June 2022
Volume 63, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2022
Autonomous Robotically Aligned OCT Enables Remote, Telehealth Retinal Imaging and Angiography
Author Affiliations & Notes
  • Ryan P McNabb
    Duke University Department of Ophthalmology, Durham, North Carolina, United States
  • Ailin Song
    Duke University Department of Ophthalmology, Durham, North Carolina, United States
  • Kyung-Min Roh
    Duke University Department of Ophthalmology, 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
  • Stefanie Schuman
    Duke University Department of Ophthalmology, Durham, North Carolina, United States
  • Glenn J Jaffe
    Duke University Department of Ophthalmology, Durham, North Carolina, United States
  • Joseph A. Izatt
    Biomedical Engineering, Duke University, Durham, North Carolina, United States
    Duke University Department of Ophthalmology, Durham, North Carolina, United States
  • Anthony N Kuo
    Duke University Department of Ophthalmology, Durham, North Carolina, United States
    Biomedical Engineering, Duke University, Durham, North Carolina, United States
  • Footnotes
    Commercial Relationships   Ryan McNabb Johnson & Johnson Vision Care, Code F (Financial Support), Leica Microsystems, Code P (Patent), Leica Microsystems, Code R (Recipient); Ailin Song None; Kyung-Min Roh None; Pablo Ortiz None; Mark Draelos None; Stefanie Schuman None; Glenn Jaffe None; Joseph Izatt Alcon, Inc., Code C (Consultant/Contractor), 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)
  • Footnotes
    Support  NEI R01-EY029302
Investigative Ophthalmology & Visual Science June 2022, Vol.63, 4453 – F0132. doi:
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    • Get Citation

      Ryan P McNabb, Ailin Song, Kyung-Min Roh, Pablo Ortiz, Mark Draelos, Stefanie Schuman, Glenn J Jaffe, Joseph A. Izatt, Anthony N Kuo; Autonomous Robotically Aligned OCT Enables Remote, Telehealth Retinal Imaging and Angiography. Invest. Ophthalmol. Vis. Sci. 2022;63(7):4453 – F0132.

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

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Abstract

Purpose : Ophthalmic OCT currently requires patients to position themselves in chin or forehead rests for stabilization with the system operator in close proximity. Robotically aligned OCT (RAOCT) enables remote patient imaging by autonomously aligning itself to a freely seated patient while the imager is physically elsewhere.

Methods : Face and pupil tracking cameras triangulated 3D eye and pupil motion enabling real-time autonomous robotic alignment of a custom 32° FOV retinal SSOCT (1040nm) system (Fig. 1A&C). In conjunction with robotic alignment, we introduced a network layer to the acquisition hardware stack: Zoom© for 2-way A/V communication and NoMachine© for encrypted IP-to-IP, GPU accelerated remote PC and hardware control (Fig. 1B), enabling kilometer-scale distances between imager and patient. The imager instructed patients (where to look, when to blink), began/ended OCT acquisition, and verified image quality. We acquired remote RAOCT retinal volumes from healthy and diseased eyes at the Duke Eye Center on 17 individuals (seated, without chin/forehead rest) under an IRB approved protocol with the imager 10.8 km away at a satellite clinic (Fig. 1D).

Results : Using autonomous robotic alignment, we remotely acquired (10.8 km) OCT and OCTA images in healthy and diseased eyes. Retinal capillaries surrounding the foveal avascular zone are well resolved in a 15° FOV OCTA image (Fig. 2A). In Fig. 2C&D are the thickness map and B-scan from a patient with cystoid macular edema (CME), epiretinal membrane (ERM), and a schisis cavity. Healthy retinas (n=14 eyes) had a mean foveal thickness of 272±1 µm with an intra-subject repeatability of ±1.7 µm; diseased retinas (n=17) had a mean thickness of 308±91 µm and a repeatability of ±1.6 µm.

Conclusions : We demonstrate OCT and OCTA imaging with kilometer-scale distance between imager and patient. This can serve as a foundation for telehealth retinal OCT without physically present technicians or physicians.

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

 

A) RAOCT optical system schematic B) Network diagram connecting remote imager to RAOCT system. C) Photograph of autonomously aligned RAOCT system. D) We imaged Duke Eye Center retinal clinic patients while the imager was located 10.8 km at satellite clinic.

A) RAOCT optical system schematic B) Network diagram connecting remote imager to RAOCT system. C) Photograph of autonomously aligned RAOCT system. D) We imaged Duke Eye Center retinal clinic patients while the imager was located 10.8 km at satellite clinic.

 

A) 32° FOV OCT en face volume projection with 15° FOV OCTA and averaged B-scan in B. B) Repeated B-scan from A. C) Thickness map of patient with CME, ERM and schisis cavity. D) Repeated B-scan from C.

A) 32° FOV OCT en face volume projection with 15° FOV OCTA and averaged B-scan in B. B) Repeated B-scan from A. C) Thickness map of patient with CME, ERM and schisis cavity. D) Repeated B-scan from C.

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