3D Retinal Vessel Density Mapping with OCT-Angiography

Mona Sharifi Sarabi, Maziyar M. Khansari, Jiong Zhang, Sam Kushner-Lenhoff, Jin Kyu Gahm, Yuchuan Qiao, Amir H. Kashani, Yonggang Shi

Research output: Contribution to journalArticlepeer-review

Abstract

Optical Coherence Tomography Angiography (OCTA) is a novel, non-invasive imaging modality of retinal capillaries at micron resolution. Recent studies have correlated macular OCTA vascular measures with retinal disease severity and supported their use as a diagnostic tool. However, these measurements mostly rely on a few summary statistics in retinal layers or regions of interest in the two-dimensional (2D) en face projection images. To enable 3D and localized comparisons of retinal vasculature between longitudinal scans and across populations, we develop a novel approach for mapping retinal vessel density from OCTA images. We first obtain a high-quality 3D representation of OCTA-based vessel networks via curvelet-based denoising and optimally oriented flux (OOF). Then, an effective 3D retinal vessel density mapping method is proposed. In this framework, a vessel density image (VDI) is constructed by diffusing the vessel mask derived from OOF-based analysis to the entire image volume. Subsequently, we utilize a non-linear, 3D OCT image registration method to provide localized comparisons of retinal vasculature across subjects. In our experimental results, we demonstrate an application of our method for longitudinal qualitative analysis of two pathological subjects with edema during the course of clinical care. Additionally, we quantitatively validate our method on synthetic data with simulated capillary dropout, a dataset obtained from a normal control (NC) population divided into two age groups and a dataset obtained from patients with diabetic retinopathy (DR). Our results show that we can successfully detect localized vascular changes caused by simulated capillary loss, normal aging, and DR pathology even in presence of edema. These results demonstrate the potential of the proposed framework in localized detection of microvascular changes and monitoring retinal disease progression.

Original languageEnglish (US)
Article number9194236
Pages (from-to)3466-3479
Number of pages14
JournalIEEE Journal of Biomedical and Health Informatics
Volume24
Issue number12
DOIs
StatePublished - Dec 2020
Externally publishedYes

Keywords

  • 3D image registration
  • Optical coherence tomography angiography
  • diabetic retinopathy
  • localized vessel density

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics
  • Electrical and Electronic Engineering
  • Health Information Management

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