April 2009
Volume 50, Issue 13
Free
ARVO Annual Meeting Abstract  |   April 2009
Predicting the Progression of ROP With Preplus
Author Affiliations & Notes
  • D. H. Ghodasra
    Division of Ophthalmology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
    University of Pennsylvania, Philadelphia, Pennsylvania
  • K. A. Karp
    Division of Ophthalmology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
  • G.-S. Ying
    University of Pennsylvania, Philadelphia, Pennsylvania
  • C. Wilson
    City University, London, United Kingdom
  • A. R. Fielder
    City University, London, United Kingdom
  • M. D. Mills
    Division of Ophthalmology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
    University of Pennsylvania, Philadelphia, Pennsylvania
  • G. E. Quinn
    Division of Ophthalmology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
    University of Pennsylvania, Philadelphia, Pennsylvania
  • Footnotes
    Commercial Relationships  D.H. Ghodasra, None; K.A. Karp, None; G.-S. Ying, None; C. Wilson, None; A.R. Fielder, None; M.D. Mills, None; G.E. Quinn, None.
  • Footnotes
    Support  Doris Duke Charitable Foundation
Investigative Ophthalmology & Visual Science April 2009, Vol.50, 3135. doi:
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      D. H. Ghodasra, K. A. Karp, G.-S. Ying, C. Wilson, A. R. Fielder, M. D. Mills, G. E. Quinn; Predicting the Progression of ROP With Preplus. Invest. Ophthalmol. Vis. Sci. 2009;50(13):3135.

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

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Abstract

Purpose: : To determine if digital image analysis of retinal vessel tortuosity and width discriminates which eyes with initial diagnosis of preplus retinopathy of prematurity (ROP) will progress to treatment.

Methods: : Posterior pole images of eyes at risk for ROP were obtained with a non-contact fundus camera (Nidek NM-200D). Retinal vessels from images at initial diagnosis of preplus or plus disease were analyzed with Computer-Aided Image Analysis of the Retina (CAIAR). ROP diagnoses were made independently of image acquisition following full ROP evaluation by expert pediatric ophthalmologists. Mean tortuosity and width for all vessels, arteries only, and veins only were compared across 4 groups: 1) eyes that did not develop ROP, 2) eyes that developed preplus ROP which regressed spontaneously, 3) eyes that developed preplus ROP which progressed to treatment, and 4) eyes that developed plus ROP without initial diagnosis of preplus.

Results: : Table 1Mean tortuosity for all vessels and arteries only increased across groups with severity of ROP. Among eyes with preplus ROP, mean width, tortuosity, and severity of peripheral disease (data not shown) at initial diagnosis were significantly lower in the group that regressed than the group that progressed, even though PMA was similar for both groups.

Conclusions: : Digital image analysis of retinal vessel tortuosity and width may be useful in predicting which eyes with preplus will progress to plus ROP requiring treatment. Since vascular abnormalities in ROP are a continuum and clinical diagnosis is subjective, quantitative measurement of retinal vessel tortuosity and width by image analysis algorithms like CAIAR may improve risk stratification of eyes with ROP.

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