April 2011
Volume 52, Issue 14
Free
ARVO Annual Meeting Abstract  |   April 2011
Characterization Of Choroidal Morphology In Healthy Eyes Using Spectral Domain Optical Coherence Tomography
Author Affiliations & Notes
  • Namrata Nandakumar
    Ophthalmology, Tufts Medical Center (NEEC), Boston, Massachusetts
  • Lauren Branchini
    Ophthalmology, Tufts Medical Center (NEEC), Boston, Massachusetts
  • Caio Regatieri
    Ophthalmology, Tufts Medical Center (NEEC), Boston, Massachusetts
  • Jonathan J. Liu
    Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts
  • James G. Fujimoto
    Electrical Engineering & Computer Scienc, Massachusetts Inst of Technology, Cambridge, Massachusetts
  • Jay S. Duker
    Ophthalmology, New England Eye Center, Boston, Massachusetts
  • Footnotes
    Commercial Relationships  Namrata Nandakumar, None; Lauren Branchini, None; Caio Regatieri, None; Jonathan J. Liu, None; James G. Fujimoto, None; Jay S. Duker, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science April 2011, Vol.52, 2856. doi:
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      Namrata Nandakumar, Lauren Branchini, Caio Regatieri, Jonathan J. Liu, James G. Fujimoto, Jay S. Duker; Characterization Of Choroidal Morphology In Healthy Eyes Using Spectral Domain Optical Coherence Tomography. Invest. Ophthalmol. Vis. Sci. 2011;52(14):2856.

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

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Abstract

Purpose: : With improved Spectral Domain Optical Coherence Tomography (SD-OCT) software it is possible to better characterize choroidal morphology compared to previous OCT hardware and software. The choroid has both large and small caliber vessels. Using SD-OCT software, we manually measured the total choroidal thickness, and the thickness of the large caliber vessel layers in healthy eyes. We then developed custom software that uses the ratio between light and dark areas in the choroid to automatically calculate the ratio of the subfoveal choroidal stromal area to the area of choroidal vessel lumen in healthy eyes.

Methods: : 43 eyes of 43 subjects with no retinal or choroidal disease underwent high-definition raster scanning using SD-OCT. The choroidal thickness was measured in three locations: at the fovea, 750 microns temporal to the fovea, and 750 microns nasal to the fovea. In the same locations, the distance from the choroid/sclera junction to the closest large choroidal vessel was measured. All measurements were performed by 2 independent observers. Custom software was used to calculate the ratio of choroidal stromal area to the choroidal vessel lumen area in the subfoveal region.

Results: : The 43 subjects had a mean age of 51.6 years. The total choroidal thickness at the fovea was 256.8 µm ± 75.8µm, 750µm temporal to the fovea was 255.0µm ± 75.7µm and 750µm nasal to the fovea was 243.2µm ± 69.3µm. The thickness of the large vessel layer at the fovea was 204.3µm ± 65.9µm, 750µm temporal to the fovea was 203.7µm ± 60.3µm and 750µm nasal to the fovea was 198.6µm ± 62.5µm. Choroidal thickness and large vessel measurements had a strong inter-observer correlation coefficients (r = 0.92, P < .0001 and r = 0.90, P < .0001 respectively). The ratio of the large vessel layer to the total choroidal thickness at the fovea was .79 ± 0.067, 750µm temporal to the fovea was .81 ± 0.068 and 750µm nasal to the fovea was 0.79 ± 0.057. The light/dark ratio in the subfoveal region had a mean of 0.26 and standard deviation of ± 0.053.

Conclusions: : We report a novel way of characterize the choroid in healthy eyes. Further studies looking at the choroidal thickness, large vessel layer thickness, and light/dark ratios in eyes with disease states such as age related macular degeneration are needed.

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