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Derivation of human retinal cell densities using high-density, spatially localized optical coherence tomography data from the human retina5.75 MB
Published VersionCC BY V4.0, Open Access
Journal article
Derivation of human retinal cell densities using high-density, spatially localized optical coherence tomography data from the human retina
Journal of Comparative Neurology , Vol.531(11), pp.1108-1125
2023
PMID: 37073514
Abstract
This study sought to identify demographic variations in retinal thickness measurements from optical coherence tomography (OCT), to enable the calculation of cell density parameters across the neural layers of the healthy human macula. From macular OCTs (n = 247), ganglion cell (GCL), inner nuclear (INL), and inner segment-outer segment (ISOS) layer measurements were extracted using a customized high-density grid. Variations with age, sex, ethnicity, and refractive error were assessed with multiple linear regression analyses, with age-related distributions further assessed using hierarchical cluster analysis and regression models. Models were tested on a naïve healthy cohort (n = 40) with Mann-Whitney tests to determine generalizability. Quantitative cell density data were calculated from histological data from previous human studies. Eccentricity-dependent variations in OCT retinal thickness closely resemble topographic cell density maps from human histological studies. Age was consistently identified as significantly impacting retinal thickness (p = .0006, .0007, and .003 for GCL, INL and ISOS), with gender affecting ISOS only (p < .0001). Regression models demonstrated that age-related changes in the GCL and INL begin in the 30th decade and were linear for the ISOS. Model testing revealed significant differences in INL and ISOS thickness (p = .0008 and .0001; however, differences fell within the OCT's axial resolution. Qualitative comparisons show close alignment between OCT and histological cell densities when using unique, high-resolution OCT data, and correction for demographics-related variability. Overall, this study describes a process to calculate in vivo cell density from OCT for all neural layers of the human retina, providing a framework for basic science and clinical investigations.
Details
- Title
- Derivation of human retinal cell densities using high-density, spatially localized optical coherence tomography data from the human retina
- Authors
- Janelle Tong (Author) - UNSW SydneyVincent Khou (Author) - UNSW SydneyMatt Trinh (Author) - UNSW SydneyDavid Alonso-Caneiro (Author) - University of the Sunshine Coast, Queensland, School of Science, Technology and EngineeringBarbara Zangerl (Author) - UNSW SydneyMichael Kalloniatis (Corresponding Author) - UNSW Sydney
- Publication details
- Journal of Comparative Neurology , Vol.531(11), pp.1108-1125
- Publisher
- John Wiley & Sons, Inc.
- Date published
- 2023
- DOI
- 10.1002/cne.25483
- ISSN
- 1096-9861; 0021-9967
- PMID
- 37073514
- Copyright note
- © 2023 The Authors. The Journal of Comparative Neurology published by Wiley Periodicals LLC. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
- Data Availability
- The data that support the findings of this study are available in the Supporting Section of this article.
- Grants
- Organisation Unit
- School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 99719552602621
- Output Type
- Journal article
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- Web Of Science research areas
- Neurosciences
- Zoology
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