June 2013
Volume 54, Issue 15
Free
ARVO Annual Meeting Abstract  |   June 2013
Characterizing foveal specialization in albinism using AOSLO and SD-OCT
Author Affiliations & Notes
  • Melissa Wilk
    Cell Biology, Neurobiology, & Anatomy, Medical College of Wisconsin, Milwaukee, WI
  • John McAllister
    Ophthalmology, Medical College of Wisconsin, Milwaukee, WI
  • Teresa Patitucci
    Cell Biology, Neurobiology, & Anatomy, Medical College of Wisconsin, Milwaukee, WI
  • Adam Dubis
    Ophthalmology, Duke University Eye Center, Durham, NC
  • Kimberly Stepien
    Ophthalmology, Medical College of Wisconsin, Milwaukee, WI
  • William Wirostko
    Ophthalmology, Medical College of Wisconsin, Milwaukee, WI
  • Deborah Costakos
    Ophthalmology, Medical College of Wisconsin, Milwaukee, WI
  • C Summers
    Ophthalmology, University of Minnesota, Minneapolis, MN
  • Murray Brilliant
    Center for Human Genetics, Marshfield Clinic, Marshfield, WI
  • Joseph Carroll
    Cell Biology, Neurobiology, & Anatomy, Medical College of Wisconsin, Milwaukee, WI
    Ophthalmology, Medical College of Wisconsin, Milwaukee, WI
  • Footnotes
    Commercial Relationships Melissa Wilk, None; John McAllister, None; Teresa Patitucci, None; Adam Dubis, None; Kimberly Stepien, None; William Wirostko, None; Deborah Costakos, None; C Summers, Clarion Healthcare, LLC (C); Murray Brilliant, None; Joseph Carroll, Imagine Eyes, Inc. (S)
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2013, Vol.54, 1509. doi:
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      Melissa Wilk, John McAllister, Teresa Patitucci, Adam Dubis, Kimberly Stepien, William Wirostko, Deborah Costakos, C Summers, Murray Brilliant, Joseph Carroll; Characterizing foveal specialization in albinism using AOSLO and SD-OCT. Invest. Ophthalmol. Vis. Sci. 2013;54(15):1509.

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

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Abstract

Purpose: Albinism is commonly associated with foveal hypoplasia, though intersubject variability is becoming appreciated. Here we sought to further quantify the variability in foveal specialization in albinism using two high-resolution imaging modalities, SD-OCT and adaptive optics scanning light ophthalmoscopy (AOSLO).

Methods: Thirty-two subjects with clinical diagnosis of albinism were recruited. DNA was extracted from blood or saliva samples from 15 subjects and examined for mutations in GPR143, TYR, OCA2, and SLC45A2. Volumetric and linear SD-OCT images of the macula were obtained, and custom Matlab software was used to derive estimates of foveal pit depth, diameter, slope, and volume. Inner segment (IS) and outer segment (OS) lengths were determined using manual segmentation of the SD-OCT line scans. Five subjects were also imaged using AOSLO, and cone density was measured using a semi-automated cone counting software.

Results: We were able to determine mutations in 10 of the subjects. While most subjects lack complete foveal excavation, 2 subjects had foveae with near normal morphology. Analysis of SD-OCT line scans in several subjects revealed a fifth distinct hyperreflective band in the outer retina that was not visible in any of the normal subjects analyzed. There was variation in the lengthening of the OS, with many subjects falling within the normal range. Despite the absence of a fully developed pit, foveal cone density ranged from 82,111 - 122,415 cones/mm2 (average = 93,385 cones/mm2; normal cone density ranges from 98,200 - 324,100 cones/mm2).

Conclusions: Our observation of normal cone packing in the absence of a foveal pit supports the idea that a pit is not required for cone packing to occur. Additional metrics of foveal specialization (IS and OS length, foveal pit morphology) in these subjects are diverse and can overlap with normal values. It remains unclear whether retinal anatomy correlates with genotype or visual function, though the ability to quantify foveal specialization non-invasively provides a mechanism with which to address this issue.

Keywords: 585 macula/fovea • 689 retina: distal (photoreceptors, horizontal cells, bipolar cells) • 648 photoreceptors  
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