March 2012
Volume 53, Issue 14
Free
ARVO Annual Meeting Abstract  |   March 2012
Variability in measurements of Diabetic Macular Edema in SD-OCT using a 3D segmentation algorithm
Author Affiliations & Notes
  • John J. Chen
    Department of Ophthalmology and Visual Sciences,
    University of Iowa, Iowa City, Iowa
  • Kyungmoo Lee
    Department of Electrical and Computer Engineering,
    University of Iowa, Iowa City, Iowa
  • Meindert Niemeijer
    Department of Ophthalmology and Visual Sciences,
    Department of Electrical and Computer Engineering,
    University of Iowa, Iowa City, Iowa
  • Milan Sonka
    Department of Ophthalmology and Visual Sciences,
    Department of Electrical and Computer Engineering,
    University of Iowa, Iowa City, Iowa
  • Michael D. Abràmoff
    Department of Ophthalmology and Visual Sciences,
    University of Iowa, Iowa City, Iowa
    Department of Veterans Affairs, Iowa City, Iowa
  • Elliott H. Sohn
    Department of Ophthalmology and Visual Sciences,
    University of Iowa, Iowa City, Iowa
  • Footnotes
    Commercial Relationships  John J. Chen, None; Kyungmoo Lee, None; Meindert Niemeijer, None; Milan Sonka, Patent (P); Michael D. Abràmoff, Patent (P); Elliott H. Sohn, None
  • Footnotes
    Support  This work was supported in part by the National Institutes of Health grants R01 EY018853, R01 EY019112, and R01 EB004640.
Investigative Ophthalmology & Visual Science March 2012, Vol.53, 4669. doi:
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      John J. Chen, Kyungmoo Lee, Meindert Niemeijer, Milan Sonka, Michael D. Abràmoff, Elliott H. Sohn; Variability in measurements of Diabetic Macular Edema in SD-OCT using a 3D segmentation algorithm. Invest. Ophthalmol. Vis. Sci. 2012;53(14):4669.

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

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Abstract

Purpose: : To evaluate the intra-session repeatability of retinal thickness measurements in patients with diabetic macular edema (DME) using our standard 3D graph search based multilayer OCT segmentation automated algorithm to measure the overall thickness of the central macula.

Methods: : 46 eyes from 29 patients diagnosed with clinically significant DME were included and underwent serial macular-centered spectral domain optical coherence (SD-OCT) scans (Heidelberg Spectralis). The central 5.8x4.7mm2 area were segmented into 4 surfaces and the average thickness between the internal limiting membrane, external limiting membrane, inner/outer segment (IS/OS) junction, and the outer surface of the retinal pigment epithelium (RPE) were determined [1]. The variability between paired scans was analyzed and compared with the central macular thickness obtained from the Heidelberg Spectralis software.

Results: : The coefficient of repeatability and variation for macular thickness using the Iowa algorithm was 5.79 μm (0.87%) for full thickness retina, 2.56 μm (2.42%) for external limiting membrane to the outer RPE, and 2.52 μm (3.27%) for IS/OS junction to the outer RPE. The coefficient of repeatability and variation of the central macular thickness using the Heidelberg software was 8.2 μm (1.11%). The average thickness of the macula was 340.5 μm using the automated software, while the central macular thickness measured by the Heidelberg software was 375.4 μm.

Conclusions: : The reproducibility of retinal thickness measurements of the average thickness of the macula in patients with diabetic macular edema is improved by using a graph search multilayer algorithm that incorporates the full 3D information available in SD-OCT. Robust quantification of macular edema allows this to be used as an objective image based secondary endpoint for macular edema treatments, possibly in combination with quantification of External Limiting Membrane disruption.

Keywords: macula/fovea • edema • diabetic retinopathy 
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