July 2018
Volume 59, Issue 9
Open Access
ARVO Annual Meeting Abstract  |   July 2018
Comparing metrics for quantifying the human rod photoreceptor mosaic
Author Affiliations & Notes
  • Emily J Patterson
    Ophthalmology & Visual Sciences, Medical College of Wisconsin, Milwaukee, Wisconsin, United States
  • Christopher S Langlo
    Cell Biology, Neurology and Anatomy, Medical College of Wisconsin, Milwaukee, Wisconsin, United States
  • Robert F Cooper
    Department of Psychology, University of Pennsylvania, Philadelphia, Pennsylvania, United States
    Department of Ophthalmology, University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • Joseph Carroll
    Ophthalmology & Visual Sciences, Medical College of Wisconsin, Milwaukee, Wisconsin, United States
    Cell Biology, Neurology and Anatomy, Medical College of Wisconsin, Milwaukee, Wisconsin, United States
  • Footnotes
    Commercial Relationships   Emily Patterson, None; Christopher Langlo, None; Robert Cooper, None; Joseph Carroll, AGTC (F), Meira GTx (C)
  • Footnotes
    Support  NIH Grants: P30EY001931, R01EY017607, T32GM080202
Investigative Ophthalmology & Visual Science July 2018, Vol.59, 652. doi:
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      Emily J Patterson, Christopher S Langlo, Robert F Cooper, Joseph Carroll; Comparing metrics for quantifying the human rod photoreceptor mosaic. Invest. Ophthalmol. Vis. Sci. 2018;59(9):652.

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

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Abstract

Purpose : Adaptive optics scanning light ophthalmoscopy (AOSLO) enables in vivo visualization of photoreceptors. As yet, rod analysis has been limited to only the highest quality images, as direct density accuracy is susceptible to minor errors in cell identification. Moreover, it is poorly understood how metrics that are commonly used to assess cones should be applied to rods in normal and diseased retinas. Here we examine the performance of various photoreceptor-based metrics in describing the rod mosaic.

Methods : Simulated confocal images were created and modified to manipulate the rod mosaic by known amounts. Rods counts were acquired using semi-automated software and used to validate the relationship between metrics: inter-cell, nearest and furthest neighbor distance, density recovery profile (DRP) spacing, and density. Further validation used confocal and non-confocal split-detection AOSLO images, in which rods and cones could be identified unequivocally, from 6 subjects: 3 normal and 3 with achromatopsia (ACHM), imaged at 10° & 5° eccentricity respectively. Rod density was estimated in 4 additional ACHM subjects imaged at 5° eccentricity, using images of more typical quality.

Results : The DRP-derived rod density[1] overestimated direct density by 47.95%; however, its value remained stable across up to 50% random simulated rod loss (mean absolute deviation = 0.63%). Using measurements of cone size and density from split detection images, we “corrected” the DRP estimate for the area occupied by cones. The discrepancy between cone-corrected DRP-derived (CCDD) and direct rod density was 4.64 – 8.83% for normal subjects and 7.03 – 11.10% for ACHM subjects. CCDD estimates of rod density yielded a mean ± SD of 90,528 ± 8,843 rods/mm2 for normal subjects and 76,326 ± 18,943 rods/mm2 for all 7 with ACHM, in line with previous estimates at 10° & 5°[2,3].

Conclusions : The DRP from confocal AOSLO, combined with cone information from split detection, provides a robust estimation of rod density, which overcomes the need to resolve every rod in the image. Thus, we were able to assess the rod mosaic in images that would otherwise be unanalyzable, and our data suggest that the rod mosaic in ACHM is structurally unaffected. Development of automated methods to segment and measure the size of cones will streamline this process and enable more efficient detection and tracking of retinal disease.

[1] PMID: 3625330
[2] PMID: 2324310
[3] PMID: 27229708

This is an abstract that was submitted for the 2018 ARVO Annual Meeting, held in Honolulu, Hawaii, April 29 - May 3, 2018.

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