Indexed as

Image Processing, Computer-AssistedArteriesDiagnosis, Computer-AssistedExpert SystemsHumansInfant, NewbornInfant, PrematureIntensive Care Units, NeonatalJoint InstabilityReproducibility of ResultsRetinal VesselsRetinopathy of PrematuritySkin Diseases, GeneticVascular Malformations

Identifiers

PMID27077667
PMCPMC5201139

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.