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.
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.