July 2019
Volume 60, Issue 9
Open Access
ARVO Annual Meeting Abstract  |   July 2019
Normative database of cone spacing and density from adaptive optics montage
Author Affiliations & Notes
  • Snega Kalaparambath
    Ophthalmology, Scheie Eye Institute, Philadelphia, Pennsylvania, United States
  • Robert F Cooper
    Ophthalmology, Scheie Eye Institute, Philadelphia, Pennsylvania, United States
    Psychology, University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • Grace Vergilio
    Ophthalmology, Scheie Eye Institute, Philadelphia, Pennsylvania, United States
  • Geoffrey K Aguirre
    Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • Jessica Ijams Wolfing Morgan
    Ophthalmology, Scheie Eye Institute, Philadelphia, Pennsylvania, United States
    Center for Advanced Retinal and Ocular Therapeutics, Philadelphia, Pennsylvania, United States
  • Footnotes
    Commercial Relationships   Snega Kalaparambath, None; Robert Cooper, Four Pi Innovations (P), Medical College of Wisconsin (C); Grace Vergilio, None; Geoffrey Aguirre, None; Jessica Morgan, AGTC (F), US Patent 8226236 (P)
  • Footnotes
    Support  NIH R01EY028601, NIH U01EY025477, NIH U01EY025864, NIH P30 EY001583, Research to Prevent Blindness, Foundation Fighting Blindness, the F. M. Kirby Foundation, and the Paul and Evanina Mackall Foundation Trust.
Investigative Ophthalmology & Visual Science July 2019, Vol.60, 1428. doi:
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    • Get Citation

      Snega Kalaparambath, Robert F Cooper, Grace Vergilio, Geoffrey K Aguirre, Jessica Ijams Wolfing Morgan; Normative database of cone spacing and density from adaptive optics montage. Invest. Ophthalmol. Vis. Sci. 2019;60(9):1428.

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

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Abstract

Purpose : Adaptive optics (AO) retinal imaging has enabled visualization of the photoreceptor mosaic, however quantification of mosaic parameters has generally been limited to discretely sampled regions of interest (ROIs). Here, we automatically estimate pointwise inter-cell distance (ICD) and cone density across retinal montages, with the intent of building a normative database from every retinal locus within a montage.

Methods : Confocal AO image sequences of the human photoreceptor mosaic were acquired at retinal locations surrounding the fovea and extending ~1.6 mm along each meridian in 20 eyes from 20 normal-sighted controls using a custom built AO scanning light ophthalmoscope. Image sequences were registered, distortions from eye motion were removed, and images were montaged. Montages were resized to a common scale between subjects. ICD over each subject’s montage was determined by extracting a grid of ROIs from the montages, taking the discrete Fourier transform (DFT) for each ROI, and automatically finding the ICD and cone density corresponding to the peak of the DFT modal ring using a custom MATLAB algorithm. ICD and density estimates from grid locations with multiple overlapping images were combined using a weighted average based on estimation quality, where quality was determined by the distinctiveness of the modal ring. Grid locations with quality assessments less than two standard deviations less than the mean quality were excluded from further analysis for each subject. Finally, ICD and density from all subjects at all grid locations were collated and the mean ICD and density was calculated across subjects.

Results : Mean ICD and density across all 20 subjects was 4.3, 5.4, 7.3, and 9.3 µm and 68,000, 39,000, 21,000, and 13,000 cones/mm2 at 0.2, 0.4, 0.8, and 1.6 mm temporal to fixation, respectively (standard deviation: 0.4, 0.4, 0.5, 0.6 µm, and 13,000, 5,300, 2,700, and 2,000 cones/mm2 respectively). Similar to previous reports, ICD was ~10% higher along superior and inferior meridians relative to the temporal and nasal meridians. Our estimation quality metric routinely excluded grid locations within the central 300 µm horizontally and 260 µm vertically.

Conclusions : We created a normative database of pointwise ICD and density across individuals using automated analysis of AO montages. This database will be useful for future studies comparing diseased and normal retina at precisely matched retinal locations.

This abstract was presented at the 2019 ARVO Annual Meeting, held in Vancouver, Canada, April 28 - May 2, 2019.

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