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.