Shear-induced diffusion of red blood cells measured with dynamic light scattering-optical coherence tomography

Ergodic speckle contrast optical coherence tomography velocimetry of rapid blood flow

Visualizing a 3D blood flow velocity field through noninvasive imaging is crucial for analyzing hemodynamic mechanisms in areas prone to disorders. However, traditional correlation-based optical coherence tomography (OCT) velocimetry techniques have a maximum measurable flow velocity depending on the A-line rate. We presented the ergodic speckle contrast OCT (ESCOCT) to break the bottleneck in measuring the rapid blood flow velocity. It achieved a measurement of blood flow velocity ranging from 9.5 to 280 mm/s using a 100 kHz swept-source (SS) OCT based on 100 A-repeats scanning mode. Addressing the non-ergodic problem of temporal OCT signals by integrating more consecutive A-scans, ESCOCT can enable the estimation for lower velocity flows by increasing A-repeats. ESCOCT provided a wide dynamic range with no upper limit on measuring blood flow velocity with an adequate signal-to-noise ratio and improved the sensitivity and accuracy of the hemodynamic assessment.

Diffuse Optical Monitoring of Cerebral Hemodynamics and Oxygen Metabolism during and after Cardiopulmonary Bypass: Hematocrit Correction and Neurological Vulnerability

Cardiopulmonary bypass (CPB) provides cerebral oxygenation and blood flow (CBF) during neonatal congenital heart surgery, but the impacts of CPB on brain oxygen supply and metabolic demands are generally unknown. To elucidate this physiology, we used diffuse correlation spectroscopy and frequency-domain diffuse optical spectroscopy to continuously measure CBF, oxygen extraction fraction (OEF), and oxygen metabolism (CMRO2) in 27 neonatal swine before, during, and up to 24 h after CPB. Concurrently, we sampled cerebral microdialysis biomarkers of metabolic distress (lactate-pyruvate ratio) and injury (glycerol). We applied a novel theoretical approach to correct for hematocrit variation during optical quantification of CBF in vivo. Without correction, a mean (95% CI) +53% (42, 63) increase in hematocrit resulted in a physiologically improbable +58% (27, 90) increase in CMRO2 relative to baseline at CPB initiation; following correction, CMRO2 did not differ from baseline at this timepoint. After CPB initiation, OEF increased but CBF and CMRO2 decreased with CPB time; these temporal trends persisted for 0-8 h following CPB and coincided with a 48% (7, 90) elevation of glycerol. The temporal trends and glycerol elevation resolved by 8-24 h. The hematocrit correction improved quantification of cerebral physiologic trends that precede and coincide with neurological injury following CPB.

SpeckleCam: high-resolution computational speckle contrast tomography for deep blood flow imaging

Laser speckle contrast imaging is widely used in clinical studies to monitor blood flow distribution. Speckle contrast tomography, similar to diffuse optical tomography, extends speckle contrast imaging to provide deep tissue blood flow information. However, the current speckle contrast tomography techniques suffer from poor spatial resolution and involve both computation and memory intensive reconstruction algorithms. In this work, we present SpeckleCam, a camera-based system to reconstruct high resolution 3D blood flow distribution deep inside the skin. Our approach replaces the traditional forward model using diffuse approximations with Monte-Carlo simulations-based convolutional forward model, which enables us to develop an improved deep tissue blood flow reconstruction algorithm. We show that our proposed approach can recover complex structures up to 6 mm deep inside a tissue-like scattering medium in the reflection geometry. We also conduct human experiments to demonstrate that our approach can detect reduced flow in major blood vessels during vascular occlusion.

Cortical microvascular blood flow velocity mapping by combining dynamic light scattering optical coherence tomography and two-photon microscopy

Significance

The accurate large-scale mapping of cerebral microvascular blood flow velocity is crucial for a better understanding of cerebral blood flow (CBF) regulation. Although optical imaging techniques enable both high-resolution microvascular angiography and fast absolute CBF velocity measurements in the mouse cortex, they usually require different imaging techniques with independent system configurations to maximize their performances. Consequently, it is still a challenge to accurately combine functional and morphological measurements to co-register CBF speed distribution from hundreds of microvessels with high-resolution microvascular angiograms.

Aim

We propose a data acquisition and processing framework to co-register a large set of microvascular blood flow velocity measurements from dynamic light scattering optical coherence tomography (DLS-OCT) with the corresponding microvascular angiogram obtained using two-photon microscopy (2PM).

Approach

We used DLS-OCT to first rapidly acquire a large set of microvascular velocities through a sealed cranial window in mice and then to acquire high-resolution microvascular angiograms using 2PM. The acquired data were processed in three steps: (i) 2PM angiogram coregistration with the DLS-OCT angiogram, (ii) 2PM angiogram segmentation and graphing, and (iii) mapping of the CBF velocities to the graph representation of the 2PM angiogram.

Results

We implemented the developed framework on the three datasets acquired from the mice cortices to facilitate the coregistration of the large sets of DLS-OCT flow velocity measurements with 2PM angiograms. We retrieved the distributions of red blood cell velocities in arterioles, venules, and capillaries as a function of the branching order from precapillary arterioles and postcapillary venules from more than 1000 microvascular segments.

Conclusions

The proposed framework may serve as a useful tool for quantitative analysis of large microvascular datasets obtained by OCT and 2PM in studies involving normal brain functioning, progression of various diseases, and numerical modeling of the oxygen advection and diffusion in the realistic microvascular networks.

Lawrence K, Tachtsidis I, Tong Y, Torricelli A, Urner T, Wabnitz H, Wolf M, Wolf U, Xu S, Yang C, Yodh AG, Yücel MA, Zhou W. Optical imaging and spectroscopy for the study of the human brain: status report

This report is the second part of a comprehensive two-part series aimed at reviewing an extensive and diverse toolkit of novel methods to explore brain health and function. While the first report focused on neurophotonic tools mostly applicable to animal studies, here, we highlight optical spectroscopy and imaging methods relevant to noninvasive human brain studies. We outline current state-of-the-art technologies and software advances, explore the most recent impact of these technologies on neuroscience and clinical applications, identify the areas where innovation is needed, and provide an outlook for the future directions.

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.

Measuring neuronal activity with diffuse correlation spectroscopy: a theoretical investigation

Significance: Diffuse correlation spectroscopy (DCS) measures cerebral blood flow non-invasively. Variations in blood flow can be used to detect neuronal activities, but its peak has a latency of a few seconds, which is slow for real-time monitoring. Neuronal cells also deform during activation, which, in principle, can be utilized to detect neuronal activity on fast timescales (within 100 ms) using DCS. Aims: We aim to characterize DCS signal variation quantified as the change of the decay time of the speckle intensity autocorrelation function during neuronal activation on both fast (within 100 ms) and slow (100 ms to seconds) timescales. Approach: We extensively modeled the variations in the DCS signal that are expected to arise from neuronal activation using Monte Carlo simulations, including the impacts of neuronal cell motion, vessel wall dilation, and blood flow changes. Results: We found that neuronal cell motion induces a DCS signal variation of ∼ 10 - 5 . We also estimated the contrast and number of channels required to detect hemodynamic signals at different time delays. Conclusions: From this extensive analysis, we do not expect to detect neuronal cell motion using DCS in the near future based on current technology trends. However, multi-channel DCS will be able to detect hemodynamic response with sub-second latency, which is interesting for brain-computer interfaces.

Shear-induced diffusion in dense granular fluids

Granular materials are comprised of solid, athermal grains. Whilst immune to thermal motion, these grains move and diffuse when they undergo shear deformation. Here we introduce this process of shear-induced diffusion with a focus on dense flows. The goal is to present the established scaling laws for continuum diffusivity and to relate them to the micro-mechanisms of a granular random walk. We then suggest how this knowledge may help advance our understanding of granular rheology and diffusion in other soft-materials.

Choosing a model for laser speckle contrast imaging

Laser speckle contrast imaging (LSCI) is a real-time full-field non-invasive technique, which is broadly applied to visualize blood flow in biomedical applications. In its foundation is the link between the speckle contrast and dynamics of light scattering particles-erythrocytes. The mathematical form describing this relationship, which is critical for accurate blood flow estimation, depends on the sample's light-scattering properties. However, in biological applications, these properties are often unknown, thus requiring assumptions to be made to perform LSCI analysis. Here, we review the most critical assumptions in the LSCI theory and simulate how they affect blood flow estimation accuracy. We show that the most commonly applied model can severely underestimate the flow change, particularly when imaging brain parenchyma or other capillary perfused tissue (e.g. skin) under ischemic conditions. Based on these observations and guided by the recent experimental results, we propose an alternative model that allows measuring blood flow changes with higher accuracy.

Stroke core revealed by tissue scattering using spatial frequency domain imaging

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We present OCT and SFDI as methods to measure the spatial extent of stroke in mice.

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OCT was a reliable predictor of the stroke core in a photothrombosis stroke model.

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SFDI scattering coefficient spatially overlaps with OCT attenuation after stroke.

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Scattering increases following stroke reliably predict ischemic injury.

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SFDI provides a wide-field optical approach to map the stroke core.

Ischemic stroke leads to a reduction or complete loss of blood supply causing injury to brain tissue, which ultimately leads to behavioral impairment. Optical techniques are widely used to study the structural and functional changes that result as a consequence of ischemic stroke both in the acute and chronic phases of stroke recovery. It is currently a challenge to accurately estimate the spatial extent of the infarct without the use of histological parameters however, and in order to follow recovery mechanisms longitudinally at the mesoscopic scale it is essential to know the spatial extent of the stroke core. In this paper we first establish optical coherence tomography (OCT) as a reliable indicator of the stroke core by analyzing signal attenuation and spatially correlating it with the infarct, determined by staining with triphenyl-tetrazolium chloride (TTC). We then introduce spatial frequency domain imaging (SFDI) as a mesoscopic optical technique that can be used to accurately measure the infarct spatial extent by exploiting changes in optical scattering that occur as a consequence of ischemic stroke. Additionally, we follow the progression of ischemia through the acute and sub-acute phases of stroke recovery using both OCT and SFDI and show a consistently high spatial overlap in estimating infarct location. The use of SFDI in assessing infarct location will allow longitudinal studies targeted at following functional recovery mechanisms on a mesoscopic level without having to sacrifice the mouse acutely.

Dynamic light scattering imaging

We introduce dynamic light scattering imaging (DLSI) to enable the wide-field measurement of the speckle temporal intensity autocorrelation function. DLSI uses the full temporal sampling of speckle fluctuations and a comprehensive model to identify the dynamic scattering regime and obtain a quantitative image of the scatterer dynamics. It reveals errors in the traditional theory of laser Doppler flowmetry and laser speckle contrast imaging and provides guidance on the best model to use in cerebral blood flow imaging.

RBC-Derived Optical Nanoparticles Remain Stable After a Freeze-Thaw Cycle

Nanosized carriers engineered from red blood cells (RBCs) provide a means for delivering various cargos, including drugs, biologics, and imaging agents. We have engineered nanosized particles from RBCs, doped with the near-infrared (NIR) fluorochrome, indocyanine green (ICG). An important issue related to clinical translation of RBC-derived nanocarriers, including these NIR nanoparticles, is their stability postfabrication. Freezing may provide a method for long-term storage of these and other RBC-derived nanoparticles. Herein, we have investigated the physical and optical stability of these particles in response to a single freeze-thaw cycle. Nanoparticles were frozen to -20 °C, stored frozen for up to 8 weeks, and then thawed at room temperature. Our results show that the hydrodynamic diameter, zeta potential, optical density, and NIR fluorescence emission of these nanoparticles are retained following the freeze-thaw cycle. The ability of these nanoparticles in NIR fluorescence imaging of ovarian cancer cells, as well as their biodistribution in reticuloendothelial organs of healthy Swiss Webster mice after the freeze-thaw cycle is similar to that for freshly prepared nanoparticles. These results indicate that a single cycle of freezing the RBC-derived nanoparticles to -20 °C followed by thawing at room temperature is an effective method to retain the physical and optical characteristics of the nanoparticles, and their interactions with biological systems without the need for use of cryoprotectants.

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.

Forward multiple scattering dominates speckle decorrelation in whole-blood flowmetry using optical coherence tomography

Quantitative blood flow measurements using optical coherence tomography (OCT) have a wide potential range of medical research and clinical applications. Flowmetry based on the temporal dynamics of the OCT signal may have the ability to measure three-dimensional flow profiles regardless of the flow direction. State-of-the-art models describing the OCT signal temporal statistics are based on dynamic light scattering (DLS), a model which is inherently limited to single scattering regimes. DLS methods continue to be applied to OCT despite the knowledge that red blood cells produce strong forward multiple scattering. Here, we postulate that forward multiple scattering is the primary mechanism causing the rate of speckle-decorrelation derived from data acquired in vivo to deviate from the rate of decorrelation determined in phantom experiments. We also postulate that multiple scattering contributions to decorrelation are only present when the sample exhibits velocity field inhomogeneities larger than the scale of a resolution volume and are thus absent in rigid bulk motion. To test these hypotheses, we performed a systematic study of the effects of forward multiple scattering on OCT signal decorrelation with phantom experiments under physiologically relevant flow conditions and relative bulk motion. Our experimental results confirm that the amount of forward multiple scattering affects the proportionality between lateral flow and decorrelation. We propose that multiply scattered light carries information from different locations in the sample and each location imprints scattering dynamics on the scattered light causing increased decorrelation rates. Our analysis confirms that the detection of forward scattered light inside the vessel lumen causes an increase in the rate of decorrelation which results in an overestimation of blood flow velocities at depths as shallow as 40 µm into whole blood for OCT systems with typical numerical apertures used in retinal imaging.

Time-of-flight resolved light field fluctuations reveal deep human tissue physiology

Red blood cells (RBCs) transport oxygen to tissues and remove carbon dioxide. Diffuse optical flowmetry (DOF) assesses deep tissue RBC dynamics by measuring coherent fluctuations of multiply scattered near-infrared light intensity. While classical DOF measurements empirically correlate with blood flow, they remain far-removed from light scattering physics and difficult to interpret in layered media. To advance DOF measurements closer to the physics, here we introduce an interferometric technique, surmounting challenges of bulk motion to apply it in awake humans. We reveal two measurement dimensions: optical phase, and time-of-flight (TOF), the latter with 22 picosecond resolution. With this multidimensional data, we directly confirm the unordered, or Brownian, nature of optically probed RBC dynamics typically assumed in classical DOF. We illustrate how incorrect absorption assumptions, anisotropic RBC scattering, and layered tissues may confound classical DOF. By comparison, our direct method enables accurate and comprehensive assessment of blood flow dynamics in humans.

Optical coherence tomography velocimetry based on decorrelation estimation of phasor pair ratios (DEPPAIR)

Quantitative velocity estimations in optical coherence tomography requires the estimation of the axial and lateral flow components. Optical coherence tomography measures the depth resolved complex field reflected from a sample. While the axial velocity component can be determined from the Doppler shift or phase shift between a pair of consecutive measurements at the same location, the estimation of the lateral component for in vivo applications is still challenging. One approach to determine lateral velocity is multiple simultaneous measurements at different angles. In another approach the lateral component can be retrieved through repeated measurements at (nearly) the same location by an analysis of the decorrelation over time. In this paper we follow the latter approach. We describe a model for the complex field changes between consecutive measurements and use it to predict the uncertainties for amplitude-based, phase-based and complex algorithms. The uncertainty of the flow estimations follows from a statistical analysis and is determined by the number of available measurements and the applied analysis method. The model is verified in phantom measurements and the dynamic range of velocity estimations is investigated. We demonstrate that phase-based and complex (phasor) based lateral flow estimation methods are superior to amplitude-based algorithms.

Dynamic imaging and quantification of subcellular motion with eigen-decomposition optical coherence tomography-based variance analysis

The dynamic properties of subcellular organism are important biomarkers of the health. Imaging subcellular level dynamics provides effective solutions for evaluating cell metabolism and testing the responses of cells to pathogens and drugs in pharmaceutical engineering. In this paper, we demonstrate an innovative approach to contrast the subcellular motion by using eigen decomposition (ED)-based variance analysis of time-dependent complex optical coherence tomography signals. This method reveals a superior advantage of contrast to noise ratio when compared with the approach that employs intensity decorrelation. Furthermore, the eigen values derived from ED processing are calculated and applied to assess the power ratios of complex signal invariance that decreases exponentially along time dimension. The validation experiments are performed on the patterned samples of yeast powder mixed with gelatin/TiO2 water solution. Additionally, the proposed method is used to image mouse cerebral cortex in normal and pathological conditions, suggesting the practicality of variance power mapping in analyzing cortical neural activities. The technique promises efficient measurement of subcellular motions with high sensitivity and high throughput for in vivo and in situ applications.

Impact of velocity gradient in Poiseuille flow on the statistics of coherent radiation scattered by flowing Brownian particles in optical coherence tomography

A closed-form expression is obtained for the temporal correlation function of the scattered radiation detected in optical coherence tomography (OCT), taking into account the flow velocity gradient across the OCT detection volume in the suspension of flowing Brownian particles. The analytical approach we use includes both the laser beam and wavefront curvature radii changing over the depth. Also, we compare our results with a previously obtained theoretical model, partially an empirical approach. Our findings suggest the importance of the flow velocity gradient for accurate measurements of flow velocity vector, particle diffusivity, shear-induced diffusion, and potentially other OCT applications.

Small Vessels Are a Big Problem in Neurodegeneration and Neuroprotection

The cerebral microcirculation holds a critical position to match the high metabolic demand by neuronal activity. Functionally, microcirculation is virtually inseparable from other nervous system cells under both physiological and pathological conditions. For successful bench-to-bedside translation of neuroprotection research, the role of microcirculation in acute and chronic neurodegenerative disorders appears to be under-recognized, which may have contributed to clinical trial failures with some neuroprotectants. Increasing data over the last decade suggest that microcirculatory impairments such as endothelial or pericyte dysfunction, morphological irregularities in capillaries or frequent dynamic stalls in blood cell flux resulting in excessive heterogeneity in capillary transit may significantly compromise tissue oxygen availability. We now know that ischemia-induced persistent abnormalities in capillary flow negatively impact restoration of reperfusion after recanalization of occluded cerebral arteries. Similarly, microcirculatory impairments can accompany or even precede neural loss in animal models of several neurodegenerative disorders including Alzheimer's disease. Macrovessels are relatively easy to evaluate with radiological or experimental imaging methods but they cannot faithfully reflect the downstream microcirculatory disturbances, which may be quite heterogeneous across the tissue at microscopic scale and/or happen fast and transiently. The complexity and size of the elements of microcirculation, therefore, require utilization of cutting-edge imaging techniques with high spatiotemporal resolution as well as multidisciplinary team effort to disclose microvascular-neurodegenerative connection and to test treatment approaches to advance the field. Developments in two photon microscopy, ultrafast ultrasound, and optical coherence tomography provide valuable experimental tools to reveal those microscopic events with high resolution. Here, we review the up-to-date advances in understanding of the primary microcirculatory abnormalities that can result in neurodegenerative processes and the combined neurovascular protection approaches that can prevent acute as well as chronic neurodegeneration.

Non-invasive and quantitative in vivo monitoring of gold nanoparticle concentration and tissue hemodynamics by hybrid optical spectroscopies

Owing to their unique combination of chemical and physical properties, inorganic nanoparticles show a great deal of potential as suitable agents for early diagnostics and less invasive therapies. Yet, their translation to the clinic has been hindered, in part, by the lack of non-invasive methods to quantify their concentration in vivo while also assessing their effect on the tissue physiology. In this work, we demonstrate that diffuse optical techniques, employing near-infrared light, have the potential to address this need in the case of gold nanoparticles which support localized surface plasmons. An orthoxenograft mouse model of clear cell renal cell carcinoma was non-invasively assessed by diffuse reflectance and correlation spectroscopies before and over several days following a single intravenous tail vein injection of polyethylene glycol-coated gold nanorods (AuNRs-PEG). Our platform enables to resolve the kinetics of the AuNR-PEG uptake by the tumor in quantitative agreement with ex vivo inductively coupled plasma mass spectroscopy. Furthermore, it allows for the simultaneous monitoring of local tissue hemodynamics, enabling us to conclude that AuNRs-PEG do not significantly alter the animal physiology. We note that the penetration depth of this current probe was a few millimeters but can readily be extended to centimeters, hence gaining clinical relevance. This study and the methodology presented here complement the nanomedicine toolbox by providing a flexible platform, extendable to other absorbing agents that can potentially be translated to human trials.

Normalized field autocorrelation function-based optical coherence tomography three-dimensional angiography

Optical coherence tomography angiography (OCTA) has been widely used for en face visualization of the microvasculature, but is challenged for real three-dimensional (3-D) topologic imaging due to the "tail" artifacts that appear below large vessels. Further, OCTA is generally incapable of differentiating descending arterioles from ascending venules. We introduce a normalized field autocorrelation function-based OCTA (g1-OCTA), which minimizes the tail artifacts and is capable of distinguishing penetrating arterioles from venules in the 3-D image. g1   (  τ  )   is calculated from repeated optical coherence tomography (OCT) acquisitions for each spatial location. The decay amplitude of g1   (  τ  )   is retrieved to represent the dynamics for each voxel. To account for the small g1   (  τ  )   decay in capillaries where red blood cells are flowing slowly and discontinuously, Intralipid is injected to enhance the OCT signal. We demonstrate that the proposed technique realizes 3-D OCTA with negligible tail projections and the penetrating arteries are readily identified. In addition, compared to regular OCTA, the proposed g1-OCTA largely increased the depth-of-field. This technique provides a more accurate rendering of the vascular 3-D anatomy and has the potential for more quantitative characterization of vascular networks.

Characterization of the microvascular cerebral blood flow response to obstructive apneic events during night sleep

Obstructive apnea causes periodic changes in cerebral and systemic hemodynamics, which may contribute to the increased risk of cerebrovascular disease of patients with obstructive sleep apnea (OSA) syndrome. The improved understanding of the consequences of an apneic event on the brain perfusion may improve our knowledge of these consequences and then allow for the development of preventive strategies. Our aim was to characterize the typical microvascular, cortical cerebral blood flow (CBF) changes in an OSA population during an apneic event. Sixteen patients (age 58 ± 8    years , 75% male) with a high risk of severe OSA were measured with a polysomnography device and with diffuse correlation spectroscopy (DCS) during one night of sleep with 1365 obstructive apneic events detected. All patients were later confirmed to suffer from severe OSA syndrome with a mean of 83 ± 15 apneas and hypopneas per hour. DCS has been shown to be able to characterize the microvascular CBF response to each event with a sufficient contrast-to-noise ratio to reveal its dynamics. It has also revealed that an apnea causes a peak increase of microvascular CBF ( 30 ± 17 % ) at the end of the event followed by a drop ( - 20 ± 12 % ) similar to what was observed in macrovascular CBF velocity of the middle cerebral artery. This study paves the way for the utilization of DCS for further studies on these populations.

Establishing the quantitative relationship between diffuse speckle contrast analysis signals with absolute blood flow

Diffuse speckle contrast analysis (DSCA) measures blood flow in deep tissues by taking advantage of the sensitivity of the speckle contrast signal to red blood cells (RBCs) motions. However, there has yet to be presented a clearly defined relationship between the absolute blood flow BF_abs and the measured speckle contrast signal. Here, we derive an expression of linear approximation function for speckle contrast, taking into account both shear-induced diffusive and correlated advective RBCs motions in the vessels. We provide a linear relationship between the slope k _slope of this linear function and BF_abs. The feasibility of this relationship is validated by Monte Carlo simulations of heterogeneous tissue with varying vessel radii. Furthermore, based on this quantitative relationship, we can determine the relative contributions of diffusive RBCs motion on the reduction of speckle contrast, considering different vascular morphology and flow profiles.

Capillary red blood cell velocimetry by phase-resolved optical coherence tomography

We present a phase-resolved optical coherence tomography (OCT) method to extend Doppler OCT for the accurate measurement of the red blood cell (RBC) velocity in cerebral capillaries. OCT data were acquired with an M-mode scanning strategy (repeated A-scans) to account for the single-file passage of RBCs in a capillary, which were then high-pass filtered to remove the stationary component of the signal to ensure an accurate measurement of phase shift of flowing RBCs. The angular frequency of the signal from flowing RBCs was then quantified from the dynamic component of the signal and used to calculate the axial speed of flowing RBCs in capillaries. We validated our measurement by RBC passage velocimetry using the signal magnitude of the same OCT time series data.