Diffuse Correlation Spectroscopy
Diffuse Correlation Spectroscopy - Related Videos
02:31
Diffuse Correlation Spectroscopy to Assess Cerebral Blood Flow in a Mouse Model
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2025
In this video, we demonstrate the diffuse correlation spectroscopy technique to measure cerebral blood flow in a mouse model of mild traumatic brain injury.
05:09
Diffuse Correlation Spectroscopy to Measure Cerebral Blood Flow in a Human Subject
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2025
Source: Menezes Forti, R. et al. Real-Time Monitoring of Neurocritical Patients with Diffuse Optical Spectroscopies. J. Vis. Exp. (2020)This video demonstrates the use of Diffuse Correlation Spectroscopy (DCS) to measure cerebral blood flow in humans. It outlines the steps for preparing the system, calibrating the probe, positioning it on the participant’s forehead, acquiring scattered light data, and analyzing intensity fluctuations to interpret blood flow dynamics in the brain.
11:43
Easy Measurement of Diffusion Coefficients of EGFP-tagged Plasma Membrane Proteins Using k-Space Image Correlation Spectroscopy
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Cited by 37 •
2014
This paper provides a step by step guide to the fluctuation analysis technique k-Space Image Correlation Spectroscopy (kICS) for measuring diffusion coefficients of fluorescently labeled plasma membrane proteins in live mammalian cells.
12:06
Molecular Diffusion in Plasma Membranes of Primary Lymphocytes Measured by Fluorescence Correlation Spectroscopy
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Cited by 3 •
2017
A method to measure protein diffusion in membranes of primary immune cells using fluorescence correlation spectroscopy (FCS) is described. In this paper, the use of antibodies for fluorescent labeling is illustrated.
10:59
Determination of Lipid Raft Partitioning of Fluorescently-tagged Probes in Living Cells by Fluorescence Correlation Spectroscopy (FCS)
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Cited by 9 •
2012
A technique to probe the lipid raft partitioning of fluorescent proteins at the plasma membrane of living cells is described. It takes advantage of the disparity in diffusion times of proteins located inside or outside of lipid rafts. Acquisition can be performed dynamically in control conditions or after drug addition.
FAQs
Near-infrared light becomes diffusely scattered as it travels through tissue, producing a detected photon pattern that changes over time. Moving red blood cells contribute to these temporal fluctuations, while relatively stationary tissue contributes less change. DCS analyzes the fluctuation behavior and converts it into a blood-flow index, allowing physiological monitoring without surgical sampling.
Photon autocorrelation quantifies how detected light fluctuations relate to one another over time. Because red blood cell motion alters the scattered-light pattern, this analysis provides a structured way to interpret dynamic optical signals rather than relying on a single light-intensity measurement. The resulting blood-flow index supports assessment of changing perfusion in living tissue.
The blood-flow index summarizes the blood-flow dynamics inferred from temporal changes in diffusely scattered photons. It is not presented as a surgical sample or tracer-based measurement; instead, it provides an optical indicator of perfusion-related activity in tissue. This makes repeated physiological assessment possible while avoiding invasive sampling and injected tracers.
A measurement illuminates tissue with near-infrared light, collects the diffusely scattered photons, and evaluates their temporal fluctuations. Photon autocorrelation then processes those fluctuations to produce a blood-flow index. Because the approach is noninvasive and can provide continuous readings, the same general workflow can support bedside monitoring or measurements made during medical interventions.
The application depends on the physiological question. In the brain, DCS can support cerebral perfusion monitoring; in muscle, it can assess muscle hemodynamics; and in tumors, it can characterize blood flow. These settings make the technique relevant to brain-function research, vascular disease studies, treatment-response evaluation, and personalized patient monitoring.
Portable, continuous measurements allow blood-flow dynamics to be followed over time rather than assessed only through an isolated observation. This supports bedside use and monitoring during interventions, while also enabling studies of changing physiology in the brain, muscle, or tumors. Such data can contribute to research on treatment response, vascular disease, and individualized monitoring.