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Blood Flow01:29

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Blood is pumped by the heart into the aorta, the largest artery in the body, and then into increasingly smaller arteries, arterioles, and capillaries. The velocity of blood flow decreases with increased cross-sectional blood vessel area. As blood returns to the heart through venules and veins, its velocity increases. The movement of blood is encouraged by smooth muscle in the vessel walls, the movement of skeletal muscle surrounding the vessels, and one-way valves that prevent backflow.
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Related Experiment Video

Updated: Mar 17, 2026

Spatial Temporal Analysis of Fieldwise Flow in Microvasculature
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Characterizing relationship between optical microangiography signals and capillary flow using microfluidic channels.

Woo June Choi1, Wan Qin1, Chieh-Li Chen2

  • 1Department of Bioengineering, University of Washington, 3720 15th NE, Seattle, WA 98195, USA; These authors contributed equally to this work.

Biomedical Optics Express
|July 23, 2016
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Summary

Optical microangiography (OMAG) now offers quantitative vascular flow assessment. This study develops a model correlating OMAG signals to flow metrics, validated with phantoms, paving the way for precise in vivo analysis.

Keywords:
(170.2655) Functional monitoring and imaging(170.4500) Optical coherence tomography(220.4000) Microstructure fabrication

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Area of Science:

  • Biomedical Optics
  • Medical Imaging
  • Fluid Dynamics

Background:

  • Optical microangiography (OMAG) visualizes micro-vascular flow in vivo.
  • Previous studies demonstrated a qualitative link between OMAG and flow, but lacked quantitative validation.

Purpose of the Study:

  • To establish a quantitative relationship between OMAG signals and blood flow.
  • To develop and validate an analytical model for OMAG signal interpretation.

Main Methods:

  • Developed a simplified analytical model for OMAG signal.
  • The model relates OMAG signal to particle number, OCT signal decorrelation, flow velocity, and imaging parameters.
  • Validated the model using microfluidic flow phantoms with controlled flow conditions.

Main Results:

  • The OMAG signal quantifies either flux (if OCT amplitudes are correlated) or concentration (if saturated).
  • Model predictions showed strong correlation with experimental flow metrics.
  • Demonstrated OMAG's potential for quantitative assessment of micro-vascular flow.

Conclusions:

  • The developed model provides a quantitative basis for OMAG interpretation.
  • OMAG is a promising tool for accurate in vivo assessment of vascular flow.
  • This work bridges the gap between qualitative observation and quantitative measurement in OMAG.