May 2008
Volume 49, Issue 13
Free
ARVO Annual Meeting Abstract  |   May 2008
Plus Disease in Retinopathy of Prematurity: Generation of Representative Images by Quantification of Expert Opinion
Author Affiliations & Notes
  • M. F. Chiang
    Ophthalmology, Columbia University, New York, New York
  • R. Gelman
    Ophthalmology, Columbia University, New York, New York
  • S. L. Williams
    Ophthalmology, Columbia University, New York, New York
  • J.-Y. Lee
    Ophthalmology, Columbia University, New York, New York
    Ophthalmology, Hallym University Medical Center, Seoul, Republic of Korea
  • D. S. Casper
    Ophthalmology, Columbia University, New York, New York
  • M. E. Martinez-Perez
    Computer Science, National Autonomous University of Mexico, Mexico City, Mexico
  • J. T. Flynn
    Ophthalmology, Columbia University, New York, New York
  • Footnotes
    Commercial Relationships  M.F. Chiang, Unpaid member of the Scientific Advisory Board of Clarity Medical Systems (Pleasanton, CA), C; R. Gelman, None; S.L. Williams, None; J. Lee, None; D.S. Casper, None; M.E. Martinez-Perez, None; J.T. Flynn, None.
  • Footnotes
    Support  NIH Grant EY13972 (MFC), Research to Prevent Blindness Career Development Award (MFC), Starr Foundation (SLW), Doris Duke Charitable Foundation (SLW)
Investigative Ophthalmology & Visual Science May 2008, Vol.49, 5046. doi:https://doi.org/
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    • Get Citation

      M. F. Chiang, R. Gelman, S. L. Williams, J.-Y. Lee, D. S. Casper, M. E. Martinez-Perez, J. T. Flynn; Plus Disease in Retinopathy of Prematurity: Generation of Representative Images by Quantification of Expert Opinion. Invest. Ophthalmol. Vis. Sci. 2008;49(13):5046. doi: https://doi.org/.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose: : To demonstrate a methodology for generating representative wide-angle images of plus disease in retinopathy of prematurity (ROP), using quantitative analysis of expert opinions.

Methods: : 34 wide-angle retinal images were independently interpreted by 22 ROP experts as "plus" or "not plus." All images were processed by the computer-based Retinal Image multiScale Analysis (RISA) system to calculate two parameters: arteriolar integrated curvature (AIC) and venular diameter (VD). Using a reference standard defined by expert consensus, sensitivity and specificity curves were calculated by varying the diagnostic cutoffs for AIC and VD. Based on these curves, individual vessels from multiple images were identified with particular diagnostic cutoffs, and were combined using graphic editing software to form representative composite wide-angle retinal images.

Results: : The values associated with 75% under-diagnosis of true plus disease (i.e. 25% sensitivity cutoff) were AIC 0.061 and VD 4.272, the values associated with 50% under-diagnosis of true plus disease (i.e. 50% sensitivity cutoff) were AIC 0.049 and VD 4.088, and the values associated with 25% under-diagnosis of true plus disease (i.e. 75% sensitivity cutoff) were AIC 0.042 and VD 3.795. Representative wide-angle images were generated by identifying and combining individual vessels with these characteristics.

Conclusions: : Computer-based image analysis permits quantification of retinal vascular features, and a spectrum of abnormalities is seen in ROP. Selection of appropriate vessels from multiple images can produce representative plus disease images corresponding to expert opinions. This may be useful for educational purposes, and for development of future disease definitions based on quantitative, objective principles.

Keywords: retinopathy of prematurity • imaging/image analysis: clinical • retina 
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