August 2021
Volume 62, Issue 11
Open Access
ARVO Imaging in the Eye Conference Abstract  |   August 2021
Analyzing automated OCT choroid thickness measurements
Author Affiliations & Notes
  • Luis De Sisternes
    Carl Zeiss Meditec Inc, Dublin, California, United States
  • Homayoun Bagherinia
    Carl Zeiss Meditec Inc, Dublin, California, United States
  • Hao Zhou
    University of Washington, Seattle, Washington, United States
  • Jie Lu
    University of Washington, Seattle, Washington, United States
  • Warren Lewis
    Bayside Photonics, Inc., Ohio, United States
  • Sophie Kubach
    Carl Zeiss Meditec Inc, Dublin, California, United States
  • Yingying Shi
    University of Miami Health System Bascom Palmer Eye Institute, Miami, Florida, United States
  • Philip J Rosenfeld
    University of Miami Health System Bascom Palmer Eye Institute, Miami, Florida, United States
  • Ruikang Wang
    University of Washington, Seattle, Washington, United States
  • Mary Kathryn Durbin
    Carl Zeiss Meditec Inc, Dublin, California, United States
  • Footnotes
    Commercial Relationships   Luis De Sisternes, Carl Zeiss Meditec Inc (E); Homayoun Bagherinia, Carl Zeiss Meditec Inc (E); Hao Zhou, None; Jie Lu, None; Warren Lewis, Carl Zeiss Meditec Inc (C); Sophie Kubach, Carl Zeiss Meditec Inc (E); Yingying Shi, None; Philip Rosenfeld, Carl Zeiss Meditec Inc (F), Carl Zeiss Meditec Inc (C); Ruikang Wang, Carl Zeiss Meditec Inc (F), Carl Zeiss Meditec Inc (C); Mary Durbin, Carl Zeiss Meditec Inc (E)
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science August 2021, Vol.62, 52. doi:
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      Luis De Sisternes, Homayoun Bagherinia, Hao Zhou, Jie Lu, Warren Lewis, Sophie Kubach, Yingying Shi, Philip J Rosenfeld, Ruikang Wang, Mary Kathryn Durbin; Analyzing automated OCT choroid thickness measurements. Invest. Ophthalmol. Vis. Sci. 2021;62(11):52.

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

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Abstract

Purpose : Advances in OCT technology allow larger field of view (FOV) scans and complex processing, such as choroid segmentation. However, little is known about automated choroid quantifications in large FOVs. We evaluate the accuracy and utility of these measurements across different macula sectors.

Methods : We collected 12x12 mm swept-source OCT volumes (PLEX® Elite 9000; ZEISS, Dublin, CA) from 27 healthy and 34 disease eyes (including 13 intermediate AMD eyes). Bruch’s membrane and choroid/sclera interface were annotated manually and automatically using prototype software, and thickness maps were generated by considering the distance between these interfaces. The optic nerve head (ONH) location was automatically detected and eliminated from the analysis. We analyzed the differences and correlation between manual and automated thickness values in an extended ETDRS grid and in a custom grid (Figure 1). We also measured the ability to discriminate between healthy and AMD eyes using each sector values for both the manual and automated methods by measuring the area under the receiver operating characteristic curve (AUC).

Results : Manual annotation resulted in smoother maps compared to the automated results due to the annotation tool employed. There were statistically significant differences (p<0.05) between manual and automated measurements in all sectors analyzed (automated values were consistently higher) due to agreement difficulty on where to draw the choroid/sclera interface. However, all sectors presented significant correlation between manual and automated measurements, with very high correlation (>0.85) in sectors not including the ONH. Lower correlation within the ONH vicinity was explained by higher difficulties in the segmentation. When comparing healthy and AMD patients, thickness was significantly higher in healthy cases (+47.6 and +44.5 µm overall in manual and automated, respectively). Discrimination was similar for both manual and automated methods excluding regions within the ONH, with higher AUC values in regions closer to the fovea. The highest AUC was observed in the superotemporal sectors in the extended ETDRS grid.

Conclusions : While significantly different, automated choroid thickness measurements show very high correlation and very similar discriminatory power to manual measurements excluding regions within the ONH.

This is a 2021 Imaging in the Eye Conference abstract.

 

Figure 1. Manual/automated choroid thickness in example AMD eye (left) and comparison analyzed data (right)

Figure 1. Manual/automated choroid thickness in example AMD eye (left) and comparison analyzed data (right)

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