Kuan Cheng Wu, Alyssa Martin, Marco Renna, Mitchell Robinson, Nisan Ozana, Stefan A Carp, Maria Angela Franceschini
Significance: Combining near-infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS) allows for quantifying cerebral blood volume, flow, and oxygenation changes continuously and non-invasively. As recently shown, the DCS pulsatile cerebral blood flow index () can be used to quantify critical closing pressure (CrCP) and cerebrovascular resistance ().
Aim: Although current DCS technology allows for reliable monitoring of the slow hemodynamic changes, resolving pulsatile blood flow at large source-detector separations, which is needed to ensure cerebral sensitivity, is challenging because of its low signal-to-noise ratio (SNR). Cardiac-gated averaging of several arterial pulse cycles is required to obtain a meaningful waveform.
Approach: Taking advantage of the high SNR of NIRS, we demonstrate a method that uses the NIRS photoplethysmography (NIRS-PPG) pulsatile signal to model DCS , reducing the coefficient of variation of the recovered pulsatile waveform () and allowing for an unprecedented temporal resolution (266 Hz) at a large source-detector separation ().
Results: In 10 healthy subjects, we verified the quality of the NIRS-PPG during common tasks, showing high fidelity against ( ). We recovered CrCP and at 0.25 Hz, times faster than previously achieved with DCS.
Conclusions: NIRS-PPG improves DCS SNR, reducing the number of gate-averaged heartbeats required to recover CrCP and .
