Enhanced quantification of retinal perfusion by improved discrimination of blood flow from bulk motion signal in OCTA

Acner Camino, Miao Zhang, Liang Liu, Jie Wang, Jia Yali, David Huang

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Purpose: Quantification of optical coherence tomography angiography (OCTA) is confounded by the prevalence of bulk motion. We have previously developed a regression-based bulk motion subtraction (rb-BMS) algorithm that estimates bulk motion velocity and corrects for its effect on flow signal. Here, we aim to investigate its ability to improve the reliability of capillary density (CD) quantification. Methods: Two spectral-domain systems (70-kHz Avanti/AngioVue and 68-kHz Cirrus/ AngioPlex) acquired 6 × 6-mm OCTA scans. The rb-BMS algorithm was applied on each OCTA volume. Regression analysis of angiographic versus reflectance signal of avascular A-lines in B-frames was used to set an optimized reflectance-adjusted threshold for discriminating vascular versus nonvascular voxels. The CD was calculated from en face maximum projections of the superficial vascular complex in macular scans and the nerve fiber layer plexus in disc scans, excluding large vessels. The retinal signal strength (RSS) was calculated by averaging the logarithmic-scale OCT reflectance signal, and its correlation with CD was investigated. Results: Eight healthy eyes were scanned with each instrument on 2 separate days. The rb-BMS algorithm improved within-visit repeatability and between-visit reproducibility of CD compared with a global-threshold measurement algorithm. Using the rb-BMS algorithm, the CD results were less affected by RSS and the population variation was reduced. Motion-induced line artifacts were also reduced. Conclusions: The rb-BMS algorithm improved the reliability of perfusion quantification in OCTA on both Food and Drug Administration–cleared spectral-domain OCTA systems. Translational Relevance: The rb-BMS method helped reduce the inter-scan variability by generating accurate vessel maps, improving the reliability of retinal perfusion quantification.

Original languageEnglish (US)
Article number20
JournalTranslational Vision Science and Technology
Volume7
Issue number6
DOIs
StatePublished - Nov 1 2018

Fingerprint

Angiography
Optical tomography
Optical Coherence Tomography
Blood
Perfusion
Blood Vessels
Regression analysis
Nerve Fibers
Artifacts
Fibers
Regression Analysis
Food

Keywords

  • Motion artifacts
  • OCTA
  • Vessel density

ASJC Scopus subject areas

  • Biomedical Engineering
  • Ophthalmology

Cite this

Enhanced quantification of retinal perfusion by improved discrimination of blood flow from bulk motion signal in OCTA. / Camino, Acner; Zhang, Miao; Liu, Liang; Wang, Jie; Yali, Jia; Huang, David.

In: Translational Vision Science and Technology, Vol. 7, No. 6, 20, 01.11.2018.

Research output: Contribution to journalArticle

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