Functional Time Domain Diffuse Correlation Spectroscopy

Interferometric near-infrared spectroscopy (iNIRS) reveals that blood flow index depends on wavelength

Blood flow index (BFI) is an optically accessible parameter, with unit distance-squared-over-time, that is widely used as a proxy for tissue perfusion. BFI is defined as the dynamic scattering probability (i.e. the ratio of dynamic to overall reduced scattering coefficients) times an effective Brownian diffusion coefficient that describes red blood cell (RBC) motion. Here, using a wavelength division multiplexed, time-of-flight- (TOF) - resolved iNIRS system, we obtain TOF-resolved field autocorrelations at 773 nm and 855 nm via the same source and collector. We measure the human forearm, comprising biological tissues with mixed static and dynamic scattering, as well as a purely dynamic scattering phantom. Our primary finding is that forearm BFI increases from 773 nm to 855 nm, though the magnitude of this increase varies across subjects (23% ± 19% for N = 3). However, BFI is wavelength-independent in the purely dynamic scattering phantom. From these data, we infer that the wavelength-dependence of BFI arises from the wavelength-dependence of the dynamic scattering probability. This inference is further supported by RBC scattering literature. Our secondary finding is that the higher-order cumulant terms of the mean squared displacement (MSD) of RBCs are significant, but decrease with wavelength. Thus, laser speckle and related modalities should exercise caution when interpreting field autocorrelations.

Measuring pulsatile cortical blood flow and volume during carotid endarterectomy

Carotid endarterectomy (CEA) involves removal of plaque in the carotid artery to reduce the risk of stroke and improve cerebral perfusion. This study aimed to investigate the utility of assessing pulsatile blood volume and flow during CEA. Using a combined near-infrared spectroscopy/diffuse correlation spectroscopy instrument, pulsatile hemodynamics were assessed in 12 patients undergoing CEA. Alterations to pulsatile amplitude, pulse transit time, and beat morphology were observed in measurements ipsilateral to the surgical side. The additional information provided through analysis of pulsatile hemodynamic signals has the potential to enable the discovery of non-invasive biomarkers related to cortical perfusion.

Fast time-domain diffuse correlation spectroscopy with superconducting nanowire single-photon detector: system validation and in vivo results

Time-domain diffuse correlation spectroscopy (TD-DCS) has been introduced as an advancement of the "classical" continuous wave DCS (CW-DCS) allowing one to not only to measure depth-resolved blood flow index (BFI) but also to extract optical properties of the measured medium without using any additional diffuse optics technique. However, this method is a photon-starved technique, specially when considering only the late photons that are of primary interest which has limited its in vivo application. In this work, we present a TD-DCS system based on a superconducting nanowire single-photon detector (SNSPD) with a high quantum efficiency, a narrow timing response, and a negligibly low dark count noise. We compared it to the typically used single-photon avalanche diode (SPAD) detector. In addition, this system allowed us to conduct fast in vivo measurements and obtain gated pulsatile BFI on the adult human forehead.

Portable, high speed blood flow measurements enabled by long wavelength, interferometric diffuse correlation spectroscopy (LW-iDCS)

Diffuse correlation spectroscopy (DCS) is an optical technique that can be used to characterize blood flow in tissue. The measurement of cerebral hemodynamics has arisen as a promising use case for DCS, though traditional implementations of DCS exhibit suboptimal signal-to-noise ratio (SNR) and cerebral sensitivity to make robust measurements of cerebral blood flow in adults. In this work, we present long wavelength, interferometric DCS (LW-iDCS), which combines the use of a longer illumination wavelength (1064 nm), multi-speckle, and interferometric detection, to improve both cerebral sensitivity and SNR. Through direct comparison with long wavelength DCS based on superconducting nanowire single photon detectors, we demonstrate an approximate 5× improvement in SNR over a single channel of LW-DCS in the measured blood flow signals in human subjects. We show equivalence of extracted blood flow between LW-DCS and LW-iDCS, and demonstrate the feasibility of LW-iDCS measured at 100 Hz at a source-detector separation of 3.5 cm. This improvement in performance has the potential to enable robust measurement of cerebral hemodynamics and unlock novel use cases for diffuse correlation spectroscopy.

Interferometric diffusing wave spectroscopy imaging with an electronically variable time-of-flight filter

Diffuse optics (DO) is a light-based technique used to study the human brain, but it suffers from low brain specificity. Interferometric diffuse optics (iDO) promises to improve the quantitative accuracy and depth specificity of DO, and particularly, coherent light fluctuations (CLFs) arising from blood flow. iDO techniques have alternatively achieved either time-of-flight (TOF) discrimination or highly parallel detection, but not both at once. Here, we break this barrier with a single iDO instrument. Specifically, we show that rapid tuning of a temporally coherent laser during the sensor integration time increases the effective linewidth seen by a highly parallel interferometer. Using this concept to create a continuously variable and user-specified TOF filter, we demonstrate a solution to the canonical problem of DO, measuring optical properties. Then, with a deep TOF filter, we reduce scalp sensitivity of CLFs by 2.7 times at 1 cm source-collector separation. With this unique combination of desirable features, i.e., TOF-discrimination, spatial localization, and highly parallel CLF detection, we perform multiparametric imaging of light intensities and CLFs via the human forehead.

Diffuse correlation spectroscopy: current status and future outlook

Diffuse correlation spectroscopy (DCS) has emerged as a versatile, noninvasive method for deep tissue perfusion assessment using near-infrared light. A broad class of applications is being pursued in neuromonitoring and beyond. However, technical limitations of the technology as originally implemented remain as barriers to wider adoption. A wide variety of approaches to improve measurement performance and reduce cost are being explored; these include interferometric methods, camera-based multispeckle detection, and long path photon selection for improved depth sensitivity. We review here the current status of DCS technology and summarize future development directions and the challenges that remain on the path to widespread adoption.

Continuous-wave parallel interferometric near-infrared spectroscopy (CW NIRS) with a fast two-dimensional camera

Interferometric near-infrared spectroscopy (iNIRS) is an optical method that noninvasively measures the optical and dynamic properties of the human brain in vivo. However, the original iNIRS technique uses single-mode fibers for light collection, which reduces the detected light throughput. The reduced light throughput is compensated by the relatively long measurement or integration times (∼1 sec), which preclude monitoring of rapid blood flow changes that could be linked to neural activation. Here, we propose parallel interferometric near-infrared spectroscopy (πNIRS) to overcome this limitation. In πNIRS we use multi-mode fibers for light collection and a high-speed, two-dimensional camera for light detection. Each camera pixel acts effectively as a single iNIRS channel. So, the processed signals from each pixel are spatially averaged to reduce the overall integration time. Moreover, interferometric detection provides us with the unique capability of accessing complex information (amplitude and phase) about the light remitted from the sample, which with more than 8000 parallel channels, enabled us to sense the cerebral blood flow with only a 10 msec integration time (∼100x faster than conventional iNIRS). In this report, we have described the theoretical foundations and possible ways to implement πNIRS. Then, we developed a prototype continuous wave (CW) πNIRS system and validated it in liquid phantoms. We used our CW πNIRS to monitor the pulsatile blood flow in a human forearm in vivo. Finally, we demonstrated that CW πNIRS could monitor activation of the prefrontal cortex by recording the change in blood flow in the forehead of the subject while he was reading an unknown text.