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Reproducibility of Retinal Vascular Phenotypes Obtained with Optical Coherence Tomography Angiography: Importance of Vessel Segmentation

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Medical Image Understanding and Analysis (MIUA 2021)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12722))

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Abstract

Optical coherence tomography angiography (OCTA) is a non-invasive imaging method that can visualize the finest vascular networks in the human retina. OCTA image analysis has been successfully applied to the investigation of retinal vascular diseases of the eye and other systemic conditions that may manifest in the eye. To characterize and distinguish OCTA images from different pathologies, it is important to identify quantitative metrics and phenotypes that have high reproducibility and are not overly susceptible to the effects of imaging artifacts. This paper demonstrates the reproducibility of several recently demonstrated candidate OCTA quantitative metrics: mean curvature and tortuosity of the whole, foveal, superior, nasal, inferior, and temporal regions; foveal and parafoveal vessel skeleton density; and finally, foveal avascular zone area and acircularity index. This paper also highlights the importance of vessel segmentation choice on reproducibility using two different segmentation methods: optimally oriented flux and Frangi filter.

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Acknowledgements

DR and YG were supported by two Medical Research Council Precision Medicine Doctoral Training Programme scholarships (MR/N013166/1). MOB is supported by grants from EPSRC (EP/R029598/1, EP/T008806/1), Fondation Leducq (17 CVD 03), the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 801423, and British Heart Foundation/The Alan Turing Institute under a Cardiovascular Data Science Award. TJM and MOB acknowledge the funders of the SCONe project (https://www.ed.ac.uk/ophthalmology/scone). This project was supported in part by the Alzheimer’s Drug Discovery Foundation and the Heed Foundation (SC) and the VitreoRetinal Surgery Foundation (SC).

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Authors and Affiliations

  1. Centre for Medical Informatics, Usher Institute, The University of Edinburgh, Edinburgh, Scotland

    Darwon Rashid, Ylenia Giarratano & Miguel O. Bernabeu

  2. Edinburgh Clinical Research Facility and Edinburgh Imaging, University of Edinburgh, Edinburgh, Scotland

    Calum Gray, Charlene Hamid & Tom MacGillivray

  3. Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, Scotland

    Tom MacGillivray

  4. Department of Ophthalmology, Duke University School of Medicine, Durham, NC, USA

    Sophie Cai, Dilraj S. Grewal, Sharon Fekrat, Cason B. Robbins, Srinath Soundararajan & Justin P. Ma

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  1. Darwon Rashid
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Correspondence to Darwon Rashid .

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Editors and Affiliations

  1. University of Oxford, Oxford, UK

    Bartłomiej W. Papież

  2. Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates

    Mohammad Yaqub

  3. University of Oxford, Oxford, UK

    Jianbo Jiao

  4. University of Oxford, Oxford, UK

    Ana I. L. Namburete

  5. University of Oxford, Oxford, UK

    J. Alison Noble

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Rashid, D. et al. (2021). Reproducibility of Retinal Vascular Phenotypes Obtained with Optical Coherence Tomography Angiography: Importance of Vessel Segmentation. In: Papież, B.W., Yaqub, M., Jiao, J., Namburete, A.I.L., Noble, J.A. (eds) Medical Image Understanding and Analysis. MIUA 2021. Lecture Notes in Computer Science(), vol 12722. Springer, Cham. https://doi.org/10.1007/978-3-030-80432-9_19

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  • DOI: https://doi.org/10.1007/978-3-030-80432-9_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-80431-2

  • Online ISBN: 978-3-030-80432-9

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