June 2015
Volume 56, Issue 7
Free
ARVO Annual Meeting Abstract  |   June 2015
Anatomically-accurate graphing and flow modeling of the retinal vasculature using Doppler OCT and angiography
Author Affiliations & Notes
  • Conor Leahy
    Biomedical Engineering, University of California, Davis, Davis, CA
  • Harsha Radhakrishnan
    Biomedical Engineering, University of California, Davis, Davis, CA
  • Geoffrey Weiner
    Shiley Eye Center, University of California-San Diego, San Diego, CA
  • Jeffrey L Goldberg
    Shiley Eye Center, University of California-San Diego, San Diego, CA
  • Vivek Jay Srinivasan
    Biomedical Engineering, University of California, Davis, Davis, CA
  • Footnotes
    Commercial Relationships Conor Leahy, None; Harsha Radhakrishnan, None; Geoffrey Weiner, None; Jeffrey Goldberg, None; Vivek Srinivasan, None
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2015, Vol.56, 5966. doi:
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      Conor Leahy, Harsha Radhakrishnan, Geoffrey Weiner, Jeffrey L Goldberg, Vivek Jay Srinivasan; Anatomically-accurate graphing and flow modeling of the retinal vasculature using Doppler OCT and angiography. Invest. Ophthalmol. Vis. Sci. 2015;56(7 ):5966.

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

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Abstract

Purpose: Normal functioning of the retina is dependent upon a sufficient supply of oxygen and other nutrients by a network of blood vessels. In this study, we present an optical coherence tomography (OCT) angiography-based graphing protocol for imaging and reconstructing the inner retinal vascular network over a field of view of 3 x 3 mm in the rat inner retina. Based on this data, we provide detailed and comprehensive characterization of the vascular branching patterns in the rodent inner retina.

Methods: Rat eyes were imaged with a 1300 nm spectral/Fourier domain OCT microscope. OCT angiography techniques were applied to enhance the contrast of the red blood cells (RBCs) within the vasculature. Additionally, flow velocity axial projections were obtained using Doppler OCT. A topological model of the inner retinal vascular network was obtained from the OCT angiography data using image processing techniques. By using experimentally-quantified flow in major retinal vessels as boundary conditions, the flow in each vessel branch down to the capillary level was inferred by modeling the vasculature as a resistive network.

Results: We present a 3D vectorized representation of the inner retinal vasculature, derived from OCT image data. We show computed vessel branch lengths and diameters, which are combined with the vectorized data to form a topologically accurate model of the retinal vasculature. We show capillary-level hemodynamics computed from this model, which could be directly cross-validated against other capillary speed and flow imaging metrics.

Conclusions: The image processing and modeling methods we have presented can yield accurate 3-D graphs that may be useful for general studies of retinal vasculature and metabolism. Vascular branching patterns within the capillary plexuses are also represented in great detail, which may open new possibilities for the investigation of neurovascular coupling and control in the retina. We anticipate that accurate biophysical models such as the one presented here, when informed by independent in vivo measurements of flow and metabolism, will advance our understanding of the relationship between flow, metabolism, and neuronal activity elsewhere in the central nervous system, and constitute a baseline to characterize changes in numerous retinal diseases.

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