Paper
14 February 2018 Capillary red blood cell velocimetry by phase-resolved optical coherence tomography
Author Affiliations +
Abstract
Quantitative measurement of blood flow velocity in capillaries is challenging due to their small size (around 5-10 μm), and the discontinuity and single-file feature of RBCs flowing in a capillary. In this work, we present a phase-resolved Optical Coherence Tomography (OCT) method for accurate measurement of the red blood cell (RBC) speed in cerebral capillaries. To account for the discontinuity of RBCs flowing in capillaries, we applied an M-mode scanning strategy that repeated A-scans at each scanning position for an extended time. As the capillary size is comparable to the OCT resolution size (3.5×3.5×3.5μm), we applied a high pass filter to remove the stationary signal component so that the phase information of the dynamic component (i.e. from the moving RBC) could be enhanced to provide an accurate estimate of the RBC axial speed. The phase-resolved OCT method accurately quantifies the axial velocity of RBC’s from the phase shift of the dynamic component of the signal. We validated our measurements by RBC passage velocimetry using the signal magnitude of the same OCT time series data. These proposed method of capillary velocimetry proved to be a robust method of mapping capillary RBC speeds across the micro-vascular network.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jianbo Tang, Sefik Evren Erdener, Buyin Fu, and David A. Boas "Capillary red blood cell velocimetry by phase-resolved optical coherence tomography ", Proc. SPIE 10483, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXII, 104832W (14 February 2018); https://doi.org/10.1117/12.2290655
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Capillaries

Optical coherence tomography

Velocimetry

Phase shifts

Blood circulation

Signal detection

Linear filtering

Back to Top