June 2021
Volume 62, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2021
In vivo imaging of inner plexiform layer (IPL) stratification in the human retina with visible light Optical Coherence Tomography (OCT)
Author Affiliations & Notes
  • Vivek J Srinivasan
    Ophthalmology, NYU Langone Health, New York, New York, United States
    Ophthalmology and Vision Science, University of California Davis, Davis, California, United States
  • Tingwei Zhang
    Biomedical Engineering, University of California Davis, Davis, California, United States
  • Aaron Michael Kho
    Biomedical Engineering, University of California Davis, Davis, California, United States
  • Footnotes
    Commercial Relationships   Vivek Srinivasan, Optovue Inc. (P); Tingwei Zhang, None; Aaron Kho, None
  • Footnotes
    Support  NIH (NS094681, EB029747, EB023591, EY026556, EY028287, EY015387, EY031469, EY012576)
Investigative Ophthalmology & Visual Science June 2021, Vol.62, 30. doi:
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    • Get Citation

      Vivek J Srinivasan, Tingwei Zhang, Aaron Michael Kho; In vivo imaging of inner plexiform layer (IPL) stratification in the human retina with visible light Optical Coherence Tomography (OCT). Invest. Ophthalmol. Vis. Sci. 2021;62(8):30.

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

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Abstract

Purpose : Employing visible light OCT, we report a stereotyped reflectivity pattern of the inner plexiform layer (IPL) that parallels IPL stratification. We characterize this pattern non-invasively in adult human subjects without ocular pathology.

Methods : Subjects were imaged by a visible light OCT prototype instrument at UC Davis with 1 micron axial resolution. A total of 15 eyes of 15 subjects were analyzed. The inner retinal layer boundaries were demarcated. At each transverse position, the IPL intensity was interpolated onto an IPL thickness percentage abscissa axis. Images were partitioned into transverse segments of 450 microns (1.5 degrees) and IPL intensities were averaged across each segment (Figure 1A-B). To detect salient features of intensity profiles, a 14th order polynomial fit was performed on the intensity profile within the IPL (Figure 1C). The polynomial fit provided access to features such as stratum location and intensity (Figure 1D).

Results : Figure 2A shows subject-by-subject fitting of stratum S5 intensity versus IPL thickness with mixed effects and fixed effects models. The fixed slopes are all greater than zero, pointing to an increase in S5 prominence with IPL thickness (Figure 2B).

Conclusions : The proposed method reveals IPL organization in living human subjects, potentially enabling studies of stratification during development and in diseases.

This is a 2021 ARVO Annual Meeting abstract.

 

Figure 1. IPL intensity profiles (background corrected, averaged transversally over 1.5 degrees, and normalized) are displayed across the image (A) and plotted versus % IPL thickness (B). (C) Average IPL profile, excluding segments with an IPL thickness below 24 microns, across locations (mean +/- std. dev) shows a stereotyped pattern with 3 peaks and 2 valleys. A polynomial fit approximates the average profile (light gray dotted line), providing estimates of intensities of extrema and their locations (D). Stratum divisions, defined as positions where intensity crossed the midpoint between adjacent extrema, are shown with red and blue shading.

Figure 1. IPL intensity profiles (background corrected, averaged transversally over 1.5 degrees, and normalized) are displayed across the image (A) and plotted versus % IPL thickness (B). (C) Average IPL profile, excluding segments with an IPL thickness below 24 microns, across locations (mean +/- std. dev) shows a stereotyped pattern with 3 peaks and 2 valleys. A polynomial fit approximates the average profile (light gray dotted line), providing estimates of intensities of extrema and their locations (D). Stratum divisions, defined as positions where intensity crossed the midpoint between adjacent extrema, are shown with red and blue shading.

 

Figure 2. Summary of fixed (fixed intercept and slope for each subject) and mixed (fixed intercept and slope, with independent random intercept and slope for each subject) effects models, applied to S5 intensity versus IPL thickness. A) Model fits are shown for each of the 15 subjects. B) All subject slopes from the fixed effects model are positive.

Figure 2. Summary of fixed (fixed intercept and slope for each subject) and mixed (fixed intercept and slope, with independent random intercept and slope for each subject) effects models, applied to S5 intensity versus IPL thickness. A) Model fits are shown for each of the 15 subjects. B) All subject slopes from the fixed effects model are positive.

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