Investigative Ophthalmology & Visual Science Cover Image for Volume 62, Issue 8
June 2021
Volume 62, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2021
Assessing the validity of a cross-platform retinal image segmentation tool in normal and diseased retina
Author Affiliations & Notes
  • Varsha Alex
    Ophthalmology, Joan and Irwin Jacobs Retina Center, La Jolla, California, United States
  • Tahmineh Motevasseli
    Ophthalmology, Joan and Irwin Jacobs Retina Center, La Jolla, California, United States
  • Jefy Alex Jayamon
    QUALCOMM Inc, San Diego, California, United States
  • Sumit R Singh
    Ophthalmology, Joan and Irwin Jacobs Retina Center, La Jolla, California, United States
  • Dirk Uwe Bartsch
    Ophthalmology, Joan and Irwin Jacobs Retina Center, La Jolla, California, United States
  • Lingyun Cheng
    Ophthalmology, Joan and Irwin Jacobs Retina Center, La Jolla, California, United States
  • Shyamanga Borooah
    Ophthalmology, Joan and Irwin Jacobs Retina Center, La Jolla, California, United States
  • William R Freeman
    Ophthalmology, Joan and Irwin Jacobs Retina Center, La Jolla, California, United States
  • Footnotes
    Commercial Relationships   Varsha Alex, None; Tahmineh Motevasseli, None; Jefy Jayamon, None; Sumit Singh, None; Dirk Bartsch, None; Lingyun Cheng, None; Shyamanga Borooah, None; William Freeman, None
  • Footnotes
    Support  UCSD Vision Research Center Core Grant from the National Eye Institute P30EY022589, NIH grant R01EY016323.
Investigative Ophthalmology & Visual Science June 2021, Vol.62, 2433. doi:
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      Varsha Alex, Tahmineh Motevasseli, Jefy Alex Jayamon, Sumit R Singh, Dirk Uwe Bartsch, Lingyun Cheng, Shyamanga Borooah, William R Freeman; Assessing the validity of a cross-platform retinal image segmentation tool in normal and diseased retina. Invest. Ophthalmol. Vis. Sci. 2021;62(8):2433.

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

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Abstract

Purpose : Retrospective, cross-sectional study, quantitatively and qualitatively comparing automated retinal image segmentation using cross platform OrionTM software to proprietary software on retinal images captured using Heidelberg HRA+OCT

Methods : Retinal layer segmentations of normal, intermediate dry AMD and diabetic macular edema eyes were performed using Spectralis® HRA+OCT and automated OCT segmentation software OrionTM. Quantitative comparisons were made between the volumes of Nerve fiber layer (NFL), Ganglion cell layer (GCL), Inner plexiform layer (IPL), Outer plexiform layer (OPL), Inner nuclear layer (INL), Outer nuclear layer (ONL), total inner retinal layer (INLY) and total outer retinal layer (OUTLY). A qualitative comparison of accuracy was made by graders who compared software segmentation to manual segmentation.

Results : In normal eyes, all retinal layer volumes calculated by the two softwares were moderate-strongly correlated (Pearson correlation, r > 0.4) except OUTLY. However, differences were statistically significant except in GCIPL and OUTLY. Qualitative analysis done using Wilcoxon test showed that OrionTM was significantly better than Heidelberg in the segmentation of NFL and INL layers (p =< 0.01). In dry AMD eyes, GCIPL, INL, ONL, INLY, TRV layer volumes were moderate-strongly correlated (r > 0.4) between softwares and their differences were statistically significant except GCIPL. Qualitatively, OrionTM generated significantly better segmentation only for the NFL (p =< 0.05). In eyes with DME, all layer volume values were moderate-strongly correlated (r > 0.4) between softwares and their differences were statistically significant except OPL and OUTLY. Qualitatively, OrionTM was significantly better at segmenting INL and OPL layers (p =< 0.01).

Conclusions : Layer volumes correlated well between OrionTM and Heidelberg softwares but were, in general, significantly different suggesting that they used different retinal landmarks for segmentation. Qualitatively, when comparing to the gold standard of manual segmentation, OrionTM segmented normal and diseased retina more accurately. Findings suggest that the cross-platform OrionTM retinal layer segmentation software can be used reliably to study the retinal layers in normal and diseased eyes.



Abbreviations: HB- Heidelberg, OR- Orion, TRV- Total retinal volume, GCIPL – GCL+IPL

This is a 2021 ARVO Annual Meeting abstract.

 

Qualitative Assessment

Qualitative Assessment

 

Retinal Segmentation

Retinal Segmentation

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