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Beneath the Surface: Revealing Deep-Tissue Blood Flow in Human Subjects with Massively Parallelized Diffuse Correlation Spectroscopy

Authors :
Kreiss, Lucas
Wu, Melissa
Wayne, Michael
Xu, Shiqi
McKee, Paul
Dwamena, Derrick
Kim, Kanghyun
Lee, Kyung Chul
Liu, Wenhui
Ulku, Aarin
Harfouche, Mark
Yang, Xi
Cook, Clare
Chaware, Amey
Lee, Seung Ah
Buckley, Erin
Bruschini, Claudio
Charbon, Edoardo
Huettel, Scott
Horstmeyer, Roarke
Publication Year :
2024

Abstract

Diffuse Correlation Spectroscopy (DCS) allows the label-free investigation of microvascular dynamics deep within living tissue. However, common implementations of DCS are currently limited to measurement depths of $\sim 1-1.5cm$, which can limit the accuracy of cerebral hemodynamics measurement. Here we present massively parallelized DCS (pDCS) using novel single photon avalanche detector (SPAD) arrays with up to 500x500 individual channels. The new SPAD array technology can boost the signal-to-noise ratio by a factor of up to 500 compared to single-pixel DCS, or by more than 15-fold compared to the most recent state-of-the-art pDCS demonstrations. Our results demonstrate the first in vivo use of this massively parallelized DCS system to measure cerebral blood flow changes at $\sim 2cm$ depth in human adults. We compared different modes of operation and applied a dual detection strategy, where a secondary SPAD array is used to simultaneously assess the superficial blood flow as a built-in reference measurement. While the blood flow in the superficial scalp tissue showed no significant change during cognitive activation, the deep pDCS measurement showed a statistically significant increase in the derived blood flow index of 8-12% when compared to the control rest state.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2403.03968
Document Type :
Working Paper