June 2022
Volume 63, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2022
Automated visualization of Henle's fiber layer and outer nuclear layer in retinal volumes using robotically-aligned optical coherence tomography
Author Affiliations & Notes
  • Amit Narawane
    Biomedical Engineering, Duke University, Durham, North Carolina, United States
  • Pablo Ortiz
    Biomedical Engineering, Duke University, Durham, North Carolina, United States
  • Mark Draelos
    Biomedical Engineering, Duke University, Durham, North Carolina, United States
  • Ryan P McNabb
    Ophthalmology, Duke University Medical Center, Durham, North Carolina, United States
  • Anthony N Kuo
    Ophthalmology, Duke University Medical Center, Durham, North Carolina, United States
    Biomedical Engineering, Duke University, Durham, North Carolina, United States
  • Joseph A. Izatt
    Biomedical Engineering, Duke University, Durham, North Carolina, United States
    Ophthalmology, Duke University Medical Center, Durham, North Carolina, United States
  • Footnotes
    Commercial Relationships   Amit Narawane None; Pablo Ortiz None; Mark Draelos None; Ryan McNabb Johnson & Johnson Vision, Code F (Financial Support), Leica Microsystems, Code P (Patent), Leica Microsystems, Code R (Recipient); Anthony Kuo Johnson & Johnson Vision, Code F (Financial Support), Leica Microsystems, Code P (Patent), Leica Microsystems, Code R (Recipient); Joseph Izatt Alcon, Inc., Code C (Consultant/Contractor), Leica Microsystems, Code P (Patent), Leica Microsystems, Code R (Recipient)
  • Footnotes
    Support  National Institutes of Health (R01-EY029302, U01-EY028079)
Investigative Ophthalmology & Visual Science June 2022, Vol.63, 3514. doi:
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      Amit Narawane, Pablo Ortiz, Mark Draelos, Ryan P McNabb, Anthony N Kuo, Joseph A. Izatt; Automated visualization of Henle's fiber layer and outer nuclear layer in retinal volumes using robotically-aligned optical coherence tomography. Invest. Ophthalmol. Vis. Sci. 2022;63(7):3514.

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

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Abstract

Purpose : Standard optical coherence tomography (OCT) retinal imaging methods do not clearly distinguish outer nuclear layer (ONL) from Henle's fiber layer (HFL). HFL can be visually distinguished from ONL by de-centering the OCT beam pupil entry position, but this process requires operator skill and involves manual adjustment for every B-scan. Robotically-aligned OCT (RAOCT) automatically optimizes the pupil entry position per B-scan to acquire retinal volumes that offer complete radial visualization of HFL.

Methods : We mounted a custom swept-source OCT (1060nm) system on a collaborative robot with face and pupil tracking cameras (Fig. 1B) to enable real-time pupil tracking of imaging subjects. As seen in Figure 1A, a 2D fast steering mirror (FSM) conjugate to the retinal image plane modifies the pupil entry position of the OCT beam. Our custom software acquired retinal OCT volumes with radial B-scans and automatically adjusted the pupil entry position for each B-scan in an optimal path to visualize the HFL (Fig. 1C). With these B-scans, we reconstructed full retinal volumes that include HFL data throughout. We acquired such retinal volumes from consented subjects under an IRB-approved protocol.

Results : Figure 2 shows B-scans from retinal volumes acquired with and without the automated pupil entry adjustment. Fig. 2A shows a B-scan from a standard volume taken through the pupil center, and Fig. 2D shows a B-scan from the reconstructed volume, combining data from the B-scans in Fig. 2B and 2C. Arrows indicate areas of increased contrast due to reflectance from HFL.

Conclusions : We developed a technique for automated volumetric HFL visualization using a pupil entry adjusting RAOCT system. With this method, retinal volumes that distinguish HFL and ONL can be readily acquired, allowing for the investigation of ONL measurements as potential biomarkers in leading ophthalmic diseases.

This abstract was presented at the 2022 ARVO Annual Meeting, held in Denver, CO, May 1-4, 2022, and virtually.

 

Fig 1: A) RAOCT system schematic. B) Actual system. C) Schematic of scan pattern. Orange line shows changing pupil entry position actuated by the FSM. Gray lines show direction of radial scan at each pupil entry point.

Fig 1: A) RAOCT system schematic. B) Actual system. C) Schematic of scan pattern. Orange line shows changing pupil entry position actuated by the FSM. Gray lines show direction of radial scan at each pupil entry point.

 

Fig 2: A) B-scan from standard OCT volume through the pupil center. B,C) B-scans at opposite pupil entry positions. C) B-scan from reconstructed volume. Arrows indicate increased contrast below outer plexiform layer (OPL) due to visualization of HFL.

Fig 2: A) B-scan from standard OCT volume through the pupil center. B,C) B-scans at opposite pupil entry positions. C) B-scan from reconstructed volume. Arrows indicate increased contrast below outer plexiform layer (OPL) due to visualization of HFL.

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