April 2011
Volume 52, Issue 14
ARVO Annual Meeting Abstract  |   April 2011
Macular Ganglion Cell-Internal Plexiform Layer: Detection and Thickness Reproducibility with Cirrus HD-OCT in Glaucoma
Author Affiliations & Notes
  • Jean-Claude Mwanza
    Ophthalmology, Bascom Palmer Eye Institute, Miami, Florida
  • Mary K. Durbin
    R & D, Carl Zeiss Meditec, Inc, Dublin, California
  • Donald L. Budenz
    Ophthalmology, Bascom Palmer Eye Institute, Miami, Florida
  • Footnotes
    Commercial Relationships  Jean-Claude Mwanza, None; Mary K. Durbin, E (E); Donald L. Budenz, None
  • Footnotes
    Support  NIH Grant P30 EY014801, Research to Prevent Blindness, and Carl Zeiss Meditec
Investigative Ophthalmology & Visual Science April 2011, Vol.52, 184. doi:
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    • Get Citation

      Jean-Claude Mwanza, Mary K. Durbin, Donald L. Budenz; Macular Ganglion Cell-Internal Plexiform Layer: Detection and Thickness Reproducibility with Cirrus HD-OCT in Glaucoma. Invest. Ophthalmol. Vis. Sci. 2011;52(14):184.

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

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Purpose: : To demonstrate the capability of Cirrus HD-OCT in detecting and measuring the macular ganglion-cell-internal plexiform (GCIP) layer thickness, and to assess its reproducibility in glaucomatous eyes.

Methods: : Fifty glaucomatous eyes (25 mild, 11 moderate, 14 severe) of 50 patients underwent macular scanning using the Cirrus OCT Macular Cube 200x200 acquisition protocol. One eye randomly selected was scanned per subject. The Carl Zeiss Meditec ganglion cell analysis (GCA) algorithm, which only includes the RGC layer and the IPL in the measurements, was used to detect the macular GCIP and measure automatically the thickness of the following parameters: overall GCIP average, the minimum GICP, and the average thicknesses of GCIP in supero-temporal, superior, supero-nasal, infero-nasal, inferior, infero-temporal sectors. Five scans were obtained on five different days within two months. The reproducibility of the measurements was evaluated by determining the intraclass correlation coefficients (ICC), coefficients of variation (COV), and test-retest standard deviation (TRT SD).

Results: : All ICCs ranged between 0.94 and 0.99, but ICCs for average GCIP ad superior parameters (range: 0.98-0.99) were slightly higher than for inferior parameters (range: 0.94-0.97). COVs were all less than 2.5%, with 1.4% for average GCIP and COVs for superior parameters (range: 1.3% - 1.6%) slightly lower than those of inferior parameters (range: 1.4% - 2.2%). The TRT SD was lowest for average GCIP (0.97), and varied from 1.28 (superior sector) to 2.17 (inferior sector). However, significant differences between severity groups of parameter averages were only found for inferior temporal GCC (p = 0.029) and minimum GCIP (p = 0.037).

Conclusions: : Cirrus HD-OCT ganglion cell analysis algorithm show excellent intervisit reproducibility of GCIP parameters. Because the Cirrus HD-OCT GCA algorithm only takes the RGC layer and the IPL in the measurements, it may accurately reflect the health of RGCs. Thus, longitudinal monitoring of GCIP may be possible with Cirrus HD-OCT for the assessment of glaucoma progression.

Keywords: ganglion cells • imaging methods (CT, FA, ICG, MRI, OCT, RTA, SLO, ultrasound) 

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