September 2016
Volume 57, Issue 12
Open Access
ARVO Annual Meeting Abstract  |   September 2016
A Novel Automated Method for the Objective Quantification of Retinal Layers Based on Spectral Domain Optical Coherence Tomography (SD-OCT) Imaging Reveals Sequential Changes in the Normal Retina with Age
Author Affiliations & Notes
  • Thomas Neyer
    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
  • Agustina C Palacio
    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
  • Andy Switala
    Department of Bioengineering, University of Louisville, Louisville, Kentucky, United States
  • Ahmed Soliman
    Department of Bioengineering, University of Louisville, 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
  • Shlomit Schaal
    Department of Ophthalmology and Visual Sciences, University of Louisville School of Medicine, Louisville, Kentucky, United States
  • Footnotes
    Commercial Relationships   Thomas Neyer, None; Ahmed ElTanboly, None; Agustina Palacio, None; Marwa Ismail, None; Andy Switala, None; Ahmed Soliman, None; Amir Hajrasouliha, University of Louisville (P); Amir Hadayer, None; Douglas Sigford, None; Ayman El-Baz, University of Louisville (P); Shlomit Schaal, 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, 5943. doi:
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      Thomas Neyer, Ahmed ElTanboly, Agustina C Palacio, Marwa Ismail, Andy Switala, Ahmed Soliman, Amir Hajrasouliha, Amir Hadayer, Douglas Kenneth Sigford, Ayman El-Baz, Shlomit Schaal; A Novel Automated Method for the Objective Quantification of Retinal Layers Based on Spectral Domain Optical Coherence Tomography (SD-OCT) Imaging Reveals Sequential Changes in the Normal Retina with Age. Invest. Ophthalmol. Vis. Sci. 2016;57(12):5943.

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

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Abstract

Purpose : The main limitation of SD-OCT imaging is that data obtained is qualitative and hence the diagnosis of retinal pathology is susceptible to interpreter bias. Quantitative, unbiased interpretation of the data is needed for objective definition of retinal layers. The purpose of this study was to develop a novel automated algorithm that objectively quantifies reflectivity of retinal layers from OCT images and to apply this algorithm to the investigation of changes that occur in the normal retina with age.

Methods : SD-OCT scans (Zeiss Cirrus HD-OCT 5000) were prospectively collected from 215 normal subjects (age 10–79) without clinical evidence of retinal pathology. Subjects with diabetes mellitus, myopia ≤ −6.00 diopters, and tilted OCT were excluded, leaving 165 (106 female; 59 male). A novel segmentation algorithm was first applied to extract twelve retinal layers using 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 the raw data. Statistical analysis employed a full factorial ANCOVA design with gender, foveal side (nasal/temporal), retinal layer, and continuous covariate age as factors.

Results : Normalized reflectivity varied significantly with age (F1,3864=482.3; p<0.0001) and layer (F11,3864=2350.5; p<0.0001) but not gender (F1,3864=0.226; p=0.635) or foveal side (F1,3864=0.159; p=0.690). The slope (change in NRS/yr) varied significantly by gender (F1,3864=25.08; p<0.0001) and retinal layer (F11,3864=18.67; p<0.0001). The interactions of foveal side with layer (F11,3864=27.07; p<0.0001) and gender (F1,3864=5.58; p=0.018) were significant. No other terms in the model were significant. NRS decreased with age overall, with the greatest declines seen in the ellipsoid zone (−3.91 NRS/yr) and NFL (−3.84 NRS/yr) (Figure 1). Normal aging had little to no effect on the RPE (−0.72 NRS/yr) or ELM (−0.95 NRS/yr).

Conclusions : A novel automated method enables quantitative analysis of the reflectivity changes in each retinal layer that occur with normal aging. Automatic quantification of SD-OCT data carries the promise to detect occult retinal pathology.

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

 

Figure 1. Slopes showing the decline of reflectivity for the twelve layers with age (95% confidence intervals).

Figure 1. Slopes showing the decline of reflectivity for the twelve layers with age (95% confidence intervals).

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