June 2015
Volume 56, Issue 7
Free
ARVO Annual Meeting Abstract  |   June 2015
Evaluation of a Smart Phone-Based Ocular Imaging System for the Assessment of Conjunctival Hyperemia
Author Affiliations & Notes
  • Peter Corcoran
    Dry Eye, R & D, Ora, Inc., Andover, MA
  • Richard Abelson
    Statistics and Data Corporation, Tempe, AZ
  • Keith Jeffrey Lane
    R & D, Ora, Inc., Andover, AZ
  • Endri Angjeli
    R & D, Ora, Inc., Andover, AZ
  • George W Ousler
    Dry Eye, R & D, Ora, Inc., Andover, MA
  • Paul J Gomes
    Allergy, Ora, Inc., Andover, MA
  • Footnotes
    Commercial Relationships Peter Corcoran, Ora, Inc. (E); Richard Abelson, SDC, Inc. (E); Keith Lane, Ora, Inc. (E); Endri Angjeli, Ora, Inc. (E); George Ousler, Ora, Inc. (E); Paul Gomes, Ora, Inc. (E)
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2015, Vol.56, 3045. doi:
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      Peter Corcoran, Richard Abelson, Keith Jeffrey Lane, Endri Angjeli, George W Ousler, Paul J Gomes; Evaluation of a Smart Phone-Based Ocular Imaging System for the Assessment of Conjunctival Hyperemia. Invest. Ophthalmol. Vis. Sci. 2015;56(7 ):3045.

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

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Abstract

Purpose: Conjunctival hyperemia can vary greatly based on the external environment, time of day, and intermittent nature of ocular surface diseases. In-office slit lamp examinations are the gold standard for evaluation of conjunctival hyperemia, but are infrequent snap shots that do not provide a global assessment of redness severity and duration, especially in the context of evaluating drug efficacy and duration of effect. We developed and tested a smart-phone based image capture system that the subject can carry out independently to capture conjunctival redness away from the clinician’s office.

Methods: An ocular imaging device and instructional software application were developed for a Samsung Galaxy S5 smart phone. Twenty images from 10 eyes were evaluated in this proof-of-concept study. Healthy volunteers self-captured images of both eyes using the smart phone system. A trained clinician then graded the severity of ocular hyperemia (0-4 scale) in these subjects at the slit lamp. All images were graded manually by trained investigators, and automatically, using a validated automated computer program1. Pearson’s Correlations were calculated between live grading and images graded by the clinician, and between live grading and images graded automatically.

Results: Previous results1 demonstrated that inter-investigator correlations of manual image grading varied between 0.68<r<0.83 (mean r=0.77; N=99 images). In this study, correlation between live grading at the slit lamp and manual image grading was r=0.76. Correlation between live grading and automatic grading of images was r=0.65.<br /> <br /> 1 Rodriguez JD, Johnston PR, Ousler GW, Smith LM, Abelson MB. Automated grading system for evaluation of ocular redness associated with dry eye Clinical Ophthalmology 2013:7 1-8.

Conclusions: These results indicate that a smart phone-based imaging system, with subsequent automated or clinical grading of redness, correlates well to live-doctor assessments. This novel device provides subject-captured data as yet never collected in real-time environmental assessments of conjunctival hyperemia, and such a tool might prove valuable in the evaluation of drugs that modify redness, or as an adjunct to cell-phone based clinical trial diary platforms.

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