Using optical fibers with different modes to improve the signal-to-noise ratio of diffuse correlation spectroscopy flow-oximeter measurements

A comprehensive overview of diffuse correlation spectroscopy: Theoretical framework, recent advances in hardware, analysis, and applications

Diffuse correlation spectroscopy (DCS) is a powerful tool for assessing microvascular hemodynamic in deep tissues. Recent advances in sensors, lasers, and deep learning have further boosted the development of new DCS methods. However, newcomers might feel overwhelmed, not only by the already-complex DCS theoretical framework but also by the broad range of component options and system architectures. To facilitate new entry to this exciting field, we present a comprehensive review of DCS hardware architectures (continuous-wave, frequency-domain, and time-domain) and summarize corresponding theoretical models. Further, we discuss new applications of highly integrated silicon single-photon avalanche diode (SPAD) sensors in DCS, compare SPADs with existing sensors, and review other components (lasers, sensors, and correlators), as well as data analysis tools, including deep learning. Potential applications in medical diagnosis are discussed and an outlook for the future directions is provided, to offer effective guidance to embark on DCS research.

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.

Comparison of numerical-integration-based methods for blood flow estimation in diffuse correlation spectroscopy

BACKGROUND AND OBJECTIVE

Diffuse correlation spectroscopy (DCS) is an optical blood flow monitoring technology that has been utilized in various biomedical applications. In signal processing of DCS, nonlinear fitting of the experimental data and the theoretical model can be a hindrance in real-time blood flow monitoring. As one of the approaches to resolve the issue, INISg1, the inverse of numerical integration of squared g1 (a normalized electric field autocorrelation function), that could surpass the state-of-the-art technique at the time in terms of signal processing speed, has been introduced. While it is possible to implement INISg1 using various numerical integration methods, no relevant studies have been performed. Meanwhile, INISg1 was only tested within limited experimental conditions, which cannot guarantee the robustness of INISg1 in various experimental conditions. Thus, this study aims to introduce variants of INISg1 and perform a thorough comparison of the original INISg1 and its variants.

METHODS

In this study, based on the right Riemann sum (RR) and trapezoid rule (TR) of numerical integration, INISg1_RR and INISg1_TR are suggested. They are thoroughly compared with the original INISg1 using model-based simulations that offer us control of most of the experimental conditions, including integration time, β, and photon count rate.

RESULTS

Except for some extreme cases, INISg1 performed more robustly than INISg1_RR and INISg1_TR. However, in extreme conditions, variants of INISg1 performed better than INISg1. With the same condition, the signal processing speed of INISg1 was 1.63 and 1.98 times faster than INISg1_RR and INISg1_TR, respectively.

CONCLUSION

This study shows that INISg1 is robust in most cases and the study can be a guide for researchers using INISg1 and its variants in different types of DCS applications.

Diffuse optical detection of global cerebral ischemia in an adult porcine model

Rapid screening for ischemic strokes in prehospital settings may improve patient outcomes by allowing early deployment of vascular recanalization therapies. However, there are no low-cost and convenient methods that can assess ischemic strokes in such a setting. Diffuse correlation spectroscopy (DCS) is a promising method for continuous, noninvasive transcranial monitoring of cerebral blood flow. In this study, we used a DCS system to detect cerebral hemodynamics before and after acute ischemic stroke in pigs. Seven adult porcines were chosen to establish ischemic stroke models via bilateral common carotid artery ligation (n = 5) or air emboli (n = 2). The results showed a significant difference in blood flow index (BFI) between the normal and ischemic groups. Relative blood flow index (rBFI) exhibited excellent results. Therefore, the diffuse optical method can assess the hemodynamic changes in acute cerebral ischemic stroke onset in pigs, and rBFI may be a promising biomarker for identifying cerebral ischemic stroke.

Multi-mode fiber-based speckle contrast optical spectroscopy: analysis of speckle statistics

Speckle contrast optical spectroscopy/tomography (SCOS/T) provides a real-time, non-invasive, and cost-efficient optical imaging approach to mapping of cerebral blood flow. By measuring many speckles (n>>10), SCOS/T has an increased signal-to-noise ratio relative to diffuse correlation spectroscopy, which measures one or a few speckles. However, the current free-space SCOS/T designs are not ideal for large field-of-view imaging in humans because the curved head contour cannot be readily imaged with a single flat sensor and hair obstructs optical access. Herein, we evaluate the feasibility of using cost-efficient multi-mode fiber (MMF) bundles for use in SCOS/T systems. One challenge with speckle contrast measurements is the potential for confounding noise sources (e.g., shot noise, readout noise) which contribute to the standard deviation measure and corrupt the speckle contrast measure that is central to the SCOS/T systems. However, for true speckle measurements, the histogram of pixel intensities from light interference follows a non-Gaussian distribution, specifically a gamma distribution with non-zero skew, whereas most noise sources have pixel intensity distributions that are Gaussian. By evaluating speckle data from static and dynamic targets imaged through an MMF, we use histograms and statistical analysis of pixel histograms to evaluate whether the statistical properties of the speckles are retained. We show that flow-based speckle can be distinguished from static speckle and from sources of system noise through measures of skew in the pixel intensity histograms. Finally, we illustrate in humans that MMF bundles relay blood flow information.

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.

Cerebrovascular impedance estimation with near-infrared and diffuse correlation spectroscopy

SIGNIFICANCE

Cerebrovascular impedance (CVI) is related to cerebral autoregulation (CA), which is the mechanism of the brain to maintain near-constant cerebral blood flow (CBF) despite changes in cerebral perfusion pressure (CPP). Changes in blood vessel impedance enable the stabilization of blood flow. Due to the interplay between CVI and CA, assessment of CVI may enable quantification of CA and may serve as a biomarker for cerebral health.

AIM

We developed a method to quantify CVI based on a combination of diffuse correlation spectroscopy (DCS) and continuous wave (CW) near-infrared spectroscopy (NIRS). Data on healthy human volunteers were used to validate the method.

APPROACH

A combined high-speed DCS-NIRS system was developed, allowing for simultaneous, noninvasive blood flow, and volume measurements in the same tissue compartment. Blood volume was used as a surrogate measurement for blood pressure and CVI was calculated as the spectral ratio of blood volume and blood flow changes. This technique was validated on six healthy human volunteers undergoing postural changes to elicit CVI changes.

RESULTS

Averaged across the six subjects, a decrease in CVI was found for a head of bed (HOB) tilting of - 40    deg . These impedance changes were reversed when returning to the horizontal (0 deg) HOB baseline.

CONCLUSIONS

We developed a combined DCS-NIRS system, which measures CBF and volume changes, which we demonstrate can be used to measure CVI. Using CVI as a metric of CA may be beneficial for assessing cerebral health, especially in patients where CPP is altered.

Blood flow estimation via numerical integration of temporal autocorrelation function in diffuse correlation spectroscopy

BACKGROUND AND OBJECTIVE

Diffuse correlation spectroscopy (DCS) is an optical technique widely used to monitor blood flow. Recently, efforts have been made to derive new signal processing methods to minimize the systems used and shorten the signal processing time. Herein, we propose alternative approaches to obtain blood flow information via DCS by numerically integrating the temporal autocorrelation curves.

METHODS

We use the following methods: the inverse of K² (IK2)-based on the framework of diffuse speckle contrast analysis-and the inverse of the numerical integration of squared g₁ (INISg1) which, based on the normalized electric field autocorrelation curve, is more simplified than IK2. In addition, g₁ thresholding is introduced to further reduce computational time and make the suggested methods comparable to the conventional nonlinear fitting approach. To validate the feasibility of the suggested methods, studies using simulation, liquid phantom, and in vivo settings were performed. In the meantime, the suggested methods were implemented and tested on three types of Arduino (Arduino Due, Arduino Nano 33 BLE Sense, and Portenta H7) to demonstrate the possibility of miniaturizing the DCS systems using microcotrollers for signal processing.

RESULTS

The simulation and experimental results confirm that both IK2 and INISg1 are sufficiently relevant to capture the changes in blood flow information. More interestingly, when g₁ thresholding was applied, our results showed that INISg1 outperformed IK2. It was further confirmed that INISg1 with g₁ thresholding implemented on a PC and Portenta H7, an advanced Arduino board, performed faster than did the deep learning-based, state-of-the-art processing method.

CONCLUSION

Our findings strongly indicate that INISg1 with g₁ thresholding could be an alternative approach to derive relative blood flow information via DCS, which may contribute to the simplification of DCS methodologies.

Non-Invasive Blood Flow Speed Measurement Using Optics

Non-invasive measurement of the arterial blood speed gives important health information such as cardio output and blood supplies to vital organs. The magnitude and change in arterial blood speed are key indicators of the health conditions and development and progression of diseases. We demonstrated a simple technique to directly measure the blood flow speed in main arteries based on the diffused light model. The concept is demonstrated with a phantom that uses intralipid hydrogel to model the biological tissue and an embedded glass tube with flowing human blood to model the blood vessel. The correlation function of the measured photocurrent was used to find the electrical field correlation function via the Siegert relation. We have shown that the characteristic decorrelation rate (i.e., the inverse of the decoherent time) is linearly proportional to the blood speed and independent of the tube diameter. This striking property can be explained by an approximate analytic solution for the diffused light equation in the regime where the convective flow is the dominating factor for decorrelation. As a result, we have demonstrated a non-invasive method of measuring arterial blood speed without any prior knowledge or assumption about the geometric or mechanic properties of the blood vessels.

Recipes for diffuse correlation spectroscopy instrument design using commonly utilized hardware based on targets for signal-to-noise ratio and precision

Over the recent years, a typical implementation of diffuse correlation spectroscopy (DCS) instrumentation has been adapted widely. However, there are no detailed and accepted recipes for designing such instrumentation to meet pre-defined signal-to-noise ratio (SNR) and precision targets. These require specific attention due to the subtleties of the DCS signals. Here, DCS experiments have been performed using liquid tissue simulating phantoms to study the effect of the detected photon count-rate, the number of parallel detection channels and the measurement duration on the precision and SNR to suggest scaling relations to be utilized for device design.

Functional interferometric diffusing wave spectroscopy of the human brain

Cerebral blood flow (CBF) is essential for brain function, and CBF-related signals can inform us about brain activity. Yet currently, high-end medical instrumentation is needed to perform a CBF measurement in adult humans. Here, we describe functional interferometric diffusing wave spectroscopy (fiDWS), which introduces and collects near-infrared light via the scalp, using inexpensive detector arrays to rapidly monitor coherent light fluctuations that encode brain blood flow index (BFI), a surrogate for CBF. Compared to other functional optical approaches, fiDWS measures BFI faster and deeper while also providing continuous wave absorption signals. Achieving clear pulsatile BFI waveforms at source-collector separations of 3.5 cm, we confirm that optical BFI, not absorption, shows a graded hypercapnic response consistent with human cerebrovascular physiology, and that BFI has a better contrast-to-noise ratio than absorption during brain activation. By providing high-throughput measurements of optical BFI at low cost, fiDWS will expand access to CBF.

Time resolved speckle contrast optical spectroscopy at quasi-null source-detector separation for non-invasive measurement of microvascular blood flow

Time (or path length) resolved speckle contrast optical spectroscopy (TD-SCOS) at quasi-null (2.85 mm) source-detector separation was developed and demonstrated. The method was illustrated by in vivo studies on the forearm muscle of an adult subject. The results have shown that selecting longer photon path lengths results in higher hyperemic blood flow change and a faster return to baseline by a factor of two after arterial cuff occlusion when compared to SCOS without time resolution. This indicates higher sensitivity to the deeper muscle tissue. In the long run, this approach may allow the use of simpler and cheaper detector arrays compared to time resolved diffuse correlation spectroscopy that are based on readily available technologies. Hence, TD-SCOS may increase the performance and decrease cost of devices for continuous non-invasive, deep tissue blood flow monitoring.

Fourier domain diffuse correlation spectroscopy with heterodyne holographic detection

We present a new approach to diffuse correlation spectroscopy which overcomes the limited light throughput of single-mode photon counting techniques. Our system employs heterodyne holographic detection to allow parallel measurement of the power spectrum of a fluctuating electric field across thousands of modes, at the shot noise limit, using a conventional sCMOS camera. This yields an order of magnitude reduction in detector cost compared to conventional techniques, whilst also providing robustness to the effects of ambient light and an improved signal-to-noise ratio during in vitro experiments. We demonstrate a GPU-accelerated holographic demodulation system capable of processing the incoming data (79.4 M pixels per second) in real-time, and a novel Fourier domain model of diffuse correlation spectroscopy which permits the direct recovery of flow parameters from the measured data. Our detection and modelling strategy are rigorously validated by modulating the Brownian component of an optical tissue phantom, demonstrating absolute measurements of the Brownian diffusion coefficient in excellent agreement with conventional methods. We further demonstrate the feasibility of our system through in vivo measurement of pulsatile flow rates measured in the human forearm.

Diffuse optical assessment of cerebral-autoregulation in older adults stratified by cerebrovascular risk

Diagnosis of cerebrovascular disease (CVD) at early stages is essential for preventing sequential complications. CVD is often associated with abnormal cerebral microvasculature, which may impact cerebral-autoregulation (CA). A novel hybrid near-infrared diffuse optical instrument and a finger plethysmograph were used to simultaneously detect low-frequency oscillations (LFOs) of cerebral blood flow (CBF), oxy-hemoglobin concentration ([HbO₂ ]), deoxy-hemoglobin concentration ([Hb]) and mean arterial pressure (MAP) in older adults before, during and after 70° head-up-tilting (HUT). The participants with valid data were divided based on Framingham risk score (FRS, 1-30 points) into low-risk (FRS ≤15, n = 13) and high-risk (FRS >15, n = 11) groups for developing CVD. The LFO gains were determined by transfer function analyses with MAP as the input, and CBF, [HbO₂ ] and [Hb] as the outputs (CA ∝ 1/Gain). At resting-baseline, LFO gains in the high-risk group were relatively lower compared to the low-risk group. The lower baseline gains in the high-risk group may attribute to compensatory mechanisms to maintain stronger steady-state CAs. However, HUT resulted in smaller gain reductions in the high-risk group compared to the low-risk group, suggesting weaker dynamic CAs. LFO gains are potentially valuable biomarkers for early detection of CVD based on associations with CAs.

High-sensitivity multispeckle diffuse correlation spectroscopy

Significance: Cerebral blood flow is an important biomarker of brain health and function as it regulates the delivery of oxygen and substrates to tissue and the removal of metabolic waste products. Moreover, blood flow changes in specific areas of the brain are correlated with neuronal activity in those areas. Diffuse correlation spectroscopy (DCS) is a promising noninvasive optical technique for monitoring cerebral blood flow and for measuring cortex functional activation tasks. However, the current state-of-the-art DCS adoption is hindered by a trade-off between sensitivity to the cortex and signal-to-noise ratio (SNR). Aim: We aim to develop a scalable method that increases the sensitivity of DCS instruments. Approach: We report on a multispeckle DCS (mDCS) approach that is based on a 1024-pixel single-photon avalanche diode (SPAD) camera. Our approach is scalable to > 100,000 independent speckle measurements since large-pixel-count SPAD cameras are becoming available, owing to the investments in LiDAR technology for automotive and augmented reality applications. Results: We demonstrated a 32-fold increase in SNR with respect to traditional single-speckle DCS. Conclusion: A mDCS system that is based on a SPAD camera serves as a scalable method toward high-sensitivity DCS measurements, thus enabling both high sensitivity to the cortex and high SNR.

Fast pulsatile blood flow measurement in deep tissue through a multimode detection fiber

SIGNIFICANCE

Noninvasive in vivo fast pulsatile blood flow measurement in deep tissue is important because the blood flow waveform is correlated with physiological parameters, such as blood pressure and elasticity of blood vessels. Compromised blood flow may cause diseases, such as stroke, foot ulcer, and myocardial ischemia. There is great clinical demand for a portable and cost-effective device for noninvasive pulsatile blood flow measurement.

AIM

A diffuse-optics-based method, diffuse speckle pulsatile flowmetry (DSPF), was developed for fast measurement (∼300  Hz) of deep tissue blood flow noninvasively. To validate its performance, both a phantom experiment and in vivo demonstration were conducted.

APPROACH

Over the past two decades, single-mode fibers have been used as detection fibers in most diffuse-optics-based deep tissue blood flow measurement modalities. We used a multimode (MM) detection fiber with a core size of 200  μm for diffused speckle pattern detection. A background intensity correction algorithm was implemented for speckle contrast calculation. The MM detection fiber helped to achieve a level of deep tissue blood flow measurement similar to that of conventional modalities, such as diffuse correlation spectroscopy and diffuse speckle contrast analysis, but it increases the measurement rate of blood flow to 300 Hz.

RESULTS

The design and implementation of the DSPF system were introduced. The theory of the background intensity correction for the diffused speckle pattern detected by the MM fiber was explained. A flow phantom was built for validation of the performance of the DSPF system. An in vivo cuff-induced occlusion experiment was performed to demonstrate the capability of the proposed DSPF system.

CONCLUSIONS

An MM detection fiber can help to achieve fast (∼300  Hz) pulsatile blood flow measurement in the proposed DSPF method. The cost-effective device and the fiber-based flexible probe increase the usability of the DSPF system significantly.

A multipixel diffuse correlation spectroscopy system based on a single photon avalanche diode array

The autocorrelation of laser speckles from coherent near infrared light is used for noninvasive estimates of relative changes in blood perfusion in techniques such as laser Doppler flowmetry (LDF) and diffuse correlation spectroscopy (DCS). In this study, a 2D array of single photon avalanche diodes (SPADs) was used to combine the strengths of multiple detectors in LDF with high light sensitivity in DCS. The system was tested on milk phantoms with varying detector fiber diameter (200 and 600 μm), source-detector fiber separation (4.6-10.2 mm), fiber-SPAD distance (2.5-36.5 mm), contiguous measurement time per repetition for the autocorrelation (1-33 ms) and temperature (15.6-46.7°C). An in vivo blood occlusion test was also performed. The multipixel approach improved signal-to-noise ratio (SNR) and, in our setup, the use of a multimode detector fiber was beneficial for SNR. In conclusion, the multipixel system works, but improvements and further studies regarding, for example, the data acquisition and optimal settings are still needed.

Portable Near-Infrared Technologies and Devices for Noninvasive Assessment of Tissue Hemodynamics

Tissue hemodynamics, including the blood flow, oxygenation, and oxygen metabolism, are closely associated with many diseases. As one of the portable optical technologies to explore human physiology and assist in healthcare, near-infrared diffuse optical spectroscopy (NIRS) for tissue oxygenation measurement has been developed for four decades. In recent years, a dynamic NIRS technology, namely, diffuse correlation spectroscopy (DCS), has been emerging as a portable tool for tissue blood flow measurement. In this article, we briefly describe the basic principle and algorithms for static NIRS and dynamic NIRS (i.e., DCS). Then, we elaborate on the NIRS instrumentation, either commercially available or custom-made, as well as their applications to physiological studies and clinic. The extension of NIRS/DCS from spectroscopy to imaging was depicted, followed by introductions of advanced algorithms that were recently proposed. The future prospective of the NIRS/DCS and their feasibilities for routine utilization in hospital is finally discussed.

Lawrence K, Amendolia O, Quattrone F, Balu R, Kofke WA, Yodh AG. Noninvasive continuous optical monitoring of absolute cerebral blood flow in critically ill adults

We investigate a scheme for noninvasive continuous monitoring of absolute cerebral blood flow (CBF) in adult human patients based on a combination of time-resolved dynamic contrast-enhanced near-infrared spectroscopy (DCE-NIRS) and diffuse correlation spectroscopy (DCS) with semi-infinite head model of photon propogation. Continuous CBF is obtained via calibration of the DCS blood flow index (BFI) with absolute CBF obtained by intermittent intravenous injections of the optical contrast agent indocyanine green. A calibration coefficient ( γ ) for the CBF is thus determined, permitting conversion of DCS BFI to absolute blood flow units at all other times. A study of patients with acute brain injury ( N = 7 ) is carried out to ascertain the stability of γ . The patient-averaged DCS calibration coefficient across multiple monitoring days and multiple patients was determined, and good agreement between the two calibration coefficients measured at different times during single monitoring days was found. The patient-averaged calibration coefficient of 1.24 × 10 9    ( mL / 100    g / min ) / ( cm 2 / s ) was applied to previously measured DCS BFI from similar brain-injured patients; in this case, absolute CBF was underestimated compared with XeCT, an effect we show is primarily due to use of semi-infinite homogeneous models of the head.

Development and characterization of a multidistance and multiwavelength diffuse correlation spectroscopy system

This paper presents a multidistance and multiwavelength diffuse correlation spectroscopy (DCS) approach and its implementation to simultaneously measure the optical proprieties of deep tissue as well as the blood flow. The system consists of three long coherence length lasers at different wavelengths in the near-infrared, eight single-photon detectors, and a correlator board. With this approach, we collect both light intensity and DCS data at multiple distances and multiple wavelengths, which provide unique information to fit for all the parameters of interest: scattering, blood flow, and hemoglobin concentration. We present the characterization of the system and its validation with phantom measurements.

Highly parallel, interferometric diffusing wave spectroscopy for monitoring cerebral blood flow dynamics

Light-scattering methods are widely used in soft matter physics and biomedical optics to probe dynamics in turbid media, such as diffusion in colloids or blood flow in biological tissue. These methods typically rely on fluctuations of coherent light intensity, and therefore cannot accommodate more than a few modes per detector. This limitation has hindered efforts to measure deep tissue blood flow with high speed, since weak diffuse light fluxes, together with low single-mode fiber throughput, result in low photon count rates. To solve this, we introduce multimode fiber (MMF) interferometry to the field of diffuse optics. In doing so, we transform a standard complementary metal-oxide-semiconductor (CMOS) camera into a sensitive detector array for weak light fluxes that probe deep in biological tissue. Specifically, we build a novel CMOS-based, multimode interferometric diffusing wave spectroscopy (iDWS) system and show that it can measure ∼20 speckles simultaneously near the shot noise limit, acting essentially as ∼20 independent photon-counting channels. We develop a matrix formalism, based on MMF mode field solutions and detector geometry, to predict both coherence and speckle number in iDWS. After validation in liquid phantoms, we demonstrate iDWS pulsatile blood flow measurements at 2.5 cm source-detector separation in the adult human brain in vivo. By achieving highly sensitive and parallel measurements of coherent light fluctuations with a CMOS camera, this work promises to enhance performance and reduce cost of diffuse optical instruments.

Simultaneous blood flow and blood oxygenation measurements using a combination of diffuse speckle contrast analysis and near-infrared spectroscopy

A combined diffuse speckle contrast analysis (DSCA)-near-infrared spectroscopy (NIRS) system is proposed to simultaneously measure qualitative blood flow and blood oxygenation changes in human tissue. The system employs an optical switch to alternate two laser sources at two different wavelengths and a CCD camera to capture the speckle image. Therefore, an optical density can be measured from two wavelengths for NIRS measurements and a speckle contrast can be calculated for DSCA measurements. In order to validate the system, a flow phantom test and an arm occlusion protocol for arterial and venous occlusion were performed. Shorter exposure times (<1 ms ) show a higher drop (between 50% and 66%) and recovery of 1/K²S values after occlusion (approximately 150%), but longer exposure time (3 ms) shows more consistent hemodynamic changes. For four subjects, the 1/K²S values dropped to an average of 82.1±4.0% during the occlusion period and the average recovery of 1/K²S values after occlusion was 109.1±0.8% . There was also an approximately equivalent amplitude change in oxyhemoglobin (OHb) and deoxyhemoglobin (RHb) during arterial occlusion (max RHb=0.0085±0.0024 mM/DPF, min OHb=-0.0057±0.0044 mM/DPF). The sensitivity of the system makes it a suitable modality to observe qualitative hemodynamic trends during induced physiological changes.

Obstructive sleep apnea-hypopnea results in significant variations in cerebral hemodynamics detected by diffuse optical spectroscopies

The objective of this study was to adapt a novel near-infrared diffuse correlation spectroscopy (DCS) flow-oximeter for simultaneous and continuous monitoring of relative changes in cerebral blood flow (rCBF) and cerebral oxygenation (i.e. oxygenated/deoxygenated/total hemoglobin concentration: Δ[HbO2]/Δ[Hb]/ΔTHC) during overnight nocturnal polysomnography (NPSG) diagnostic test for obstructive sleep apnea-hypopnea (OSAH). A fiber-optic probe was fixed on subject's frontal head and connected to the DCS flow-oximeter through a custom-designed fiber-optic connector, which allowed us to easily connect/detach the optical probe from the device when the subject went to bathroom. To minimize the disturbance to the subject, the DCS flow-oximeter was remotely operated by a desktop located in the control room. The results showed that apneic events caused significant variations in rCBF and ΔTHC. Moreover, the degrees of variations in all measured cerebral variables were significantly correlated with the severity of OSAH as determined by the apnea-hypopnea index (AHI), demonstrating the OSAH influence on both CBF and cerebral oxygenation. Large variations in arterial blood oxygen saturation (SaO2) were also found during OSAH. Since frequent variations/disturbances in cerebral hemodynamics may adversely impact brain function, future study will investigate the correlations between these cerebral variations and functional impairments for better understanding of OSAH pathophysiology.

Diffuse correlation spectroscopy for measurement of cerebral blood flow: future prospects

Diffuse correlation spectroscopy (DCS) is an emerging optical modality used to measure cortical cerebral blood flow. This outlook presents a brief overview of the technology, summarizing the advantages and limitations of the method, and describing its recent applications to animal, adult, and infant cohorts. At last, the paper highlights future applications where DCS may play a pivotal role individualizing patient management and enhancing our understanding of neurovascular coupling, activation, and brain development.

Instrumentation in Diffuse Optical Imaging

Diffuse optical imaging is highly versatile and has a very broad range of applications in biology and medicine. It covers diffuse optical tomography, fluorescence diffuse optical tomography, bioluminescence, and a number of other new imaging methods. These methods of diffuse optical imaging have diversified instrument configurations but share the same core physical principle – light propagation in highly diffusive media, i.e., the biological tissue. In this review, the author summarizes the latest development in instrumentation and methodology available to diffuse optical imaging in terms of system architecture, light source, photo-detection, spectral separation, signal modulation, and lastly imaging contrast.

Diffuse correlation spectroscopy for non-invasive, micro-vascular cerebral blood flow measurement

Diffuse correlation spectroscopy (DCS) uses the temporal fluctuations of near-infrared (NIR) light to measure cerebral blood flow (CBF) non-invasively. Here, we provide a brief history of DCS applications in the brain with an emphasis on the underlying physical ideas, common instrumentation and validation. Then we describe recent clinical research that employs DCS-measured CBF as a biomarker of patient well-being, and as an indicator of hemodynamic and metabolic responses to functional stimuli.

Noninvasive evaluation of electrical stimulation impacts on muscle hemodynamics via integrating diffuse optical spectroscopies with muscle stimulator

Technologies currently available for the monitoring of electrical stimulation (ES) in promoting blood circulation and tissue oxygenation are limited. This study integrated a muscle stimulator with a diffuse correlation spectroscopy (DCS) flow-oximeter to noninvasively quantify muscle blood flow and oxygenation responses during ES. Ten healthy subjects were tested using the integrated system. The muscle stimulator delivered biphasic electrical current to right leg quadriceps muscle, and a custom-made DCS flow-oximeter was used for simultaneous measurements of muscle blood flow and oxygenation in both legs. To minimize motion artifact of muscle fibers during ES, a novel gating algorithm was developed for data acquisition at the time when the muscle was relaxed. ES at 2, 10, and 50 Hz were applied for 20 min on each subject in three days sequentially. Results demonstrate that the 20-min ES at all frequencies promoted muscle blood flow significantly. However, only the ES at 10 Hz resulted in significant and persistent increases in oxy-hemoglobin concentration during and post ES. This pilot study supports the application of the integrated system to quantify tissue hemodynamic improvements for the optimization of ES treatment in patients suffering from diseases caused by poor blood circulation and low tissue oxygenation (e.g., pressure ulcer).

Diffuse Correlation Spectroscopy (DCS) for Assessment of Tissue Blood Flow in Skeletal Muscle: Recent Progress

Near-infrared diffuse correlation spectroscopy (DCS) is an emerging technology for monitoring blood flow in various tissues. This article reviews the recent progress of DCS for the assessment of skeletal muscle blood flow, including the developments in technology allowing use during dynamic exercise and muscular electrical stimulation, the utilization for diagnosis of muscle vascular diseases, and the applications for evaluating treatment effects. The limitations of current DCS studies and future perspective are finally discussed.