Diffuse Correlation Spectroscopy Measurements Research Articles

Abstract 430: The Use of DCS as a Predictive Model for the Development of DCI Following aSAH ‐ Preliminary Experience

Background Delayed cerebral ischemia (DCI) remains the leading cause of morbidity and mortality in patients with subarachnoid hemorrhage (SAH). DCI results in focal neurological deficits in 30‐50% of patients within 4‐10 days following aneurysm rupture. Given the short comings of the current technologies in identifying DCI (mainly, transcranial dopplers), the current study employed the use of non‐invasive optical measurements of cerebral blood flow (CBF) using a custom‐built diffuse correlation spectroscopy (DCS) device. This research is supported by an R01 NIINDS funding mechanism. Methods We preformed daily bilateral cerebral blood flow measurements using a custom built DCS device in six patients following aSAH until discharge from our facility. Daily collection of transcranial doppler readings, NIHSS and GCS scores, in conjunction with other relevant clinical and angiographic procedural data were collected daily from admission until day 14 (or later if the patient remained symptomatic). In patients who underwent intra‐arterial vasospasm treatment in the angio suite, DCS recordings were obtained immediately before, after, and throughout the infusion. Results Recordings were successfully obtained in six patients. No safety concerns or interference with standard workflow procedures were noted. Correlation of daily DCS measurements with changes in clinical exam and occurrence of DCI are being finalized and prepared for the SVIN conference. Conclusions Preliminary analysis have demonstrated that the use of DCS optical measurements is safe and effective in the clinical setting with minimal interruptions to standard clinical operations.

Noninvasive optical monitoring of cerebral hemodynamics in a preclinical model of neonatal intraventricular hemorrhage.

Intraventricular hemorrhage (IVH) is a common complication in premature infants and is associated with white matter injury and long-term neurodevelopmental disabilities. Standard diagnostic tools such as cranial ultrasound and MRI are widely used in both preclinical drug development and clinical practice to detect IVH. However, these methods only provide endpoint assessments of blood accumulation and lack real-time information about dynamic changes in ventricular blood flow. This limitation could potentially result in missed opportunities to advance drug candidates that may have protective effects against IVH. In this pilot study, we aimed to develop a noninvasive optical approach using diffuse correlation spectroscopy (DCS) to monitor real-time hemodynamic changes associated with hemorrhagic and sub-hemorrhagic events in a preclinical rabbit model of IVH. DCS measurements were conducted during the experimental induction of IVH, and results were compared with ultrasound and histological analysis to validate findings. Significant changes in hemodynamics were detected in all animals subjected to IVH-inducing procedures, including those that did not show clear positive results on ultrasound. The study revealed progressively elevated coefficients of variation in blood flow, particularly driven by increased oscillations within the 0.05-0.1 Hz frequency band. These hemodynamic changes were more pronounced in animals that developed IVH, as confirmed by ultrasound. Our findings suggest that real-time optical monitoring with DCS can provide critical insights into pathological blood flow changes, offering a more sensitive and informative tool for evaluating potential therapeutics in the context of IVH.

All-optics technique for monitoring absolute cerebral blood flow: validation against magnetic resonance imaging perfusion.

The ability to monitor cerebral blood flow (CBF) at the bedside is essential to managing critical-care patients with neurological emergencies. Diffuse correlation spectroscopy (DCS) is ideal because it is non-invasive, portable, and inexpensive. We investigated a near-infrared spectroscopy (NIRS) approach for converting DCS measurements into physiological units of blood flow. Using magnetic resonance imaging perfusion as a reference, we investigated the accuracy of absolute CBF measurements from a bolus-tracking NIRS method that used transient hypoxia as a flow tracer and hypercapnia-induced increases in CBF measured by DCS. Twelve participants (7 female, years) completed a hypercapnia protocol with simultaneous CBF recordings from DCS and arterial spin labeling (ASL). Nine participants completed the transient hypoxia protocol while instrumented with time-resolved NIRS. The estimate of baseline CBF was subsequently used to calibrate hypercapnic DCS data. Moderately strong correlations at baseline ( and ) and during hypercapnia ( and ) were found between CBF values from calibrated DCS and ASL (range 34 to ). Results demonstrated the feasibility of an all-optics approach that can both quantify CBF and perform continuous perfusion monitoring.

Wearable fiber-free optical sensor for continuous monitoring of neonatal cerebral blood flow and oxygenation.

Unstable cerebral hemodynamics places preterm infants at high risk of brain injury. We adapted an innovative, fiber-free, wearable diffuse speckle contrast flow-oximetry (DSCFO) device for continuous monitoring of both cerebral blood flow (CBF) and oxygenation in neonatal piglets and preterm infants. DSCFO uses two small laser diodes as focused-point and a tiny CMOS camera as a high-density two-dimensional detector to detect spontaneous spatial fluctuation of diffuse laser speckles for CBF measurement, and light intensity attenuations for cerebral oxygenation measurement. The DSCFO was first validated against the established diffuse correlation spectroscopy (DCS) in neonatal piglets and then utilized for continuous CBF and oxygenation monitoring in preterm infants during intermittent hypoxemia (IH) events. Significant correlations between the DSCFO and DCS measurements of CBF variations in neonatal piglets were observed. IH events induced fluctuations in CBF, cerebral oxygenation, and peripheral cardiorespiratory vitals in preterm infants. However, no consistent correlation patterns were observed among peripheral and cerebral monitoring parameters. This pilot study demonstrated the feasibility of DSCFO technology to serve as a low-cost wearable sensor for continuous monitoring of multiple cerebral hemodynamic parameters. The results suggested the importance of multi-parameter measurements for understanding deep insights of peripheral and cerebral regulations. The innovative DSCFO technology may serve as a low-cost wearable sensor for continuous bedside monitoring of multiple cerebral hemodynamic parameters in neonatal intensive care units. Concurrent DSCFO and DCS measurements of CBF variations in neonatal piglet models generated consistent results. No consistent correlation patterns were observed among peripheral and cerebral monitoring parameters in preterm neonates, suggesting the importance of multi-parameter measurements for understanding deep insights of peripheral and cerebral regulations during IH events. Integrating and correlating multiple cerebral functional parameters with clinical outcomes may identify biomarkers for prediction and management of IH associated brain injury.

Review of measurements and imaging of cytochrome-c-oxidase in humans using near-infrared spectroscopy: an update.

This review examines advancements in the measurement and imaging of oxidized cytochrome-c-oxidase (oxCCO) using near-infrared spectroscopy (NIRS) in humans since 2016. A total of 34 published papers were identified, with a focus on both adult and neonate populations. The NIRS-derived oxCCO signal has been demonstrated to correlate with physiological parameters and hemodynamics. New instrumentation, such as systems that allow the imaging of changes of oxCCO with diffuse optical tomography or combine the oxCCO measurement with diffuse correlation spectroscopy measures of blood flow, have advanced the field in the past decade. However, variability in its response across different populations and paradigms and lack of standardization limit its potential as a reliable and valuable indicator of brain health. Future studies should address these issues to fulfill the vision of oxCCO as a clinical biomarker.

Association Between Disrupted Cerebral Autoregulation and Radiographic Neurologic Injury for Children on Extracorporeal Membrane Oxygenation: A Prospective Pilot Study.

Validation of a real-time monitoring device to evaluate the risk or occurrence of neurologic injury while on extracorporeal membrane oxygenation (ECMO) may aid clinicians in prevention and treatment. Therefore, we performed a pilot prospective cohort study of children under 18 years old on ECMO to analyze the association between cerebral blood pressure autoregulation as measured by diffuse correlation spectroscopy (DCS) and radiographic neurologic injury. DCS measurements of regional cerebral blood flow were collected on enrolled patients and correlated with mean arterial blood pressure to determine the cerebral autoregulation metric termed DCSx. The primary outcome of interest was radiographic neurologic injury on eligible computed tomography (CT) or magnetic resonance imaging (MRI) scored by a blinded pediatric neuroradiologist utilizing a previously validated scale. Higher DCSx scores, which indicate disruption of cerebral autoregulation, were associated with higher radiographic neurologic injury score (slope, 11.0; 95% confidence interval [CI], 0.29-22). Patients with clinically significant neurologic injury scores of 10 or more had higher median DCSx measures than patients with lower neurologic injury scores (0.48 vs . 0.13; p = 0.01). Our study indicates that obtaining noninvasive DCS measures for children on ECMO is feasible and disruption of cerebral autoregulation determined from DCS is associated with higher radiographic neurologic injury score.

Influence of source-detector separation on diffuse correlation spectroscopy measurements of cerebral blood flow with a multilayered analytical model.

.Significance: Diffuse correlation spectroscopy (DCS) is an emerging noninvasive optical technology for bedside monitoring of cerebral blood flow. However, extracerebral hemodynamics can significantly influence DCS estimations of cerebral perfusion. Advanced analytical models can be used to remove the contribution of extracerebral hemodynamics; however, these models are highly sensitive to measurement noise. There is a need for an empirical determination of the optimal source–detector separation(s) (SDS) that improves the accuracy and reduces sensitivity to noise in the estimation of cerebral blood flow with these models.Aim: To determine the influence of SDS on solution uniqueness, measurement accuracy, and sensitivity to inaccuracies in model parameters when using the three-layer model to estimate cerebral blood flow with DCS.Approach: We performed a series of in silico simulations on samples spanning a wide range of physiologically-relevant layer optical properties, thicknesses, and flow. Data were simulated at SDS ranging from 0.5 to 3.0 cm using the three-layer solution to the correlation diffusion equation (with and without noise added) and using three-layer slab Monte Carlo simulations. We quantified the influence of SDS on uniqueness, accuracy, and sensitivity to inaccuracies in model parameters using the three-layer inverse model.Results: Two SDS are required to ensure a unique solution of cerebral blood flow index (CBFi). Combinations of 0.5/1.0/1.5 and 2.5 cm provide the optimal choice for balancing the depth penetration with signal-to-noise ratio to minimize the error in CBFi across a wide range of samples with varying optical properties, thicknesses, and dynamics.Conclusions: These results suggest that the choice of SDS is critical for minimizing the estimated error of cerebral blood flow when using the three-layer model to analyze DCS data.

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

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. 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. 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. 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. 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.

Development of a Monte Carlo-wave model to simulate time domain diffuse correlation spectroscopy measurements from first principles.

.Significance: Diffuse correlation spectroscopy (DCS) is an optical technique that measures blood flow non-invasively and continuously. The time-domain (TD) variant of DCS, namely, TD-DCS has demonstrated a potential to improve brain depth sensitivity and to distinguish superficial from deeper blood flow by utilizing pulsed laser sources and a gating strategy to select photons with different pathlengths within the scattering tissue using a single source–detector separation. A quantitative tool to predict the performance of TD-DCS that can be compared with traditional continuous wave DCS (CW-DCS) currently does not exist but is crucial to provide guidance for the continued development and application of these DCS systems.Aims: We aim to establish a model to simulate TD-DCS measurements from first principles, which enables analysis of the impact of measurement noise that can be utilized to quantify the performance for any particular TD-DCS system and measurement geometry.Approach: We have integrated the Monte Carlo simulation describing photon scattering in biological tissue with the wave model that calculates the speckle intensity fluctuations due to tissue dynamics to simulate TD-DCS measurements from first principles.Results: Our model is capable of simulating photon counts received at the detector as a function of time for both CW-DCS and TD-DCS measurements. The effects of the laser coherence, instrument response function, detector gate delay, gate width, intrinsic noise arising from speckle statistics, and shot noise are incorporated in the model. We have demonstrated the ability of our model to simulate TD-DCS measurements under different conditions, and the use of our model to compare the performance of TD-DCS and CW-DCS under a few typical measurement conditions.Conclusion: We have established a Monte Carlo-Wave model that is capable of simulating CW-DCS and TD-DCS measurements from first principles. In our exploration of the parameter space, we could not find realistic measurement conditions under which TD-DCS outperformed CW-DCS. However, the parameter space for the optimization of the contrast to noise ratio of TD-DCS is large and complex, so our results do not imply that TD-DCS cannot indeed outperform CW-DCS under different conditions. We made our code available publicly for others in the field to find use cases favorable to TD-DCS. TD-DCS also provides a promising way to measure deep brain tissue dynamics using a short source–detector separation, which will benefit the development of technologies including high density DCS systems and image reconstruction using a limited number of source–detector pairs.

Accuracy of diffuse correlation spectroscopy measurements of cerebral blood flow when using a three-layer analytical model.

Diffuse correlation spectroscopy (DCS) is a non-invasive optical technology for the assessment of an index of cerebral blood flow (CBFi). Analytical methods that model the head as a three-layered medium (i.e., scalp, skull, brain) are becoming more commonly used to minimize the contribution of extracerebral layers to the measured DCS signal in adult cerebral blood flow studies. However, these models rely on a priori knowledge of layer optical properties and thicknesses. Errors in these values can lead to errors in the estimation of CBFi, although the magnitude of this influence has not been rigorously characterized. Herein, we investigate the accuracy of measuring cerebral blood flow with a three-layer model when errors in layer optical properties or thicknesses are present. Through a series of in silico experiments, we demonstrate that CBFi is highly sensitive to errors in brain optical properties and skull and scalp thicknesses. Relative changes in CBFi are less sensitive to optical properties but are influenced by errors in layer thickness. Thus, when using the three-layer model, accurate estimation of scalp and skull thickness are required for reliable results.

Validation of diffuse correlation spectroscopy measures of critical closing pressure against transcranial Doppler ultrasound in stroke patients.

Significance: Intracranial pressure (ICP), variability in perfusion, and resulting ischemia are leading causes of secondary brain injury in patients treated in the neurointensive care unit. Continuous, accurate monitoring of cerebral blood flow (CBF) and ICP guide intervention and ultimately reduce morbidity and mortality. Currently, only invasive tools are used to monitor patients at high risk for intracranial hypertension.Aim: Diffuse correlation spectroscopy (DCS), a noninvasive near-infrared optical technique, is emerging as a possible method for continuous monitoring of CBF and critical closing pressure (CrCP or zero-flow pressure), a parameter directly related to ICP.Approach: We optimized DCS hardware and algorithms for the quantification of CrCP. Toward its clinical translation, we validated the DCS estimates of cerebral blood flow index () and CrCP in ischemic stroke patients with respect to simultaneously acquired transcranial Doppler ultrasound (TCD) cerebral blood flow velocity (CBFV) and CrCP.Results: We found CrCP derived from DCS and TCD were highly linearly correlated (ipsilateral , ; contralateral , ). We found weaker correlations between and CBFV (ipsilateral , ; contralateral , ) probably due to the different vasculature measured.Conclusion: Our results suggest DCS is a valid alternative to TCD for continuous monitoring of CrCP.

Impact of changes in tissue optical properties on near-infrared diffuse correlation spectroscopy measures of skeletal muscle blood flow.

Near-infrared diffuse correlation spectroscopy (DCS) is increasingly used to study relative changes in skeletal muscle blood flow. However, most diffuse correlation spectrometers assume that tissue optical properties-such as absorption (μa) and reduced scattering (μ's) coefficients-remain constant during physiological provocations, which is untrue for skeletal muscle. Here, we interrogate how changes in tissue μa and μ's affect DCS calculations of blood flow index (BFI). We recalculated BFI using raw autocorrelation curves and μa/μ's values recorded during a reactive hyperemia protocol in 16 healthy young individuals. First, we show that incorrectly assuming baseline μa and μ's substantially affects peak BFI and BFI slope when expressed in absolute terms (cm2/s, P < 0.01), but these differences are abolished when expressed in relative terms (% baseline). Next, to evaluate the impact of physiologic changes in μa and μ's, we compared peak BFI and BFI slope when μa and μ's were held constant throughout the reactive hyperemia protocol versus integrated from a 3-s rolling average. Regardless of approach, group means for peak BFI and BFI slope did not differ. Group means for peak BFI and BFI slope were also similar following ad absurdum analyses, where we simulated supraphysiologic changes in μa/μ's. In both cases, however, we identified individual cases where peak BFI and BFI slope were indeed affected, with this result being driven by relative changes in μa over μ's. Overall, these results provide support for past reports in which μa/μ's were held constant but also advocate for real-time incorporation of μa and μ's moving forward.NEW & NOTEWORTHY We investigated how changes in tissue optical properties affect near-infrared diffuse correlation spectroscopy (NIR-DCS)-derived indices of skeletal muscle blood flow (BFI) during physiological provocation. Although accounting for changes in tissue optical properties has little impact on BFI on a group level, individual BFI calculations are indeed impacted by changes in tissue optical properties. NIR-DCS calculations of BFI should therefore account for real-time, physiologically induced changes in tissue optical properties whenever possible.

Speckle contrast diffuse correlation tomography of cerebral blood flow in perinatal disease model of neonatal piglets.

We adapted and tested an innovative noncontact speckle contrast diffuse correlation tomography (scDCT) system for 3D imaging of cerebral blood flow (CBF) variations in perinatal disease models utilizing neonatal piglets, which closely resemble human neonates. CBF variations were concurrently measured by the scDCT and an established diffuse correlation spectroscopy (DCS) during global ischemia, intraventricular hemorrhage, and asphyxia; significant correlations were observed. Moreover, CBF variations associated reasonably with vital pathophysiological changes. In contrast to DCS measurements of mixed signals from local scalp, skull and brain, scDCT generates 3D images of CBF distributions at prescribed depths within the head, thus enabling specific determination of regional cerebral ischemia. With further optimization and validation in animals and human neonates, scDCT has the potential to be a noninvasive imaging tool for both basic neuroscience research in laboratories and clinical applications in neonatal intensive care units.

Diffuse correlation spectroscopy measurements of blood flow using 1064nm light.

.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 () 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.

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 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.

Hematocrit significantly confounds diffuse correlation spectroscopy measurements of blood flow.

Diffuse correlation spectroscopy (DCS) is an optical modality used to measure an index of blood flow in biological tissue. This blood flow index depends on both the red blood cell flow rate and density (i.e., hematocrit), although the functional form of hematocrit dependence is not well delineated. Herein, we develop and validate a novel tissue-simulating phantom containing hundreds of microchannels to investigate the influence of hematocrit on blood flow index. For a fixed flow rate, we demonstrate a significant inverse relationship between hematocrit and blood flow index that must be accounted for to accurately estimate blood flow under anemic conditions.

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.

Diffuse Correlation Spectroscopy at Short Source-Detector Separations: Simulations, Experiments and Theoretical Modeling

Diffuse correlation spectroscopy (DCS) has widely been used as a non-invasive optical technique to measure tissue perfusion in vivo. DCS measurements are quantified to yield information about moving scatterers using photon diffusion theory and are therefore obtained at long source-detector separations (SDS). However, short SDS DCS could be used for measuring perfusion in small animal models or endoscopically in clinical studies. Here, we investigate the errors in analytically retrieved flow coefficients from simulated and experimental data acquired at short SDS. Monte Carlo (MC) simulations of photon correlation transport was programmed to simulate DCS measurements and used to (a) examine the accuracy and validity of theoretical analyses, and (b) model experimental measurements made on phantoms at short SDS. Experiments consisted of measurements from a series of optical phantoms containing an embedded flow channel. Both the fluid flow rate and depth of the flow channel from the liquid surface were varied. Inputs to MC simulations required to model experiments were obtained from corrected theoretical analyses. Results show that the widely used theoretical DCS model is robust for quantifying relative changes in flow. We also show that retrieved flow coefficients at short SDS can be scaled to retrieve absolute values via MC simulations.

Optimization of detected optical intensity for measurement of diffuse correlation spectroscopy: Intralipid phantom study

Diffuse correlation spectroscopy (DCS) has recently been employed for noninvasive acquisition of blood flow information in deep tissues. In this study, we build a new DCS device based on software correlator. Through the intralipid phantom experiment, we obtained the quantitative relationship between the noise of detected optical intensity and the measurement error of Brownian diffusion coefficient. First, the quantitative influences of background noise and correction factor of detectors on actual beta are developed. Second, the intralipid phantom experiments show that the bigger deviation of actual beta to ideal value will result in the more measurement error of Brownian diffusion coefficient. The background noise and correction factor will lead to the deviation of actual beta to ideal value. The best situation to measure Brownian diffusion coefficient is that actual beta should be larger than 0.4 which requests the detected optical intensity by detector larger than 10 times of background noise and smaller than about 3000kcps. Moreover, our result show the collecting ability of optical intensity of probe is related to type of detecting fiber itself other than the lens coupling on it. In conclusion, we report a new DCS device based on the software correlator and show how the noise of detected optical intensity affects the DCS measurement.

Small separation diffuse correlation spectroscopy for measurement of cerebral blood flow in rodents.

Diffuse correlation spectroscopy (DCS) has shown promise as a means to non-invasively measure cerebral blood flow in small animal models. Here, we characterize the validity of DCS at small source-detector reflectance separations needed for small animal measurements. Through Monte Carlo simulations and liquid phantom experiments, we show that DCS error increases as separation decreases, although error remains below 12% for separations > 0.2 cm. In mice, DCS measures of cerebral blood flow have excellent intra-user repeatability and strongly correlate with MRI measures of blood flow (R = 0.74, p<0.01). These results are generalizable to other DCS applications wherein short-separation reflectance geometries are desired.