Laser & Optoelectronics Progress, Volume. 59, Issue 6, 0617006(2022)

Diffusion Correlation Spectroscopy for Tissue Blood Flow Monitoring and Its Clinical Applications

Zhe Li1,2,3、*, Jinchao Feng1,2,3、**, and Kebin Jia1,2,3、***
Author Affiliations
  • 1Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
  • 2Beijing Laboratory of Advanced Information Networks, Beijing 100124, China
  • 3Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing 100124, China
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    Diffusion correlation spectroscopy (DCS) is a relatively new methodology that has been extensively used for the noninvasive monitoring of tissue blood flow. This technology irradiates the tissue surface with near-infrared light, calculates the light intensity autocorrelation function of the scattered spot on the tissue surface, and computes the movement of red blood cells to realize the quantitative detection of blood flow changes in tissues. DCS measurements show more promise for the noninvasive, radiation-free, continuous and real-time monitoring, wide application range, and low detection requirements of tissue blood flow than the other blood flow monitoring methods such as laser Doppler flowmetry (LDF), magnetic resonance imaging (MRI), and positron emission tomography (PET). Moreover, DCS technology can be utilized for the bedside monitoring of tissue blood flow. The DCS technique is mainly introduced in which its theoretical background, instrumentation, progress, and clinical applications are included, as well as its future development prospects are discussed.

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    Zhe Li, Jinchao Feng, Kebin Jia. Diffusion Correlation Spectroscopy for Tissue Blood Flow Monitoring and Its Clinical Applications[J]. Laser & Optoelectronics Progress, 2022, 59(6): 0617006

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    Paper Information

    Category: Medical Optics and Biotechnology

    Received: Dec. 17, 2021

    Accepted: Jan. 17, 2022

    Published Online: Mar. 8, 2022

    The Author Email: Zhe Li (lizhe1023@bjut.edu.cn), Jinchao Feng (fengjc@bjut.edu.cn), Kebin Jia (kebinj@bjut.edu.cn)

    DOI:10.3788/LOP202259.0617006

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