April 2011
Volume 52, Issue 14
Free
ARVO Annual Meeting Abstract  |   April 2011
Evaluation Of Plus Disease Progression Using Digital Registration Of Multiple Images
Author Affiliations & Notes
  • Michael F. Chiang
    Ophthalmology and Medical Informatics, Oregon Health & Science University, Portland, Oregon
  • Jane S. Myung
    Ophthalmology, Weill-Cornell Medical Center, New York, New York
  • Rony Gelman
    Ophthalmology, Columbia University, New York, New York
  • Grant D. Aaker
    Ophthalmology, Weill Cornell Medical College, New York, New York
  • Nathan M. Radcliffe
    Ophthalmology, Weill Cornell Medical College, New York, New York
  • Robison V. Chan
    Ophthalmology, Weill Cornell Medical College, New York, New York
  • Footnotes
    Commercial Relationships  Michael F. Chiang, MFC is an unpaid member of the Scientific Advisory Board for Clarity Medical Systems (Pleasanton, CA) (C), National Institutes of Health grant EY19474 (MFC) (F); Jane S. Myung, None; Rony Gelman, None; Grant D. Aaker, None; Nathan M. Radcliffe, None; Robison V. Chan, St. Giles Foundation (RVPC) (F)
  • Footnotes
    Support  NIH Grant EY19494 (MFC), St. Giles Foundation (RVPC)
Investigative Ophthalmology & Visual Science April 2011, Vol.52, 3454. doi:
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      Michael F. Chiang, Jane S. Myung, Rony Gelman, Grant D. Aaker, Nathan M. Radcliffe, Robison V. Chan; Evaluation Of Plus Disease Progression Using Digital Registration Of Multiple Images. Invest. Ophthalmol. Vis. Sci. 2011;52(14):3454.

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

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Abstract

Purpose: : To determine whether review of dynamic flickering images, generated by digital registration of images from different time points, can improve accuracy and speed of detecting plus disease progression in retinopathy of prematurity (ROP) compared to the standard method of reviewing static side-by-side images.

Methods: : A set of 15 de-identified wide-angle retinal image pairs from infants who developed plus disease were uploaded to a secure study website. Image pairs representing plus disease progression were taken at least 1 week apart, and image pairs representing controls were taken on the same day. Dynamic flickering image pairs were obtained using digital registration software (EyeIC, Narberth, PA). Ten ROP experts independently reviewed each image pair on the study website, initially displayed as static side-by-side images and subsequently displayed as dynamic flickering pairs. Experts were asked to identify which image in each pair exhibited increased severity, or to state the images were identical. Speed of diagnosis was measured using a computer timestamp, and accuracy of detecting change in ROP severity was measured using examination date and ophthalmoscopic findings as a reference standard.

Results: : Diagnostic speed was significantly faster by by review of dynamic flickering image pairs (24.7±8.3 seconds) than by static side-by-side pairs (40.3±18.3 seconds) (p=0.002). For static side-by-side image pairs, experts made an accurate response in a mean (SD, %) of 11.4 (1.65, 76%) out of 15 image pairs. For dynamic flickering image pairs, experts made an accurate response in a mean (SD, %) of 11.3 (1.70, 75%) of 15 image pairs. There was no statistically significant difference in the accuracy of identifying plus disease progression between the two methods.

Conclusions: : Identification of plus disease progression was significantly faster by review of dynamic flickering image pairs than by review of standard static images, although there was no difference in accuracy. Dynamic flickering with digital registration may warrant further investigation as a diagnostic method for ROP progression.

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