Optical coherence tomography (OCT) is a novel high-resolution imaging technique capable of visualizing in vivo structures at a resolution of ~10 μm. We have developed specialized OCT-based approaches that quantify diameter, speed, and flow rate in human cutaneous microvessels. In this study, we hypothesized that OCT-based microvascular assessments would possess comparable levels of reliability when compared with those derived using conventional laser Doppler flowmetry (LDF).
Speckle decorrelation images (OCT) and red blood cell flux (LDF) measures were collected from adjacent forearm skin locations on 2 d (48 h apart), at baseline, and after a 30-min rapid local heating protocol (30°C–44°C) in eight healthy young individuals. OCT postprocessing quantified cutaneous microvascular diameter, speed, flow rate, and density (vessel recruitment) within a region of interest, and data were compared between days.
Forearm skin LDF (13 ± 4 to 182 ± 31 AU, P < 0.05) and OCT-derived diameter (41.8 ± 6.6 vs 64.5 ± 6.9 μm), speed (68.4 ± 9.5 vs 89.0 ± 7.3 μm·s−1), flow rate (145.0 ± 60.6 vs 485 ± 132 pL·s−1), and density (9.9% ± 4.9% vs 45.4% ± 5.9%) increased in response to local heating. The average OCT-derived microvascular flow response (pL·s−1) to heating (234% increase) was lower (P < 0.05) than the LDF-derived change (AU) (1360% increase). Pearson correlation was significant for between-day local heating responses in terms of OCT flow (r = 0.93, P < 0.01), but not LDF (P = 0.49). Bland–Altman analysis revealed that between-day baseline OCT-derived flow rates were less variable than LDF-derived flux.
Our findings indicate that OCT, which directly visualizes human microvessels, not only allows microvascular quantification of diameter, speed, flow rate, and vessel recruitment but also provides outputs that are highly reproducible. OCT is a promising novel approach that enables a comprehensive assessment of cutaneous microvascular structure and function in humans.
1Cardiovascular Research Group, School of Human Sciences (Exercise and Sport Science), Faculty of Science, The University of Western Australia, Perth, AUSTRALIA;
2School of Kinesiology, Faculty of Health and Behavioural Science, Lakehead University, Thunderbay, Ontario, CANADA;
3Department of Physiology, Faculty of Medicine, Airlangga University, Surabaya, INDONESIA;
4Australian Research Council Centre of Excellence for Nanoscale Biophotonics, Adelaide Medical School, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, AUSTRALIA;
5Institute for Photonics and Advanced Sensing, University of Adelaide, Adelaide, AUSTRALIA; and
6School of Electrical, Electronic and Computer Engineering, Faculty of Engineering and Mathematical Sciences, The University of Western Australia, Perth, AUSTRALIA
Address for correspondence: Winthrop Professor Daniel J. Green, Ph.D., School of Human Sciences (Exercise and Sport Science), The University of Western Australia, M408, 35 Stirling Highway, Perth 6009, Australia; E-mail: firstname.lastname@example.org.
K. J. S. and R A. contributed equally to this work.
Submitted for publication October 2018.
Accepted for publication January 2019.
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Online date: February 25, 2019