Pathlength-selective, interferometric diffuse correlation spectroscopy (PaLS-iDCS).

Diffuse correlation spectroscopy (DCS) is an optical method that offers non-invasive assessment of blood flow in tissue through the analysis of intensity fluctuations in diffusely backscattered coherent light. The non-invasive nature of the technique has enabled several clinical applications for deep tissue blood flow measurements, including cerebral blood flow monitoring as well as tumor blood flow mapping. While a promising technique, in measurement configurations targeting deep tissue hemodynamics, the standard DCS implementations suffer from insufficient signal-to-noise ratio (SNR), depth sensitivity, and sampling rate, limiting their utility. In this work, we present an enhanced DCS method called pathlength-selective, interferometric DCS (PaLS-iDCS), which improves upon both the sensitivity of the measurement to deep tissue hemodynamics and the SNR of the measurement using pathlength-specific coherent gain. Through interferometric detection, PaLS-iDCS can provide time-of-flight (ToF) specific blood flow information without the use of expensive time-tagging electronics and low-jitter detectors. The new technique is compared to time-domain DCS (TD-DCS), another enhanced DCS method able to resolve photon ToF in tissue, through Monte Carlo simulation, phantom experiments, and human subject measurements. PaLS-iDCS consistently demonstrates improvements in SNR (>2x) for similar measurement conditions (same photon ToF), and the SNR improvements allow for measurements at extended photon ToFs, which have increased sensitivity to deep tissue hemodynamics (~50% increase). Further, like TD-DCS, PaLS-iDCS allows direct estimation of tissue optical properties from the sampled ToF distribution without the need for a separate spectroscopic measurement. This method offers a relatively straightforward way to allow DCS systems to make robust measurements of blood flow with greatly enhanced sensitivity to deep tissue hemodynamics, enabling further applications of this non-invasive technology.

Choosing a camera and optimizing system parameters for speckle contrast optical spectroscopy.

Speckle contrast optical spectroscopy (SCOS) is an emerging camera-based technique that can measure human cerebral blood flow (CBF) with high signal-to-noise ratio (SNR). At low photon flux levels typically encountered in human CBF measurements, camera noise and nonidealities could significantly impact SCOS measurement SNR and accuracy. Thus, a guide for characterizing, selecting, and optimizing a camera for SCOS measurements is crucial for the development of next-generation optical devices for monitoring human CBF and brain function. Here, we provide such a guide and illustrate it by evaluating three commercially available complementary metal-oxide-semiconductor cameras, considering a variety of factors including linearity, read noise, and quantization distortion. We show that some cameras that are well-suited for general intensity imaging could be challenged in accurately quantifying spatial contrast for SCOS. We then determine the optimal operating parameters for the preferred camera among the three and demonstrate measurement of human CBF with this selected low-cost camera. This work establishes a guideline for characterizing and selecting cameras as well as for determining optimal parameters for SCOS systems.

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.

Multi-wavelength multi-distance diffuse correlation spectroscopy system for assessment of premature infants' cerebral hemodynamics.

Infants born at an extremely low gestational age (ELGA, < 29 weeks) are at an increased risk of intraventricular hemorrhage (IVH), and there is a need for standalone, safe, easy-to-use tools for monitoring cerebral hemodynamics. We have built a multi-wavelength multi-distance diffuse correlation spectroscopy device (MW-MD-DCS), which utilizes time-multiplexed, long-coherence lasers at 785, 808, and 853 nm, to simultaneously quantify the index of cerebral blood flow (CBFi) and the hemoglobin oxygen saturation (SO2). We show characterization data on liquid phantoms and demonstrate the system performance on the forearm of healthy adults, as well as clinical data obtained on two preterm infants.

Comparing the performance potential of speckle contrast optical spectroscopy and diffuse correlation spectroscopy for cerebral blood flow monitoring using Monte Carlo simulations in realistic head geometries.

Significance: The non-invasive measurement of cerebral blood flow based on diffuse optical techniques has seen increased interest as a research tool for cerebral perfusion monitoring in critical care and functional brain imaging. Diffuse correlation spectroscopy (DCS) and speckle contrast optical spectroscopy (SCOS) are two such techniques that measure complementary aspects of the fluctuating intensity signal, with DCS quantifying the temporal fluctuations of the signal and SCOS quantifying the spatial blurring of a speckle pattern. With the increasing interest in the use of these techniques, a thorough comparison would inform new adopters of the benefits of each technique. Aim: We systematically evaluate the performance of DCS and SCOS for the measurement of cerebral blood flow. Approach: Monte Carlo simulations of dynamic light scattering in an MRI-derived head model were performed. For both DCS and SCOS, estimates of sensitivity to cerebral blood flow changes, coefficient of variation of the measured blood flow, and the contrast-to-noise ratio of the measurement to the cerebral perfusion signal were calculated. By varying complementary aspects of data collection between the two methods, we investigated the performance benefits of different measurement strategies, including altering the number of modes per optical detector, the integration time/fitting time of the speckle measurement, and the laser source delivery strategy. Results: Through comparison across these metrics with simulated detectors having realistic noise properties, we determine several guiding principles for the optimization of these techniques and report the performance comparison between the two over a range of measurement properties and tissue geometries. We find that SCOS outperforms DCS in terms of contrast-to-noise ratio for the cerebral blood flow signal in the ideal case simulated here but note that SCOS requires careful experimental calibrations to ensure accurate measurements of cerebral blood flow. Conclusion: We provide design principles by which to evaluate the development of DCS and SCOS systems for their use in the measurement of cerebral blood flow.

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.

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.

Functional Time Domain Diffuse Correlation Spectroscopy.

Time-domain diffuse correlation spectroscopy (TD-DCS) offers a novel approach to high-spatial resolution functional brain imaging based on the direct quantification of cerebral blood flow (CBF) changes in response to neural activity. However, the signal-to-noise ratio (SNR) offered by previous TD-DCS instruments remains a challenge to achieving the high temporal resolution needed to resolve perfusion changes during functional measurements. Here we present a next-generation optimized functional TD-DCS system that combines a custom 1,064 nm pulse-shaped, quasi transform-limited, amplified laser source with a high-resolution time-tagging system and superconducting nanowire single-photon detectors (SNSPDs). System characterization and optimization was conducted on homogenous and two-layer intralipid phantoms before performing functional CBF measurements in six human subjects. By acquiring CBF signals at over 5 Hz for a late gate start time of the temporal point spread function (TPSF) at 15 mm source-detector separation, we demonstrate for the first time the measurement of blood flow responses to breath-holding and functional tasks using TD-DCS.

Diffuse Correlation Spectroscopy Beyond the Water Peak Enabled by Cross-Correlation of the Signals From InGaAs/InP Single Photon Detectors.

OBJECTIVE: Diffuse correlation spectroscopy (DCS) is an optical technique that allows for the non-invasive measurement of blood flow. Recent work has shown that utilizing longer wavelengths beyond the traditional NIR range provides a significant improvement to signal-to-noise ratio (SNR). However, current detectors both sensitive to longer wavelengths and suitable for clinical applications (InGaAs/InP SPADs) suffer from suboptimal afterpulsing and dark noise characteristics. To overcome these barriers, we introduce a cross correlation method to more accurately recover blood flow information using InGaAs/InP SPADs. METHODS: Two InGaAs/InP SPAD detectors were used for during in vitro and in vivo DCS measurements. Cross correlation of the photon streams from each detector was performed to calculate the correlation function. Detector operating parameters were varied to determine parameters which maximized measurement SNR.State-space modeling was performed to determine the detector characteristics at each operating point. RESULTS: Evaluation of detector characteristics was performed across the range of operating conditions. Modeling the effects of the detector noise on the correlation function provided a method to correct the distortion of the correlation curve, yielding accurate recovery of flow information as confirmed by a reference detector. CONCLUSION: Through a combination of cross-correlation of the signals from two detectors, model-based characterization of detector response, and optimization of detector operating parameters, the method allows for the accurate estimation of the true blood flow index. SIGNIFICANCE: This work presents a method by which DCS can be performed at longer NIR wavelengths with existing detector technology, taking advantage of the increased SNR.

Characterization of continuous wave ultrasound for acousto-optic modulated diffuse correlation spectroscopy (AOM-DCS).

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 performance of a visible wavelength optical sensor for monitoring intestinal perfusion and oxygenation.

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.

In-silico and in-vitro investigation of a photonic monitor for intestinal perfusion and oxygenation.

The quantification of visceral organ oxygenation after trauma-related systemic hypovolemia and shock is critical to enable effective resuscitation. In this work, a photoplethysmography-based (PPG) sensor was specifically designed for probing the perfusion and oxygenation condition of intestinal tissue with the ultimate goal to monitor patients post trauma to guide resuscitation. Through Monte Carlo modeling, suitable optofluidic phantoms were determined, the wavelength and separation distance for the sensor was optimized, and sensor performance for the quantification of tissue perfusion and oxygenation was tested on the in-vitro phantom. In particular, the Monte Carlo simulated both a standard block three-layer model and a more realistic model including villi. Measurements were collected on the designed three layer optofluidic phantom and the results taken with the small form factor PPG device showed a marked improvement when using shorter visible wavelengths over the more conventional longer visible wavelengths. Overall, in this work a Monte Carlo model was developed, an optofluidic phantom was built, and a small form factor PPG sensor was developed and characterized using the phantom for perfusion and oxygenation over the visible wavelength range. The results show promise that this small form factor PPG sensor could be used as a future guide to shock-related resuscitation.