A comprehensive overview of diffuse correlation spectroscopy: Theoretical framework, recent advances in hardware, analysis, and applications
Quan Wang,
Mingliang Pan,
Lucas Kreiss,
Saeed Samaei,
Stefan A. Carp,
Johannes D. Johansson,
Yuanzhe Zhang,
Melissa Wu,
Roarke Horstmeyer,
Mamadou Diop,
David Day-Uei Li
Affiliations
Quan Wang
Department of Biomedical Engineering, Faculty of Engineering, University of Strathclyde, Glasgow, United Kingdom
Mingliang Pan
Department of Biomedical Engineering, Faculty of Engineering, University of Strathclyde, Glasgow, United Kingdom
Lucas Kreiss
Department of Biomedical Engineering, Duke University, Durham, NC, United States
Saeed Samaei
Department of Medical and Biophysics, Schulich School of Medical & Dentistry, Western University, London, Ontario, Canada; Lawson Health Research Institute, Imaging Program, London, Ontario, Canada
Stefan A. Carp
Massachusetts General Hospital, Optics at Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School, Charlestown, MA, United States
Johannes D. Johansson
Department of Biomedical Engineering, Linköping University, Linköping, Sweden
Yuanzhe Zhang
Department of Biomedical Engineering, Faculty of Engineering, University of Strathclyde, Glasgow, United Kingdom
Melissa Wu
Department of Biomedical Engineering, Duke University, Durham, NC, United States
Roarke Horstmeyer
Department of Biomedical Engineering, Duke University, Durham, NC, United States
Mamadou Diop
Department of Medical and Biophysics, Schulich School of Medical & Dentistry, Western University, London, Ontario, Canada; Lawson Health Research Institute, Imaging Program, London, Ontario, Canada
David Day-Uei Li
Department of Biomedical Engineering, Faculty of Engineering, University of Strathclyde, Glasgow, United Kingdom; Corresponding author.
Diffuse correlation spectroscopy (DCS) is a powerful tool for assessing microvascular hemodynamic in deep tissues. Recent advances in sensors, lasers, and deep learning have further boosted the development of new DCS methods. However, newcomers might feel overwhelmed, not only by the already-complex DCS theoretical framework but also by the broad range of component options and system architectures. To facilitate new entry to this exciting field, we present a comprehensive review of DCS hardware architectures (continuous-wave, frequency-domain, and time-domain) and summarize corresponding theoretical models. Further, we discuss new applications of highly integrated silicon single-photon avalanche diode (SPAD) sensors in DCS, compare SPADs with existing sensors, and review other components (lasers, sensors, and correlators), as well as data analysis tools, including deep learning. Potential applications in medical diagnosis are discussed and an outlook for the future directions is provided, to offer effective guidance to embark on DCS research.
