From whole-organ imaging to in-silico blood flow modeling: A new multi-scale network analysis for revisiting tissue functional anatomy

Abstract

We present a multidisciplinary image-based blood flow perfusion modeling of a whole organ vascular network for analyzing both its structural and functional properties. We show how the use of Light-Sheet Fluorescence Microscopy (LSFM) permits whole-organ microvascular imaging, analysis and modelling. By using adapted image post-treatment workflow, we could segment, vectorize and reconstruct the entire micro-vascular network composed of 1.7 million vessels, from the tissue-scale, inside a * 25 × 5 × 1 = 125mm 3 volume of the mouse fat pad, hundreds of times larger than previous studies, down to the cellular scale at micron resolution, with the entire blood perfusion modeled. Adapted network analysis revealed the structural and functional organization of meso-scale tissue as strongly connected communities of vessels. These communities share a distinct heterogeneous core region and a more homogeneous peripheral region, consistently with known biological functions of fat tissue. Graph clustering analysis also revealed two distinct robust meso-scale typical sizes (from 10 to several hundred times the cellular size), revealing, for the first time, strongly connected functional vascular communities. These community networks support heterogeneous micro-environments. This work provides the proof of concept that in-silico all-tissue perfusion modeling can reveal new structural and functional exchanges between micro-regions in tissues, found from community clusters in the vascular graph.

Tissue clearing and imaging methods for cardiovascular development

“…A special field of image segmentation is vasculature segmentation, where vessels can be segmented and skeletonized and branching points established, and 3D vasculature network can then be reconstructed ( Park et al., 2015 ; Corliss et al., 2019 ; Kennel et al., 2018 ). As a next step, the blood flow can be computed and modeled ( Kennel et al., 2020 ).…”

“…Future will be also in combination with other visualizing and analyzing methods used on developing hearts, as physiological analysis of heart activation and conduction system analyzed by optical mapping. Image analysis also could be combined with advanced mathematical modeling, as in brain samples illustrated with blood flow modeling in brain capillaries ( Kennel et al., 2020 ; Perdikaris et al., 2016 ). For heart research the blood flow modeling in coronary vasculature would move the field significantly.…”

Unbiased analysis of obesity related, fat depot specific changes of adipocyte volumes and numbers using light sheet fluorescence microscopy

“…in the large animal model (LAM) of diet induced obesity (DIO) in Göttingen minipigs [6]. Methodologically, the use of an LSFM-based approach for quantitative volume-and numberanalyses of adipocytes was motivated by the principal advantages of LSFM-analyses, allowing for a quick and straightforward 3D-visualization and morphological analysis of tissue elements in optically cleared, intact (adipose) tissue samples [24,27,41]. Provided the reliability and accuracy of obtained measurement results, LSFM-based analyses thus hold a great potential to efficiently examine relevant quantitative (and qualitative) histomorphological parameters of adipocytes with less effort and analytical travail than conventional quantitative morphological analysis methods that depend on 2D histological sections.…”

“…Here, we report the application of 3D light sheet florescence microscopy (LSFM) of optically cleared adipose tissue samples as a simple, fast and elegant approach to characterize the relevant quantitative changes of adipose tissue and adipocyte morphology in different adipose tissue depots of the DIO minipig model. LSFM of optically cleared tissue specimen is a rapidly evolving imaging technique [19][20][21], allowing for direct 3D imaging of cellular details in tissue samples up to the size of several cm 3 , e.g., to visualize complex vascularization patterns of organs, tumor samples [22,23], or adipose tissue depots [24]. For LSFM, the tissue specimens are cleared, i.e., made optically transparent, using a variety of different possible methods and protocols.…”

“…[19][20][21]23,25,26]. In translational obesity research, LSFM has already proven its practicability for 3D imaging of adipose tissue, as well as for the visualization of sympathetic innervation, vascular networks, or inflammatory foci in cleared (murine) adipose tissue samples, using specific fluorescence labelled antibodies or lectins [24,27]. The swift and direct visualization of 3D tissue structures by LSFM, and the direct measurability of morphological features of these structures by digital 3D-image analysis could also efficiently simplify analyses of adipocyte volumes and numbers, which can, so far, only be determined unbiasedly using comparably elaborate and time-consuming quantitative stereological analysis methods.…”