July 2019
Volume 60, Issue 9
Open Access
ARVO Annual Meeting Abstract  |   July 2019
Automated 2D and 3D assessment of choroidal thickness and vasculature with swept-source OCT
Author Affiliations & Notes
  • Hao Zhou
    University of Washington, Seattle, Washington, United States
  • Zhongdi Chu
    University of Washington, Seattle, Washington, United States
  • Qinqin Zhang
    University of Washington, Seattle, Washington, United States
  • Yining Dai
    Shanxi Eye Hospital, Taiyuan, China
  • Giovanni Gregori
    Department of Ophthalmology, Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida, United States
  • Philip J. Rosenfeld
    Department of Ophthalmology, Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida, United States
  • Ruikang K Wang
    University of Washington, Seattle, Washington, United States
  • Footnotes
    Commercial Relationships   Hao Zhou, None; Zhongdi Chu, None; Qinqin Zhang, None; Yining Dai, None; Giovanni Gregori, Carl Zeiss Meditec (F), Carl Zeiss Meditec (P); Philip Rosenfeld, Carl Zeiss Meditec (F), Carl Zeiss Meditec (C); Ruikang Wang, Carl Zeiss Meditec (C), Carl Zeiss Meditec (F), Carl Zeiss Meditec (P)
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science July 2019, Vol.60, 1267. doi:
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    • Get Citation

      Hao Zhou, Zhongdi Chu, Qinqin Zhang, Yining Dai, Giovanni Gregori, Philip J. Rosenfeld, Ruikang K Wang; Automated 2D and 3D assessment of choroidal thickness and vasculature with swept-source OCT. Invest. Ophthalmol. Vis. Sci. 2019;60(9):1267.

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

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Abstract

Purpose : Automated methods for assessing choroidal vasculature are surprisingly limited. This work aims to develop an automated method that accurately segments the choroid and provides choroidal vasculature information from 3D OCT scans without the necessity of OCT angiography. We propose 2D and 3D metrics for choroidal vasculature: choroidal vessel area intensity (VAD), choroid vessel volume (CVV), choroid stroma volume (CSV), choroidal vessel volume density (VVD) and choroidal stroma-to-vessel volume ratio (SVR).

Methods : SS-OCT imaging (PLEX® Elite 9000 (ZEISS, Dublin, CA)) was used to collect 12x12 mm macular scans from subjects. The steps for automatic 3D segmentation of choroid included: 1) attenuation correction; 2) excluding optic disc; and 3) graph search for Bruch’s membrane and the outer border of choroidal vessels. The 2D choroidal vasculature map was obtained using minimum en face projection. The 3D choroidal vessels were segmented on each B-scan in the whole volume scan. From the segmented 3D choroidal vessels, the metrics of mean choroid thickness (MCT), VAD, CVV, CSV, VVD and SVR were investigated in 2D or 3D (Fig. 1).

Results : 144 normal subjects were recruited with at least 20 subjects from each decade ranging from 20s to 80s. The automatic choroid segmentations assisted by attenuation correction were validated with manual segmentations and showed good agreement on all metrics (all P<0.0001). VAD, CVV and CSV showed significant correlations with choroid thickness (all P < 0.0001). Interestingly, VVD and SVR were constant with small variations among all subjects (68.9±1.3% and 0.45±0.03). Age-related distributions of choroid thickness and metrics for choroidal vessels from the normal database were also analyzed. All choroid-related metrics were significantly correlated with age (all P<0.0001) except VVD and SVR (Fig.2).

Conclusions : The proposed automated choroidal assessments of thickness and vasculature were successful in both 2D and 3D OCT scans, which will be clinically useful in quantitative investigations of ocular diseases involving the choroid such as AMD, central serous chorioretinopathy, polypoidal choroidal vasculopathy and pathologic myopia.

This abstract was presented at the 2019 ARVO Annual Meeting, held in Vancouver, Canada, April 28 - May 2, 2019.

 

Fig. 1. Flow chart for automated 2D and 3D assessment of choroidal thickness and vasculature.

Fig. 1. Flow chart for automated 2D and 3D assessment of choroidal thickness and vasculature.

 

Fig. 2. (A-C) Pearson’s correlation analysis of MCT, VAD, VVD. (D-F) Age-related distribution of MCT, VAD and VVD.

Fig. 2. (A-C) Pearson’s correlation analysis of MCT, VAD, VVD. (D-F) Age-related distribution of MCT, VAD and VVD.

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