A constrained independent component analysis technique for artery–vein separation of two-photon laser scanning microscopy images of the cerebral microvasculature

Identification of cortical arteries and veins in awake mice using two-photon microscopy

Distinguishing arteries from veins in the cerebral cortex is critical for studying hemodynamics under pathophysiological conditions, which plays an important role in the diagnosis and treatment of various vessel-related diseases. However, due to the complexity of the cerebral vascular network, it is challenging to identify arteries and veins in vivo. Here, we demonstrate an artery-vein separation method that employs a combination of multiple scanning modes of two-photon microscopy and a custom-designed stereoscopic fixation device for mice. In this process, we propose a novel method for determining the line scanning direction, which allows us to determine the blood flow directions. The vasculature branches have been identified using an optimized z-stack scanning mode, followed by the separation of blood vessel types according to the directions of blood flow and branching patterns. Using this strategy, the penetrating arterioles and penetrating venules in awake mice could be accurately identified and the type of cerebral thrombus has been also successfully isolated without any empirical knowledge or algorithms. Our research presents a new, more accurate, and efficient method for cortical artery-vein separation in awake mice, providing a useful strategy for the application of two-photon microscopy in the study of cerebrovascular pathophysiology.

Imaging and graphing of cortical vasculature using dynamically focused optical coherence microscopy angiography

Recently, optical coherence tomography (OCT) angiography has enabled label-free imaging of vasculature based on dynamic scattering in vessels. However, quantitative volumetric analysis of the vascular networks depicted in OCT angiography data has remained challenging. Multiple-scattering tails (artifacts specific to the imaging geometry) make automated assessment of vascular morphology problematic. We demonstrate that dynamically focused optical coherence microscopy (OCM) angiography with a high numerical aperture, chosen so the scattering length greatly exceeds the depth-of-field, significantly reduces the deleterious effect of multiple-scattering tails in synthesized angiograms. Capitalizing on the improved vascular image quality, we devised and tailored a self-correcting automated graphing approach that achieves a reconstruction of cortical microvasculature from OCM angiography data sets with accuracy approaching that attained by trained operators. The automated techniques described here will facilitate more widespread study of vascular network topology in health and disease.

Multi-dimensional complete ensemble empirical mode decomposition with adaptive noise applied to laser speckle contrast images

Laser speckle contrast imaging (LSCI) is a noninvasive full-field optical technique which allows analyzing the dynamics of microvascular blood flow. LSCI has attracted attention because it is able to image blood flow in different kinds of tissue with high spatial and temporal resolutions. Additionally, it is simple and necessitates low-cost devices. However, the physiological information that can be extracted directly from the images is not completely determined yet. In this work, a novel multi-dimensional complete ensemble empirical mode decomposition with adaptive noise (MCEEMDAN) is introduced and applied in LSCI data recorded in three physiological conditions (rest, vascular occlusion and post-occlusive reactive hyperaemia). MCEEMDAN relies on the improved complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and our algorithm is specifically designed to analyze multi-dimensional data (such as images). Over the recent multi-dimensional ensemble empirical mode decomposition (MEEMD), MCEEMDAN has the advantage of leading to an exact reconstruction of the original data. The results show that MCEEMDAN leads to intrinsic mode functions and residue that reveal hidden patterns in LSCI data. Moreover, these patterns differ with physiological states. MCEEMDAN appears as a promising way to extract features in LSCI data for an improvement of the image understanding.

Quantitative estimates of stimulation-induced perfusion response using two-photon fluorescence microscopy of cortical microvascular networks

Functional hyperemia, or the increase in focal perfusion elicited by neuronal activation, is one of the primary functions of the neurovascular unit and a hallmark of healthy brain functioning. While much is known about the hemodynamics on the millimeter to tenths of millimeter-scale accessible by MRI, there is a paucity of quantitative data on the micrometer-scale changes in perfusion in response to functional stimulation. We present a novel methodology for quantification of perfusion and intravascular flow across the 3D microvascular network in the rat somatosensory cortex using two-photon fluorescence microscopy (2PFM). For approximately 96% of responding microvessels in the forelimb representation of the primary somatosensory cortex, brief (~2s) forepaw stimulation resulted in an increase of perfusion 20±4% (mean±sem). The perfusion levels associated with the remaining 4% of the responding microvessels decreased 10±9% upon stimulation. Vessels irrigating regions of lower vascular density were found to exhibit higher flow (p<0.02), supporting the notion that local vascular morphology and hemodynamics reflect the metabolic needs of the surrounding parenchyma. High dispersion (~77%) in perfusion levels suggests high spatial variation in tissue susceptibility to hypoxia. The current methodology enables quantification of absolute perfusion associated with individual vessels of the cortical microvascular bed and its changes in response to functional stimulation and thereby provides an important tool for studying the cellular mechanisms of functional hyperemia, the spatial specificity of perfusion response to functional stimulation, and, broadly, the micrometer-scale relationship between vascular morphology and function in health and disease.