Fiber-Based Ultra-High-Speed Diffuse Speckle Contrast Analysis System for Deep Blood Flow Sensing Using a Large SPAD Camera

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Fiber-Based Ultra-High-Speed Diffuse Speckle Contrast Analysis System for Deep Blood Flow Sensing Using a Large SPAD Camera
Title:
Fiber-Based Ultra-High-Speed Diffuse Speckle Contrast Analysis System for Deep Blood Flow Sensing Using a Large SPAD Camera
Journal Title:
Biosensors
Keywords:
Publication Date:
07 August 2025
Citation:
Wang, Q., Bi, R., Zheng, S., Erdogan, A. T., Qi, Y., Li, C., Hua, Y., Pan, M., Wang, Y., Finlayson, N., Olivo, M., Henderson, R. K., & Li, D. D.-U. (2025). Fiber-Based Ultra-High-Speed Diffuse Speckle Contrast Analysis System for Deep Blood Flow Sensing Using a Large SPAD Camera. Biosensors, 15(8), 514. https://doi.org/10.3390/bios15080514
Abstract:
Diffuse speckle contrast analysis (DSCA), also called speckle contrast optical spectroscopy (SCOS), has emerged as a groundbreaking optical imaging technique for tracking dynamic biological processes, including blood flow and tissue perfusion. Recent advancements in single-photon avalanche diode (SPAD) cameras have unlocked exceptional sensitivity, time resolution, and high frame-rate imaging capabilities. Despite this, the application of large-format SPAD arrays in speckle contrast analysis is still relatively uncommon. This study introduces a pioneering use of a large-format SPAD camera for DSCA. By harnessing the camera’s high temporal resolution and photon-detection efficiency, we significantly enhance the accuracy and robustness of speckle contrast measurements. Our experimental results demonstrate the system’s remarkable ability to capture rapid temporal variations over a broad field of view, enabling detailed spatiotemporal analysis. Through simulations, phantom experiments, and in vivo studies, we validated the proposed approach’s potential for cerebral blood flow and functional tissue monitoring. This work highlights the transformative impact of large SPAD cameras on DSCA, setting the stage for breakthroughs in optical imaging.
License type:
Attribution 4.0 International (CC BY 4.0)
Funding Info:
This research / project is supported by the A*STAR - Biomedical Engineering Programme
Grant Reference no. : C221318003

This work was supported in part by A*STAR BMRC Central Research fund 2024.
Description:
ISSN:
2079-6374
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