September 2016
Volume 57, Issue 12
Open Access
ARVO Annual Meeting Abstract  |   September 2016
Subtle Early Changes in Diabetic Retinas Revealed by a Novel Method that Automatically Quantifies Spectral Domain Optical Coherence Tomography (SD-OCT) Images
Author Affiliations & Notes
  • Shlomit Schaal
    Department of Ophthalmology and Visual Sciences, University of Louisville School of Medicine, Louisville, Kentucky, United States
  • Marwa Ismail
    Department of Bioengineering, University of Louisville, Louisville, Kentucky, United States
  • Agustina C Palacio
    Department of Ophthalmology and Visual Sciences, University of Louisville School of Medicine, Louisville, Kentucky, United States
  • Ahmed ElTanboly
    Department of Bioengineering, University of Louisville, Louisville, Kentucky, United States
  • Andy Switala
    Department of Bioengineering, University of Louisville, Louisville, Kentucky, United States
  • Ahmed Soliman
    Department of Bioengineering, University of Louisville, Louisville, Kentucky, United States
  • Thomas Neyer
    Department of Ophthalmology and Visual Sciences, University of Louisville School of Medicine, Louisville, Kentucky, United States
  • Amir Hajrasouliha
    Department of Ophthalmology and Visual Sciences, University of Louisville School of Medicine, Louisville, Kentucky, United States
  • Amir Hadayer
    Department of Ophthalmology and Visual Sciences, University of Louisville School of Medicine, Louisville, Kentucky, United States
  • Douglas Kenneth Sigford
    Department of Ophthalmology and Visual Sciences, University of Louisville School of Medicine, Louisville, Kentucky, United States
  • Ayman El-Baz
    Department of Bioengineering, University of Louisville, Louisville, Kentucky, United States
  • Footnotes
    Commercial Relationships   Shlomit Schaal, University of Louisville (P); Marwa Ismail, None; Agustina Palacio, None; Ahmed ElTanboly, None; Andy Switala, None; Ahmed Soliman, None; Thomas Neyer, None; Amir Hajrasouliha, University of Louisville (P); Amir Hadayer, None; Douglas Sigford, None; Ayman El-Baz, University of Louisville (P)
  • Footnotes
    Support  This project is supported by the Coulter Translational Partnership Grant (Schaal, El-Baz 2015), and by an unrestricted institutional grant from Research to Prevent Blindness (RPB). This project was supported by Zeiss in the means of Zeiss Cirrus HD-OCT 5000 machine loan to the University of Louisville.
Investigative Ophthalmology & Visual Science September 2016, Vol.57, 6324. doi:
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    • Get Citation

      Shlomit Schaal, Marwa Ismail, Agustina C Palacio, Ahmed ElTanboly, Andy Switala, Ahmed Soliman, Thomas Neyer, Amir Hajrasouliha, Amir Hadayer, Douglas Kenneth Sigford, Ayman El-Baz; Subtle Early Changes in Diabetic Retinas Revealed by a Novel Method that Automatically Quantifies Spectral Domain Optical Coherence Tomography (SD-OCT) Images. Invest. Ophthalmol. Vis. Sci. 2016;57(12):6324.

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

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Abstract

Purpose : Diabetes inevitably results in diabetic retinopathy (DR) with time. SD-OCT imaging is used to assess diabetic changes in the retina, however these changes are apparent only late in the disease, when the retinal anatomy is already compromised. The purpose of this study was to develop an automated algorithm to detect occult retinal changes on SD-OCT images prior to the development of obvious anatomical or clinical changes.

Methods : Spectral domain OCT scans (Zeiss Cirrus HD-OCT 5000) were obtained from 16 diabetic subjects aged 53-76 years without clinical evidence of DR. 16 healthy subjects, matched for sex and age were used as controls. Subjects with high myopia (≤ -6.00 diopters) or tilted OCT scans were excluded. Twelve distinct layers were first segmented using a novel automated algorithm that combines shape, intensity, and spatial information. A novel normalized reflectivity scale (NRS) ranging from 0 units (vitreous) to 1000 units (retinal pigment epithelium [RPE]) was then applied to calculate the reflectivity for each segmented layer from the raw data. Tortuosity of retinal layers was quantified using the mean absolute curvature κ of the boundary between adjacent layers.

Results : Normalized reflectivity varied significantly by diagnosis (F1,658 = 24.18; p < 0.0001) and retinal layer (F11,658 = 457.3; p < 0.0001). Reflectivity per layer differed by side of the fovea (F11,658 = 6.13; p < 0.0001). Reflectivity in diabetic subjects in all layers was in average 35.1 NRS greater than in their matched controls (Figure 1). Curvature varied significantly by layer (F11,658 = 11.9; p < 0.0001) and side (F1,658 = 6.63; p = 0.010). Post hoc testing revealed significant differences in the IPL and INL where κ averaged 1.91 mm−1 and 1.12 mm−1 greater, respectively, in diabetes compared to control (Figure 2).

Conclusions : An automated image analysis algorithm allows the identification of subtle changes in diabetic retinas that occur prior to the disruption of normal anatomy. Detection of such changes carries the promise of early diagnosis of DR in diabetics.

This is an abstract that was submitted for the 2016 ARVO Annual Meeting, held in Seattle, Wash., May 1-5, 2016.

 

Normalized reflectivity per layer and diagnosis. No layer showed significant differences between diabetics and controls.

Normalized reflectivity per layer and diagnosis. No layer showed significant differences between diabetics and controls.

 

Mean and standard deviation of tortuosity per layer and diagnosis. **Control and diabetic subjects show significant differences (p < 0.05).

Mean and standard deviation of tortuosity per layer and diagnosis. **Control and diabetic subjects show significant differences (p < 0.05).

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