June 2022
Volume 63, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2022
Comparison of Manual and Automated Retinal Flow Deficit Measurements in Proliferative Diabetic Retinopathy using Swept-Source OCT Imaging
Author Affiliations & Notes
  • Karin Rose Lypka
    Department Ophthalmology, University of Miami School of Medicine, Miami, Florida, United States
  • Qinqin Zhang
    Department of Bioengineering, University of Washington, Seattle, Washington, United States
  • Mengxi Shen
    Department Ophthalmology, University of Miami School of Medicine, Miami, Florida, United States
  • Jonathan Russell
    Institute for Vision Research and Department of Ophthalmology and Visual Sciences, The University of Iowa Roy J and Lucille A Carver College of Medicine, Iowa City, Iowa, United States
  • Hasenin Al-khersan
    Department Ophthalmology, University of Miami School of Medicine, Miami, Florida, United States
  • Megan Zou
    Columbia University, New York, New York, United States
  • William J Feuer
    Department Ophthalmology, University of Miami School of Medicine, Miami, Florida, United States
  • Ruikang K Wang
    Department of Bioengineering, University of Washington, Seattle, Washington, United States
    Department of Ophthalmology, University of Washington, Seattle, Washington, United States
  • Giovanni Gregori
    Department Ophthalmology, University of Miami School of Medicine, Miami, Florida, United States
  • Philip J Rosenfeld
    Department Ophthalmology, University of Miami School of Medicine, Miami, Florida, United States
  • Footnotes
    Commercial Relationships   Karin Lypka None; Qinqin Zhang None; Mengxi Shen None; Jonathan Russell Carl Zeiss Meditec, Code C (Consultant/Contractor); Hasenin Al-khersan None; Megan Zou None; William Feuer None; Ruikang Wang Carl Zeiss Meditec, Code C (Consultant/Contractor), Carl Zeiss Meditec, Code F (Financial Support), Carl Zeiss Meditec, Code P (Patent); Giovanni Gregori Carl Zeiss Meditec, Code F (Financial Support); Philip Rosenfeld Carl Zeiss Meditec, Code C (Consultant/Contractor), Carl Zeiss Meditec, Code F (Financial Support)
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2022, Vol.63, 2918 – F0071. doi:
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    • Get Citation

      Karin Rose Lypka, Qinqin Zhang, Mengxi Shen, Jonathan Russell, Hasenin Al-khersan, Megan Zou, William J Feuer, Ruikang K Wang, Giovanni Gregori, Philip J Rosenfeld; Comparison of Manual and Automated Retinal Flow Deficit Measurements in Proliferative Diabetic Retinopathy using Swept-Source OCT Imaging. Invest. Ophthalmol. Vis. Sci. 2022;63(7):2918 – F0071.

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

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Abstract

Purpose : Manual measurements of retinal flow deficits (RFDs) in eyes with proliferative diabetic retinopathy (PDR) imaged with widefield swept-source OCT (SS-OCT) were compared with measurements from an automated algorithm.

Methods : In a retrospective review of patients enrolled in a prospective SS-OCT (PLEX® Elite 9000, Carl Zeiss Meditec, Dublin CA) imaging study, a consecutive case series of eyes with PDR were imaged using a foveal-centered 12x12mm scan pattern underwent manual segmentation of areas with RFDs. Total retinal vasculature slabs were used for analysis of RFDs. A previously published algorithm was used to assess RFDs by converting a 2-dimensional en face SS-OCTA image to a vessel binary image using MATLAB. The areas of RFDs identified using the manual and automated methods were compared.

Results : A total of 19 eyes with PDR from 15 patients over 62 visits were compared. All scans were evaluated. The average RFD area measurements were not significantly different between manual (16.72 ± 17.27 mm2) and algorithm (17.64 ± 15.33 mm2) (p=0.15). 75% of the manual and algorithm measurements were within 5 mm2 of each other, with total measurements ranging from 0-80 mm2. There was also no significant difference between areas of RFDs detected only by the manual approach (5.14 ± 3.94 mm2) compared with the algorithm approach (6.06 ± 3.91 mm2; p=0.15). Examples of the scans and RFD outlines are shown in Fig. 1.

Conclusions : On average, the two techniques yielded similar results for total RFD area measurements with no disparity in areas detected by only one technique. This suggests that the automated approach might be useful for grading and monitoring RFDs in eyes with PDR.

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

 

Fig. 1. Comparison of manual and automated algorithm outlines of retinal flow deficits (RFDs) on SS-OCTA images from two eyes with PDR. First row = Total retinal SS-OCTA images; Second row, white = manually-graded RFDs; Third row, white = algorithm-graded RFDs; Fourth row, blue = common RFDs, purple = manual-only RFDs, red = algorithm-only RFDs.

Fig. 1. Comparison of manual and automated algorithm outlines of retinal flow deficits (RFDs) on SS-OCTA images from two eyes with PDR. First row = Total retinal SS-OCTA images; Second row, white = manually-graded RFDs; Third row, white = algorithm-graded RFDs; Fourth row, blue = common RFDs, purple = manual-only RFDs, red = algorithm-only RFDs.

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