Near-lifespan longitudinal tracking of brain microvascular morphology, topology, and flow in male mice

Abstract

In age-related neurodegenerative diseases, pathology often develops slowly across the lifespan. As one example, in diseases such as Alzheimer’s, vascular decline is believed to onset decades ahead of symptomology. However, challenges inherent in current microscopic methods make longitudinal tracking of such vascular decline difficult. Here, we describe a suite of methods for measuring brain vascular dynamics and anatomy in mice for over seven months in the same field of view. This approach is enabled by advances in optical coherence tomography (OCT) and image processing algorithms including deep learning. These integrated methods enabled us to simultaneously monitor distinct vascular properties spanning morphology, topology, and function of the microvasculature across all scales: large pial vessels, penetrating cortical vessels, and capillaries. We have demonstrated this technical capability in wild-type and 3xTg male mice. The capability will allow comprehensive and longitudinal study of a broad range of progressive vascular diseases, and normal aging, in key model systems.

Microvascular structure variability explains variance in fMRI functional connectivity

“…Such an analysis could be facilitated through the acquisition resting-state fMRI from individual subjects, followed by the application of methodologies described in recent literature to reconstruct the vasculature of the brain [22][23][24][25][26]. Additionally, this approach could prove valuable in researching neurovascular disorders to study the influence of variables such as sex, age, and disease on an individual's vascular structure [22,46,64] and how it's reflected in whole-brain functional connectivity.…”

Bessel Beam Optical Coherence Microscopy Enables Multiscale Assessment of Cerebrovascular Network Morphology and Function

“…Our method provides the high level of detail approaching that of 2PM while offering morphological information and total flow velocity measurements across all imaged vessels. Notably, a recent OCM study has looked into longitudinal vascular network alterations during the onset of Alzheimer’s disease 7 . However, conventional OCM approaches are plagued by hard compromises between the spatial resolution, depth of field and imaging speed, which limits their ability to extract and quantify vascular network characteristics across scales.…”

“…Due to extensive interconnectivity of the vasculature, many pathologies result in long- and short-term blood flow velocity alterations. For example, Alzheimer’s has been linked with long-term cortical hypoperfusion, affecting vessel diameters as well as blood flow velocities 6,7 . In stroke, a sudden local hypoperfusion is caused by obstruction of a major vessel, but blood flow may even increase in the surrounding regions in an attempt to compensate through the remaining vascular network 8 .…”

“…However, OCTA is plagued by image artifacts that often prohibit accurate volumetric blood vessel segmentation 18 . Nevertheless, recent deep learning segmentation approaches can adequately deal with OCTA artifacts and extract vascular networks, allowing vessel-wise quantitative analysis 7 . Yet, these approaches are currently unable to fully capture the cortical vasculature’s network characteristics, encompassing the blood flow from pial arteries into diving arterioles through the capillary bed and back through the venous tree.…”

Neuroinflammation increases oxygen extraction in a mouse model of Alzheimer’s disease

“…Some studies showed no obvious changes in CBF and capillary flow in young mice but severe reduction of flow and disturbed flow homogenization in aged transgenic mice [ 73 ]. Recent advances in optical coherence tomography (OCT) will help delineate the precise trajectory of hemodynamic alterations during AD by enabling near-lifespan tracking of microvascular morphology and function [ 117 ]. Lastly, estimating cerebral metabolic of oxygen (CMRO2) in response to inflammation using Krogh-Erlang model [ 118 ] or the recent proposed ODACITI model [ 119 ] could further validate our findings of increased oxygen extraction in inflamed AD brain tissue.…”