Accurate assessment of cerebral microvascular flow is crucial for understanding brain functioning and neurovascular diseases. Dynamic Light Scattering Optical Coherence Tomography (DLS-OCT) has been used to obtain blood velocity measurements in a large number of microvascular segments, including arterioles, capillaries, and venules in anesthetized mice. However, anesthesia induces large changes in the microvascular blood flow. Imaging awake animals by DLS-OCT is preferable, but very challenging due to motion artifacts. Here, we present the first DLS-OCT measurements of cortical microvascular blood flow in awake mice, made possible by an innovative algorithm based on Vertical Displacement at Inflection (IVD) in velocity distribution.
Accurate measurement of the microcirculation dynamics, including the blood vessel 3D structure, blood flow velocity and the blood flow transit time can not only improve our understanding of the pathology of microcirculation dysfunction-related disease, but also provide important parameters for disease diagnosis, prevention, and early treatment. In this work, we introduce a comprehensive optical coherence tomography (OCT)-based functional imaging technology for the 3D measurement of the micro vessel networks’ structure, blood flow velocity, and the blood flow transit time. The M-mode data acquisition (repeated A-scans) was employed in this technique. For blood vessel 3D structure imaging, we developed a first order field autocorrelation function (g1)-based adaptive analysis method to suppress the blood vessel tail artifacts and enhance the blood flow in small vessels. For blood flow velocity 3D imaging, we developed a set of quantitative dynamic analysis methods to measure both the axial and total blood flow velocity of the complex vessel network. We further developed a graphing method to obtain the 3D topological parameters of the 3D vessel network, including the vessel skeleton, branching, vessel diameter, and the blood flow speed at each location. With those information, we are able to, to the best of our knowledge, obtain the 3D blood transit time in the complex vessel network for the first of time. The proposed technique has the advantage of obtaining these three important blood flow biomarkers from a single data acquisition, which greatly simplifies the experiment procedure. The proposed OCT approach has a wide application in the field of microcirculation dysfunction-related disease studies.
SignificanceThe 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.AimWe 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).ApproachWe 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.ResultsWe 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.ConclusionsThe 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.
In this work, we proposed a novel normalized filed autocorrelation function (g1) –based functional ultrasound (fUS). We introduced a metrics derived from g1 function of ultrasound signals that is inversely proportional to blood flow and validated g1-fUS with in vivo experiments of whisker stimulation. Results show that g1-fUS is able to detect blood flow speed change in response to enhanced neural activity and is not affected by clutters compared to power Doppler based fUS, indicating that g1-fUS is a good candidate for whole brain functional imaging in small animals.
Significance: A long-standing challenge of the blood vessel tail artifacts along the axial direction prevents optical coherence tomography angiography (OCTA) for a comprehensive three-dimensional (3D) vascular mapping. Addressing the blood vessel tail artifacts issue will make OCTA to be a real 3D blood vessel structural imaging technique, which in combination with OCT-based blood flow velocity measurements will pave the way for a simpler and robust 3D imaging of the capillary transit time, one important parameter for the evaluation of micro circulation.
Approach: We first described the basic principles of OCTA imaging, discussed the origin of blood vessel tail artifacts in an OCTA image, then reviewed the existing OCTA techniques for tail artifacts suppression, and at last we envisioned the potential solutions for effective OCTA tail artifacts suppression.
Results: The origin of blood vessel tail artifacts is due to the multiple scattering of photons with flowing red blood cells, which elongates the light path of the dynamic signal from vessel lumen to the tail regions. High numerical aperture implementation, subtraction-based post-data processing, Hessian filtering, and high acquisition rate-based dynamic analysis methods have been proposed to address the blood vessel tail artifacts issue in OCTA.
Conclusions: High acquisition rate-based dynamic analysis in combination with Hessian filtering have the potential to effectively suppress the blood vessel tail artifacts and in the meantime preserve flows in small vessels within the tail region, providing real 3D OCTA imaging of blood vessel structures.
We present the use of intrinsic optical signal imaging to monitor the progression of ischemic stroke in the acute and chronic phases of recovery. An optimized mouse photothrombosis stroke model is used to induce stroke in the sensory forelimb area and longitudinal recovery is assessed using resting state functional connectivity as well as forelimb stimulation. These functional measures are then correlated with behavioral outcome assessed with a forelimb asymmetry test. Obtaining measures in both the acute and chronic phases of recovery will enable better interpretation of human functional neuroimaging stroke studies and allow their use in understanding acute stroke.
We report optical coherence tomography (OCT) imaging of localized fast optical signals (FOS) arising from whisker stimulation in awake mice. The activated voxels were identified by fitting the OCT intensity signal time course with a response function over a time scale of a few hundred milliseconds after the whisker stimulation. The significantly activated voxels were shown to be localized to the expected brain region for whisker stimulation. The ability to detect functional stimulation-evoked, depth resolved FOS with intrinsic contrast from the cortex provides a new tool for neural activity studies.
Scanning microscopy’s resolution of highly localized dynamics in awake animals is limited by bulk motion. We present a modular optical flow sensor based on spectral domain OCT which measures the specimen’s 3D displacement in real-time. A rose-function scan pattern rapidly acquires B-lines used to estimate displacements via an adaptive cross-correlation approach. Axial displacements are estimated from phase fluctuations apparent in the cross-correlation of the complex SD-OCT signal. The technique’s 3-dimensional readout rate and sensitivity to physiologically-relevant motion frequencies and magnitudes is evaluated.
Photoacoustic tomography (PAT) reconstruction with linear transducer arrays suffers from limited view artifacts, which impairs the reconstruction accuracy. Here, we introduce a modified Tikhonov regularization method to include vascular map obtained by Ultrasound localized microscopy (ULM) as a spatial prior in PAT reconstruction. We suggest an approach based on L-curve and Pearson correlation map to guide the selection of optimal regularization parameters. Simulation results suggest that spatial prior-based Tikhonov regularization can effectively address the limited view artifacts of PAT reconstruction with linear transducer arrays, paving the way of integrating PAT with ULM to enhance reconstruction accuracy in limited-view PAT.
We present a framework to coregister a large set of blood flow measurements from the cortical microvascular segments obtained by DLS-OCT with the microvascular angiogram obtained using TPM. By using this framework, we estimated the distributions of the mean RBC velocities in arterioles, venules, and capillaries, and as a function of the branching order from over 1,000 microvascular segments. The developed tools will help with more quantitative analysis of the large data sets obtained by OCT and TPM in the studies involving normal brain functioning, progression of various diseases, and numerical modeling of the oxygen transport in the microvascular networks.
Significance: The optical properties of biological samples provide information about the structural characteristics of the tissue and any changes arising from pathological conditions. Optical coherence tomography (OCT) has proven to be capable of extracting tissue’s optical properties using a model that combines the exponential decay due to tissue scattering and the axial point spread function that arises from the confocal nature of the detection system, particularly for higher numerical aperture (NA) measurements. A weakness in estimating the optical properties is the inter-parameter cross-talk between tissue scattering and the confocal parameters defined by the Rayleigh range and the focus depth.
Aim: In this study, we develop a systematic method to improve the characterization of optical properties with high-NA OCT.
Approach: We developed a method that spatially parameterizes the confocal parameters in a previously established model for estimating the optical properties from the depth profiles of high-NA OCT.
Results: The proposed parametrization model was first evaluated on a set of intralipid phantoms and then validated using a low-NA objective in which cross-talk from the confocal parameters is negligible. We then utilize our spatially parameterized model to characterize optical property changes introduced by a tissue index matching process using a simple immersion agent, 2,2’-thiodiethonal.
Conclusions: Our approach improves the confidence of parameter estimation by reducing the degrees of freedom in the non-linear fitting model.
Animal models of stroke are used extensively to study the mechanisms involved in the acute and chronic phases of recovery following stroke. A translatable animal model that closely mimics the mechanisms of a human stroke is essential in understanding recovery processes as well as developing therapies that improve functional outcomes. We describe a photothrombosis stroke model that is capable of targeting a single distal pial branch of the middle cerebral artery with minimal damage to the surrounding parenchyma in awake head-fixed mice. Mice are implanted with chronic cranial windows above one hemisphere of the brain that allow optical access to study recovery mechanisms for over a month following occlusion. Additionally, we study the effect of laser spot size used for occlusion and demonstrate that a spot size with small axial and lateral resolution has the advantage of minimizing unwanted photodamage while still monitoring macroscopic changes to cerebral blood flow during photothrombosis. We show that temporally guiding illumination using real-time feedback of blood flow dynamics also minimized unwanted photodamage to the vascular network. Finally, through quantifiable behavior deficits and chronic imaging we show that this model can be used to study recovery mechanisms or the effects of therapeutics longitudinally.
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.
Blood flow imaging is an essential part of biomedical research, particularly in the vascular and neurovascular physiology. It includes various imaging modalities, with laser speckle contrast imaging (LSCI) being one of the most extensively used tools for the rapid wide-field flow characterization.
For years, the capability of LSCI to become a quantitative tool has been discussed. Being based on the contrast relation to the speckle correlation time, the method requires a robust model and its correct parametrization. Main uncertainties are (i) light scattering and particle motion regimes which define the form of the field autocorrelation function g1 and (ii) static scattering and speckle averaging effects on the intensity correlation function g2. Multi-exposure laser speckle contrast imaging and proper system calibration can solve the later issue, but in order to evaluate g1 form, one has to directly measure speckle autocorrelation.
We introduce the dynamic laser speckle imaging (DLSI) as a new step in the wide-field speckle dynamics analysis. By utilizing a high-speed camera and recording backscattered light at more than 20000 frames per second we are able to measure the temporal intensity correlation (g2) in the mice cortex. We demonstrate that DLSI data can be used to estimate all parameters of the speckle autocorrelation model. By finding the best fit model for each pixel, we show that all three types of known g1 models can be found in the cortex and that the best fit model depends on the vessel size. Furthermore, we explore the commonly used model for the blood flow index and explain its deviations from the actual flow speed. We show that DLSI can be used to calibrate LSCI, thus solving contrast imaging problems and providing a lightweight quantitative tool for the blood flow imaging.
Optical coherence tomography angiography (OCTA) has been widely used for en face visualization of vasculatures but challenged for real 3D topologic imaging due to the ‘tail’ artifacts that appear below large vessel because of multiple scattered light within the vessel. We introduce a normalized field autocorrelation function-based OCTA (𝒈𝟏-OCTA) which minimizes the projection artifacts and is capable of 3D topologic vasculature imaging. 𝒈𝟏(τ) is calculated from repeated OCT acquisitions for each spatial location. The largest decay 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 (RBCs) are flowing slowly and discontinuously, Intralipid is injected to enhance the OCT signal. With the Intralipid-enhanced signal and shorter decorrelation time processing, we demonstrate that the proposed technique realized 3D OCTA with high signal-to-noise ratio and a negligible ‘tail’ projection. In addition, compared to regular OCTA, the proposed 𝒈𝟏-OCTA doubles the imaging depth. By reducing ‘tail’ artifacts, this technique provides a more accurate rendering of the vascular anatomy for more quantitative characterization of the vascular networks.
Quantitative measurement of blood flow velocity in capillaries is challenging due to their small size (around 5-10 μm), and the discontinuity and single-file feature of RBCs flowing in a capillary. In this work, we present a phase-resolved Optical Coherence Tomography (OCT) method for accurate measurement of the red blood cell (RBC) speed in cerebral capillaries. To account for the discontinuity of RBCs flowing in capillaries, we applied an M-mode scanning strategy that repeated A-scans at each scanning position for an extended time. As the capillary size is comparable to the OCT resolution size (3.5×3.5×3.5μm), we applied a high pass filter to remove the stationary signal component so that the phase information of the dynamic component (i.e. from the moving RBC) could be enhanced to provide an accurate estimate of the RBC axial speed. The phase-resolved OCT method accurately quantifies the axial velocity of RBC’s from the phase shift of the dynamic component of the signal. We validated our measurements by RBC passage velocimetry using the signal magnitude of the same OCT time series data. These proposed method of capillary velocimetry proved to be a robust method of mapping capillary RBC speeds across the micro-vascular network.
Dynamic Light Scattering-Optical Coherence Tomography (DLS-OCT) takes the advantages of using DLS to measure particle flow and diffusion within an OCT resolution-constrained 3D volume, enabling the simultaneous measurements of absolute RBC velocity and diffusion coefficient with high spatial resolution. In this work, we applied DLS-OCT to measure both RBC velocity and the shear-induced diffusion coefficient within penetrating venules of the somatosensory cortex of anesthetized mice. Blood flow laminar profile measurements indicate a blunted laminar flow profile, and the degree of blunting decreases with increasing vessel diameter. The measured shear-induced diffusion coefficient was proportional to the flow shear rate with a magnitude of ~ 0.1 to 0.5 × 10-6 mm2 . These results provide important experimental support for the recent theoretical explanation for why DCS is dominantly sensitive to RBC diffusive motion.
Optical coherence tomography (OCT) can obtain light scattering properties with a high resolution, while photoacoustic
imaging (PAI) is ideal for mapping optical absorbers in biological tissues, and ultrasound (US) could penetrate deeply
into tissues and provide elastically structural information. It is attractive and challenging to integrate these three imaging
modalities into a miniature probe, through which, both optical absorption and scattering information of tissues as well as
deep-tissue structure can be obtained. Here, we present a novel side-view probe integrating PAI, OCT and US imaging
based on double-clad fiber which is used as a common optical path for PAI (light delivery) and OCT (light
delivery/detection), and a 40 MHz unfocused ultrasound transducer for PAI (photoacoustic detection) and US
(ultrasound transmission/receiving) with an overall diameter of 1.0 mm. Experiments were conducted to demonstrate the
capabilities of the integrated multimodal imaging probe, which is suitable for endoscopic imaging and intravascular
imaging.
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