Diffuse optical methods have been used for more than 30 years to noninvasively quantify hemodynamics in the brain, skeletal muscles, and other tissues. In particular, near-infrared spectroscopy (NIRS) is widely adopted for cerebral oximetry clinical applications¹ and functional neuroimaging studies.² NIRS employs light in the red and near-infrared spectral region, between 650 and 900 nm, where overall tissue absorption is low and dominated by hemoglobin species while water absorption is not significant. This optical window permits light penetration of several centimeters into the tissue and high sensitivity to hemoglobin concentration changes. Diffuse correlation spectroscopy (DCS)^3,4 is another diffuse optical method that is rapidly growing and being employed in a range of biomedical applications.^{5 – 7} In DCS, a tissue of interest is illuminated by coherent near-infrared light, which causes a speckled interference pattern to form after the light scatters multiple times through the tissue. Dynamic scattering of the light by moving red blood cells causes the speckle pattern to fluctuate rapidly. These fluctuations are typically detected 2 to 3 cm away from the source and are quantified by measuring the temporal intensity autocorrelation curve, $g_2(\tau )=⟨I(t)I(t+\tau )⟩/{⟨I(\tau )⟩}^2$, of a single speckle. The decay of the autocorrelation curve is fit with the solution of the correlation diffusion equation⁴ to obtain an index of blood flow (${\mathrm{BF}}_i$) in units of ${\mathrm{cm}}^2/\mathrm{s}$. Although the units of ${\mathrm{BF}}_i$ are not the conventional units of $\mathrm{ml}/\min /100\mathrm{g}$ tissue for perfusion, ${\mathrm{BF}}_i$ has been shown to be reliably proportional to absolute flow, as demonstrated against “gold standards,” such as arterial spin-labeled MRI,^{8 – 10} fluorescent microspheres,¹¹ bolus tracking time-domain NIRS,^12,13 and phase-encoded velocity mapping MRI.¹⁴

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.

Diffuse correlation spectroscopy (DCS) is a non-invasive optical method for the measurement of blood flow (BF).¹ In DCS, the tissue is illuminated by a long coherence length near-infrared laser, and the speckle pattern formed by moving scatterers, mostly red blood cells, modulates the detected light. The decay of the measured temporal intensity autocorrelation function $[g_2(\tau )]$ originated by the speckle fluctuations provides an index of blood flow (${\mathrm{BF}}_{\mathrm{i}}$),² with units ${\mathrm{cm}}^2/\mathrm{s}$. To maximize the contrast of the measured speckle, single-mode fibers are used, greatly limiting potential photon throughput. Current DCS devices employing single-photon avalanche photodiodes (SPAD) detectors and laser sources at 700 to 850 nm typically operate at a source-detector (SD) separation of 25 mm and an acquisition rate of 1 Hz.³ Larger SD separations are desirable for improving brain sensitivity and reducing scalp signal contamination, especially in the adult population. Faster acquisition rates are needed to detect fast BF dynamics and effectively remove the large pulsatile systemic component from the cerebral signals. Unfortunately, the low signal-to-noise ratio (SNR) of current devices limits the acquisition rates and prevents the use of SD separations $>2.5\mathrm{cm}$.

Diffuse correlation spectroscopy (DCS) is an optical technique that measures the temporal fluctuations of multiply scattered light to characterize the displacement dynamics of scattering particles in the sample under interrogation.¹ By analyzing the time course of the measured intensity signal through the intensity autocorrelation, $g_2(\tau )$, measurements of blood flow can be derived by utilizing the correlation diffusion theory.² This technique has many benefits for clinical monitoring, including its noninvasive nature and its ability to allow for continuous monitoring. Blood flow measurements using DCS have been explored as a method to monitor cerebral blood flow at the bedside,^{3 – 5} to distinguishing benign and malignant breast cancer lesions,^6,7 and to monitor skeletal muscle physiology in exercise science.^{8 – 10} In all areas of application, the presence of intervening superficial layers can distort the DCS blood flow measurements of the tissue of interest (extracerebral layers for head measurements, subcutaneous fat for muscle measurements, and noninvolved breast tissue for the breast measurements). In the neuromonitoring arena, one of the most promising application areas, clinical translation of DCS has yet to be realized despite the benefits of the technique having been shown in several clinical conditions, including stroke, traumatic brain injury, hydrocephalus, and Alzheimer’s disease.^{11 – 14} This in part is due to difficulties in cerebral blood flow measurements in adults due to the significant thickness of the extracerebral layers.¹⁵

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.

Diffuse correlation spectroscopy (DCS), an optical technique that relies on sampling the intensity fluctuations of a speckle pattern set-up by diffusely scattered coherent light to quantify deep tissue blood flow, is seeing increased adoption as a non-invasive research tool for cerebral perfusion monitoring in clinical settings including critical care and sleep apnea, and for functional brain imaging.^{1 – 6} However, as usually implemented, DCS relies on the use of single or few-mode fibers to sample the speckle pattern in conjunction with photon counting detectors to construct the intensity temporal auto-correlation function, $g_2(\tau )$.⁷ This dramatically limits the photon throughput [e.g., in comparison with near-infrared spectroscopy (NIRS) where large area detectors and multi-mode fiber bundles can be used] and poses practical challenges to the use of DCS in translational studies. Consequently, substantial effort in the field is now dedicated to improving the signal-to-noise ratio (SNR) of diffuse optical blood flow measurements.⁸