May 2008
Volume 49, Issue 13
Free
ARVO Annual Meeting Abstract  |   May 2008
Validation of a Newly-Developed Macular Sectioning Algorithm With Stratus Optical Coherence Tomography in Glaucoma
Author Affiliations & Notes
  • T. S. Vajaranant
    University of Illinois at Chicago, Chicago, Illinois
    Ophthalmology,
  • A. M. Bagci
    University of Illinois at Chicago, Chicago, Illinois
    Electrical and Computer Engineering,
  • R. Ansari
    University of Illinois at Chicago, Chicago, Illinois
    Electrical and Computer Engineering,
  • R. Zelkha
    University of Illinois at Chicago, Chicago, Illinois
    Ophthalmology,
  • J. T. Wilensky
    University of Illinois at Chicago, Chicago, Illinois
    Ophthalmology,
  • D. P. Edward
    Ophthalmology, Summa Health Systems, Akron, Ohio
  • M. Shahidi
    University of Illinois at Chicago, Chicago, Illinois
    Ophthalmology,
  • Footnotes
    Commercial Relationships  T.S. Vajaranant, None; A.M. Bagci, None; R. Ansari, None; R. Zelkha, None; J.T. Wilensky, None; D.P. Edward, None; M. Shahidi, None.
  • Footnotes
    Support  NEI Grant R01EY017918 (MS). Dept Core grant NIH EY01792, Research to Prevent Blindness
Investigative Ophthalmology & Visual Science May 2008, Vol.49, 4650. doi:https://doi.org/
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      T. S. Vajaranant, A. M. Bagci, R. Ansari, R. Zelkha, J. T. Wilensky, D. P. Edward, M. Shahidi; Validation of a Newly-Developed Macular Sectioning Algorithm With Stratus Optical Coherence Tomography in Glaucoma. Invest. Ophthalmol. Vis. Sci. 2008;49(13):4650. doi: https://doi.org/.

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

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Abstract

Purpose: : Structural alteration in the retinal layers of the macula has been previously described in glaucoma. We tested a previously validated macular sectioning algorithm, developed at our institution using Stratus OCT in discriminating changes between the retinal layers: normal and glaucomatous retina in the macular area

Methods: : Twenty-four eyes of 20 subjects (14 eyes of normally-sighted control subjects, 10 eyes of 6 glaucoma subjects) were recruited. The glaucoma patients had moderate to severe visual field defect (average mean deviation = -15.27 dB). Exclusion criteria included significant media opacity, macular pathology and history of diabetes. Stratus OCT (Carl Zeiss, Meditec, Inc, Dublin, CA) was used to measure macular thickness (6 linear scans). The previously developed automated macular sectioning algorithm was used to measure macular retinal nerve fiber layer (mRNFL), inner retinal thickness (innerRT = inner limiting membrane to the outer edge of the outer plexiform layer) and outer retinal thickness (outerRT =outer nuclear layer). For each retinal layer, a two-tailed t-test was performed to assess any difference of the retinal thickness between the glaucoma and the control groups.

Results: : For mRNFL thickness, the mean ± SD was 26.9 ± 3.6 µ in control and 11.5 ± 9.5 µ in glaucoma. For innerRT thickness, the mean ± SD was 159.1 ± 15.7 µ in control and 143.4 ± 19.4 µ in glaucoma. For outerRT thickness, the mean ± SD was 77.3 ± 6.3 µ in control and 89.9 ± 6.3 µ in glaucoma. Both mRNFL and innerRT thickness was statistically significant decreased in the glaucoma group when compared to the control group (p < 0.001 for mRNFL and p = 0.039 for innerRT). In contrast, outerRT thickness was statistically significant increased in the glaucoma group when compared to the control group (p < 0.001).

Conclusions: : The macular sectioning algorithm had the ability to detect thinning of the mRNFL and innerRT in patients with moderate to severe glaucoma. Our finding of increased outerRT is similar to data from a previous report showing increased the outer retinal thickness using a different macular segmentation algorithm. Macular sectioning as measured with our newly-developed algorithm using the Stratus OCT may be useful in examining glaucomatous changes within different layers of the retina. A long-term study is needed to determine if this test can serve as an adjunct objective test for monitoring of glaucomatous progression.

Keywords: imaging/image analysis: clinical 
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