Biology subjects

Glandorf, L.

Publications and source records attributed to Glandorf, L..

3 recordsLinked to original sources

bioRxiv2025

In Vivo Network-Level Cerebrovascular Mapping Reveals the Impact of Flow Topology on Capillary Stalls After Stroke

Cerebral microvasculature is essential for brain function, but how flow and large-scale connectivity contribute to its resilience or failure remains poorly understood. To address this, we developed OMNIMap, a framework for mesoscale in vivo mapping of functional microvascular networks, capturing flow dynamics and connectivity across thousands of capillaries. OMNIMap integrates extended-focus optical coherence microscopy and learning-based segmentation with global vessel-graph optimization to resolve artery-vein classification and branching order, linking capillary flow and stalls to broader network context. Applied to over 40,000 capillaries in the mouse cortex before and after ischemic stroke, we observe heterogeneous vulnerability patterns: while most capillaries stall or reduce flow after arterial occlusion, some experience accelerated flow. Further analysis revealed that stall-prone flow topology subtypes were less prevalent than their robust counterparts. Notably, the overall distribution of these subtypes remains largely preserved after stroke, revealing a previously unrecognized, system-level organizing principle that alleviates the impact of individual capillary stalls to maintain network-level perfusion.

neuroscience↗

bioRxiv2024

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

Understanding the morphology and function of large-scale cerebrovascular networks is crucial for studying brain health and disease. However, reconciling the demands for imaging on a broad scale with the precision of high-resolution volumetric microscopy has been a persistent challenge. In this study, we introduce Bessel beam optical coherence microscopy with an extended focus to capture the full cortical vascular hierarchy in mice over 1000 x 1000 x 360 m3 field-of-view at capillary level resolution. The post-processing pipeline leverages a supervised deep learning approach for precise 3D segmentation of high-resolution angiograms, hence permitting reliable examination of microvascular structures at multiple spatial scales. Coupled with high-sensitivity Doppler optical coherence tomography, our method enables the computation of both axial and transverse blood velocity components as well as vessel-specific blood flow direction, facilitating a detailed assessment of morpho-functional characteristics across all vessel dimensions. Through graph-based analysis, we deliver insights into vascular connectivity, all the way from individual capillaries to broader network interactions, a task traditionally challenging for in vivo studies. The new imaging and analysis framework extends the frontiers of research into cerebrovascular function and neurovascular pathologies.

bioengineering↗

bioRxiv2024

Pia-FLOW: Deciphering hemodynamic maps of the pial vascular connectome and its response to arterial occlusion

The pial vasculature is the sole source of blood supply to the neocortex. The brain is contained within the skull, a vascularized bone marrow with a unique anatomical connection to the brain. Recent developments in tissue clearing have enabled unprecedented mapping of the entire pial and calvarial vasculature. However, what are the absolute flow rates values of those vascular networks? This information cannot accurately be retrieved with the commonly used bioimaging methods. Here, we introduce Pia-FLOW, a new approach based on large-scale fluo-rescence localization microscopy, to attain hemodynamic imaging of the whole murine pial and calvarial vasculature at frame rates up to 1000 Hz and spatial resolution reaching 5.4 {micro}m. Using Pia-FLOW, we provide detailed maps of flow velocity, direction and vascular diameters which can serve as ground-truth data for further studies, advancing our understanding of brain fluid dynamics. Furthermore, Pia-FLOW revealed that the pial vascular network functions as one unit for robust allocation of blood after stroke.

neuroscience↗