July 2019
Volume 60, Issue 9
Open Access
ARVO Annual Meeting Abstract  |   July 2019
Automated Method for the Long-term Quantiative Analysis of Macular Neovascularization using Optical Coherence Tomography Angiography (OCTA)
Author Affiliations & Notes
  • Alexandra Miere
    Ophthalmology, Centre Hospitalier intercommunal de Creteil, Creteil, France
    Laboratory of Images, Signals and Intelligent Systems, University Paris-Est, Créteil, France
  • Donato Colantuono
    Ophthalmology, Centre Hospitalier intercommunal de Creteil, Creteil, France
  • Avi Ohayon
    Ophthalmology, Centre Hospitalier intercommunal de Creteil, Creteil, France
  • Kawther Taibouni
    Laboratory of Images, Signals and Intelligent Systems, University Paris-Est, Créteil, France
  • Eric Petit
    Laboratory of Images, Signals and Intelligent Systems, University Paris-Est, Créteil, France
  • Camille JUNG
    Clinical Research Center, GRC Macula, and Biological Ressources Center, Centre Hospitalier Intercommunal de Créteil, Créteil, France
  • Eric H Souied
    Ophthalmology, Centre Hospitalier intercommunal de Creteil, Creteil, France
    Clinical Research Center, GRC Macula, and Biological Ressources Center, Centre Hospitalier Intercommunal de Créteil, Créteil, France
  • Footnotes
    Commercial Relationships   Alexandra Miere, None; Donato Colantuono, None; Avi Ohayon, None; Kawther Taibouni, None; Eric Petit, None; Camille JUNG, None; Eric Souied, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science July 2019, Vol.60, 3000. doi:https://doi.org/
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      Alexandra Miere, Donato Colantuono, Avi Ohayon, Kawther Taibouni, Eric Petit, Camille JUNG, Eric H Souied; Automated Method for the Long-term Quantiative Analysis of Macular Neovascularization using Optical Coherence Tomography Angiography (OCTA). Invest. Ophthalmol. Vis. Sci. 2019;60(9):3000. doi: https://doi.org/.

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

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Abstract

Purpose : The present study aimed to evaluate an algorithm of automatic segmentation and quantification of macular neovascularization (MNV) and to evaluate quantitatively, throughout a long-term follow-up of the OCTA, the predictive value of these variables, in patients presenting age-related macular degeneration.

Methods : Consecutive patients with wet AMD underwent multimodal imaging, including optical coherence angiography tomography (OCTA) at baseline and last follow up. The Sorensen-Dice coefficient (DSC) was calculated to evaluate the performance of automatic segmentation versus manual segmentation. Changes in total area, vascular area, vascular density, and fractal dimension were correlated with the final exudative signs on Spectral Domain Optical Coherence Tomography (SD-OCT). Receiver Operator Characteristic (ROC) curves were generated to evaluate the predictive value of these variations.

Results : Forty-two eyes were included. The average follow up time was 14 months. The average DSC was 0.72 +/- 0.15 baseline and 0.72 +/- 0.13 follow up. The correlation coefficient between the automatic and manual measurements was in the range 0.464-0.949 (p = 0.0019, p <0.0001). The inter-class correlation was in the range 0.423-0.843. The ROC curves and the area under the curve show a specificity of 69% for the presence of exudative recurrences for the variation of the whole area, of 63% for the vascular density and 62% for the vascular area. The fractal dimension was not specific for the presence of SD-OCT recurrences.

Conclusions : The algorithm designed in this study seems reliable and allows a faster and more consistent evaluation of OCTA images. Of the quantiative variables used in the recent literature, the variation of the total surface seems the most specific for the presence of the exudative recurrences on conventional multimodal imagery.

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

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