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Blood Flow

Blood Flow

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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Updated: May 6, 2026

Doppler Optical Coherence Tomography of Retinal Circulation

Doppler Optical Coherence Tomography of Retinal Circulation

Published on: September 18, 2012

Time-Resolved Dynamic Optical Coherence Tomography for Retinal Blood Flow Analysis.

Philippe Valmaggia^1,2,3, Philippe C Cattin¹, Robin Sandkühler¹

¹Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland.

Investigative Ophthalmology & Visual Science

|June 5, 2024

Summary

This study introduces a new method using time-resolved structural Optical Coherence Tomography (OCT) to dynamically analyze retinal blood flow. The technique reveals pulsatile blood flow dynamics near the optic nerve head, offering potential for clinical insights.

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Last Updated: May 6, 2026

Doppler Optical Coherence Tomography of Retinal Circulation

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Published on: September 18, 2012

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Area of Science:

Ophthalmology
Biomedical Imaging
Medical Technology

Background:

Current Optical Coherence Tomography (OCT) provides static images, limiting dynamic blood flow visualization and quantification in the retina.
Assessing retinal blood flow is crucial for diagnosing and monitoring various ocular diseases.

Purpose of the Study:

To present a novel method for analyzing retinal blood flow dynamics using time-resolved structural OCT.
To enable dynamic visualization and quantification of blood flow, overcoming limitations of static OCT representations.

Main Methods:

Developed novel imaging protocols for video-rate time-resolved OCT B-scans at various sensor integration times.
Utilized a velocity model based on signal-to-noise ratio (SNR) drops due to fringe washout to calculate blood flow velocity.
Manually annotated vessel centers and extracted surrounding subvolumes for analysis.

Main Results:

Time-resolved dynamic structural OCT successfully revealed pulsatile SNR changes in retinal vessels.
Calculated potential blood flow velocities across all tested integration times.
Observed stronger fringe washout with longer integration times, yet consistent SNR ratios.

Conclusions:

Demonstrated the feasibility of estimating blood flow profiles using fringe washout analysis with structural OCT.
Showcased pulsatile dynamics in vessels near the optic nerve head.
Time-resolved dynamic OCT holds significant potential for uncovering valuable clinical blood flow information.