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Significance: The ability of diffuse correlation spectroscopy (DCS) to measure cerebral blood flow (CBF) in humans is hindered by the low signal-to-noise ratio (SNR) of the method. This limits the high acquisition rates needed to resolve dynamic flow changes and to optimally filter out large pulsatile oscillations and prevents the use of large source-detector separations (≥3 cm), which are needed to achieve adequate brain sensitivity in most adult subjects. Aim: To substantially improve SNR, we have built a DCS device that operates at 1064 nm and uses superconducting nanowire single-photon detectors (SNSPD). Approach: We compared the performances of the SNSPD-DCS in humans with respect to a typical DCS system operating at 850 nm and using silicon single-photon avalanche diode detectors. Results: At a 25-mm separation, we detected 13 ± 6 times more photons and achieved an SNR gain of 16 ± 8 on the forehead of 11 subjects using the SNSPD-DCS as compared to typical DCS. At this separation, the SNSPD-DCS is able to detect a clean pulsatile flow signal at 20 Hz in all subjects. With the SNSPD-DCS, we also performed measurements at 35 mm, showing a lower scalp sensitivity of 31 ± 6 % with respect to the 48 ± 8 % scalp sensitivity at 25 mm for both the 850 and 1064 nm systems. Furthermore, we demonstrated blood flow responses to breath holding and hyperventilation tasks. Conclusions: While current commercial SNSPDs are expensive, bulky, and loud, they may allow for more robust measures of non-invasive cerebral perfusion in an intensive care setting.

Significance: Diffuse correlation spectroscopy (DCS) is an established optical modality that enables noninvasive measurements of blood flow in deep tissue by quantifying the temporal light intensity fluctuations generated by dynamic scattering of moving red blood cells. Compared with near-infrared spectroscopy, DCS is hampered by a limited signal-to-noise ratio (SNR) due to the need to use small detection apertures to preserve speckle contrast. However, DCS is a dynamic light scattering technique and does not rely on hemoglobin contrast; thus, there are significant SNR advantages to using longer wavelengths (>1000 nm) for the DCS measurement due to a variety of biophysical and regulatory factors. Aim: We offer a quantitative assessment of the benefits and challenges of operating DCS at 1064 nm versus the typical 765 to 850 nm wavelength through simulations and experimental demonstrations. Approach: We evaluate the photon budget, depth sensitivity, and SNR for detecting blood flow changes using numerical simulations. We discuss continuous wave (CW) and time-domain (TD) DCS hardware considerations for 1064 nm operation. We report proof-of-concept measurements in tissue-like phantoms and healthy adult volunteers. Results: DCS at 1064 nm offers higher intrinsic sensitivity to deep tissue compared with DCS measurements at the typically used wavelength range (765 to 850 nm) due to increased photon counts and a slower autocorrelation decay. These advantages are explored using simulations and are demonstrated using phantom and in vivo measurements. We show the first high-speed (cardiac pulsation-resolved), high-SNR measurements at large source–detector separation (3 cm) for CW-DCS and late temporal gates (1 ns) for TD-DCS. Conclusions: DCS at 1064 nm offers a leap forward in the ability to monitor deep tissue blood flow and could be especially useful in increasing the reliability of cerebral blood flow monitoring in adults.

Diffuse correlation spectroscopy (DCS) is an established diffuse optical technique that uses the analysis of temporal speckle intensity fluctuations to measure blood flow in tissue. As a non-invasive technique, DCS has been used to monitor patient cerebral blood flow at the bedside. Though an effective measurement tool, extra-cerebral contamination of the DCS signal limits the sensitivity to changes in brain blood flow. In order to overcome this depth sensitivity challenge, we present a method, overlapping volumes, acousto-optic modulated DCS (AOM-DCS), to improve sensitivity to deeper tissue structures.

Intra and post-operative blood flow monitoring of tissue has been shown to be effective in the improvement of patient outcomes. Diffuse correlation spectroscopy (DCS) has been shown to be effective in measuring blood flow at the bedside, and is a useful technique in measuring cerebral blood flow (CBF) in many clinical settings. However, DCS suffers from reduced sensitivity to blood flow changes at larger tissue depths, making measurements of CBF in adults difficult. This issue can be addressed with acousto-optic modulated diffuse correlation spectroscopy (AOM-DCS), which is a hybrid technique that combines the sensitivity of DCS to blood flow with ultrasound resolution to allow for improved spatial resolution of the optical signal based on knowledge of the area which is insonified by ultrasound. We present a quantitative model for perfusion estimation based on AOM-DCS in the presence of continuous wave ultrasound, supported by theoretical derivations, Monte Carlo simulations, and phantom and human subject experiments. Quantification of the influence of individual mechanisms that contribute to the temporal fluctuations of the optical intensity due to ultrasound is shown to agree with previously derived results. By using this model, the recovery of blood-flow induced scatterer dynamics based on ultrasound-modulated light is shown to deviate by less than one percent from the standard DCS measurement of scatterer dynamics over a range of optical scattering values and scatterer motion conditions. This work provides an important step towards future implementation of AOM-DCS setups with more complex spatio-temporal distributions of ultrasound pressure, which are needed to enhance the DCS spatial resolution.

In-vivo, optical measurements of cerebral blood flow are confounded by superficial blood flow. Here, we present acousto-optic modulated diffuse correlation spectroscopy (AOM-DCS) for blood flow monitoring, showing good agreement between theoretical predictions and experimental results.

Diffuse correlation spectroscopy (DCS) is an emerging technology that allows for the quantitative estimation of blood flow in tissue. By monitoring the autocorrelation of the time course of light speckle intensity, information about the motion of scattering particles, mostly red blood cells in the microvasculature of biological tissues, can be determined. The speckle fluctuations are due to motion of scatters along the entire path length of the photon from the source to the detector, which makes the determination of the location of the motion a difficult task. Multi-distance and tomographic methods have been employed to measure decorrelation times at different source detector separations, which helps to separate superficial blood flow from blood flow deeper in the tissue. DCS in the time-domain (TD-DCS) is being evaluated as a method to increase depth sensitivity by considering only the late arriving photons. Depth resolved quantification of blood flow is especially important when blood flow measurements of the brain are desired, as the superficial blood flow of the scalp is a known contaminant to the cortical signal. Recent demonstrations by other groups have shown the utility of ultrasound tagging of light to be an effective method to discriminate flow at different depths.1 Here we utilize ultrasound pulses to modulate the motion of particles at specific depths, which is dependent upon the time-of-flight of the ultrasound pulse. By analyzing the autocorrelation of the speckle intensity at different delay periods after the pulse, quantitative, depth specific information about the flow can be determined. References: 1. Tsalach, A. et al. Depth selective acousto-optic flow measurement. Biomed. Opt. Express 6, 4871–86 (2015).

Traumatic injury resulting in hemorrhage is a prevalent cause of death worldwide. The current standard of care for trauma patients is to restore hemostasis by controlling bleeding and administering intravenous volume resuscitation. Adequate resuscitation to restore tissue blood flow and oxygenation is critical within the first hours following admission to assess severity and avoid complications. However, current clinical methods for guiding resuscitation are not sensitive or specific enough to adequately understand the patient condition. To better address the shortcomings of the current methods, an approach to monitor intestinal perfusion and oxygenation using a multiwavelength (470, 560, and 630 nm) optical sensor has been developed based on photoplethysmography and reflectance spectroscopy. Specifically, two sensors were developed using three wavelengths to measure relative changes in the small intestine. Using vessel occlusion, systemic changes in oxygenation input, and induction of hemorrhagic shock, the capabilities and sensitivity of the sensor were explored in vivo. Pulsatile and nonpulsatile components of the red, blue, and green wavelength signals were analyzed for all three protocols (occlusion, systemic oxygenation changes, and shock) and were shown to differentiate perfusion and oxygenation changes in the jejunum. The blue and green signals produced better correlation to perfusion changes during occlusion and shock, while the red and blue signals, using a new correlation algorithm, produced better data for assessing changes in oxygenation induced both systemically and locally during shock. The conventional modulation ratio method was found to be an ineffective measure of oxygenation in the intestine due to noise and an algorithm was developed based on the Pearson correlation coefficient. The method utilized the difference in phase between two different wavelength signals to assess oxygen content. A combination of measures from the three wavelengths provided verification of oxygenation and perfusion states, and showed promise for the development of a clinical monitor.