De l'imagerie tissu entier à la modélisation in silico du réseau vasculaire du tissu adipeux

Le tissu adipeux est traditionnellement décrit comme étant constitué de lobules : des entités de formes ovoïdales composées de cellules et de vaisseaux et faiblement connectées entre elles.Récemment, il a été montré qu’un potentiel métabolique spécifique (le browning) co-localise avec cette organisation en lobules au sein d’un même tissu. Dans ce travail de thèse, nous nous intéressons à décrire plus précisément l’organisation structurelle et fonctionnelle du tissu adipeux selon plusieurs aspects. Dans un premier temps, on s’attache à segmenter les lobules du tissu adipeux en utilisant une méthode de traitement d’image originale. Nous mettons en évidence une organisation 3D complexe et suivant plusieurs échelles. En particulier, il semble que le potentiel de browning soit également lié à une organisation structurelle particulière en clusters de lobules. Dans un second temps, à partir d’imagerie 3D, nous reconstruisons le réseau vasculaire entier du tissu adipeux et réalisons une simulation d’écoulements sanguins micro-vasculaires. Plusieurs hétérogénéités structurelles et fonctionnelles sont alors mises en valeurs à l’aide d’une analyse en communautés qui composent le tissu adipeux (par algorithme de clustering). Ces résultats confirment l’existence d’une zone centrale fortement vascularisée et qui se démarque également comme étant le lieu d’une perfusion sanguine d’intensité différente. Dans une dernière partie, nous abordons la question de transferts thermiques entre vaisseaux sanguins suivant des géométries simples mais pertinentes. Nous réalisons une étude systématique des paramètres adimensionnels clés du problème et mettons en évidence un invariant des échanges de chaleur : un optimum à faible nombre de Péclet (convection de même ordre que la diffusion). Nous introduisons également une méthode de calibration de paramètres effectifs dans le contexte des modèles homogénéisés de température à travers des tissus vascularisés

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

We present a multi-disciplinary 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 micro- vascular 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

3D analysis of the whole subcutaneous adipose tissue reveals a complex spatial network of interconnected lobules with heterogeneous browning ability

Adipose tissue, as the main energy storage organ and through its endocrine activity, is interconnected with all physiological functions. It plays a fundamental role in energy homeostasis and in the development of metabolic disorders. Up to now, this tissue has been analysed as a pool of different cell types with very little attention paid to the organization and putative partitioning of cells. Considering the absence of a complete picture of the intimate architecture of this large soft tissue, we developed a method that combines tissue clearing, acquisition of autofluorescence or lectin signals by confocal microscopy, segmentation procedures based on contrast enhancement, and a new semi-automatic image analysis process, allowing accurate and quantitative characterization of the whole 3D fat pad organization. This approach revealed the unexpected anatomic complexity of the murine subcutaneous fat pad. Although the classical picture of adipose tissue corresponds to a superposition of simple and small ellipsoidal lobules of adipose cells separated by mesenchymal spans, our results show that segmented lobules display complex 3D poly-lobular shapes. Despite differences in shape and size, the number of these poly-lobular subunits is similar from one fat pad to another. Finally, investigation of the relationships of these subunits between each other revealed a never-described organization in two clusters with distinct molecular signatures and specific vascular and sympathetic nerve densities correlating with different browning abilities. This innovative procedure reveals that subcutaneous adipose tissue exhibits a subtle functional heterogeneity with partitioned areas, and opens new perspectives towards understanding its functioning and plasticity

A proof-of-concept pipeline to guide evaluation of tumor tissue perfusion by dynamic contrast-agent imaging: Direct simulation and inverse tracer-kinetic procedures

Dynamic contrast-enhanced (DCE) perfusion imaging has shown great potential to non-invasively assess cancer development and its treatment by their characteristic tissue signatures. Different tracer kinetics models are being applied to estimate tissue and tumor perfusion parameters from DCE perfusion imaging. The goal of this work is to provide an in silico model-based pipeline to evaluate how these DCE imaging parameters may relate to the true tissue parameters. As histology data provides detailed microstructural but not functional parameters, this work can also help to better interpret such data. To this aim in silico vasculatures are constructed and the spread of contrast agent in the tissue is simulated. As a proof of principle we show the evaluation procedure of two tracer kinetic models from in silico contrast-agent perfusion data after a bolus injection. Representative microvascular arterial and venous trees are constructed in silico. Blood flow is computed in the different vessels. Contrast-agent input in the feeding artery, intra-vascular transport, intra-extravascular exchange and diffusion within the interstitial space are modeled. From this spatiotemporal model, intensity maps are computed leading to in silico dynamic perfusion images. Various tumor vascularizations (architecture and function) are studied and show spatiotemporal contrast imaging dynamics characteristic of in vivo tumor morphotypes. The Brix II also called 2CXM, and extended Tofts tracer-kinetics models common in DCE imaging are then applied to recover perfusion parameters that are compared with the ground truth parameters of the in silico spatiotemporal models. The results show that tumor features can be well identified for a certain permeability range. The simulation results in this work indicate that taking into account space explicitly to estimate perfusion parameters may lead to significant improvements in the perfusion interpretation of the current tracer-kinetics models

From full tissue imaging to in silico modelisation of adipose tissue vascular network

Le tissu adipeux est traditionnellement décrit comme étant constitué de lobules : des entités de formes ovoïdales composées de cellules et de vaisseaux et faiblement connectées entre elles.Récemment, il a été montré qu’un potentiel métabolique spécifique (le browning) co-localise avec cette organisation en lobules au sein d’un même tissu. Dans ce travail de thèse, nous nous intéressons à décrire plus précisément l’organisation structurelle et fonctionnelle du tissu adipeux selon plusieurs aspects. Dans un premier temps, on s’attache à segmenter les lobules du tissu adipeux en utilisant une méthode de traitement d’image originale. Nous mettons en évidence une organisation 3D complexe et suivant plusieurs échelles. En particulier, il semble que le potentiel de browning soit également lié à une organisation structurelle particulière en clusters de lobules. Dans un second temps, à partir d’imagerie 3D, nous reconstruisons le réseau vasculaire entier du tissu adipeux et réalisons une simulation d’écoulements sanguins micro-vasculaires. Plusieurs hétérogénéités structurelles et fonctionnelles sont alors mises en valeurs à l’aide d’une analyse en communautés qui composent le tissu adipeux (par algorithme de clustering). Ces résultats confirment l’existence d’une zone centrale fortement vascularisée et qui se démarque également comme étant le lieu d’une perfusion sanguine d’intensité différente. Dans une dernière partie, nous abordons la question de transferts thermiques entre vaisseaux sanguins suivant des géométries simples mais pertinentes. Nous réalisons une étude systématique des paramètres adimensionnels clés du problème et mettons en évidence un invariant des échanges de chaleur : un optimum à faible nombre de Péclet (convection de même ordre que la diffusion). Nous introduisons également une méthode de calibration de paramètres effectifs dans le contexte des modèles homogénéisés de température à travers des tissus vascularisés.Adipose tissue is traditionally described as consisting of lobules: ovoid-shaped entities composed of cells and vessels and weakly connected to each other. Recently, it has been shown that a specific metabolic potential (browning) colocalize with this organization in lobules within the same tissue. In this thesis work, we are interested in describing more precisely the structural and functional organization of adipose tissue from several aspects. We first perform a segmentation of adipose tissue lobules using an original image processing method. We highlight a complex 3D organization and relevant on several scales. In particular, it seems that browning potential is also linked to a particular structural organisation in clusters of lobules. In a second step, using 3D imaging, we reconstruct the entire vascular network of adipose tissue and simulate micro-vascular blood flow. Several structural and functional heterogeneities are then highlighted using an analysis in communities among adipose tissue (by clustering algorithm). These results confirm the existence of a highly vascularized central area that also stands out as the site of a more marked blood perfusion. In a last part, we approach the question of heat transfers between blood vessels following simple but relevant geometries. We carry out a systematic study of the key dimensionless parameters of the problem and highlight an invariant of heat exchanges: an optimum at low Péclet number (convection of the same order as diffusion). We also introduce a method of calibrating effective parameters in the context of homogenized temperature models across vascularized tissues

Thermal significance and optimal transfer in vessels bundles is influenced by vascular density

International audienceA semi-analytic method is used in order to systematically compute stationary 3-D coupled convection-diffusion in various parallel counter-current configurations and evaluate their thermal significance. This semi-analytic method permits a complete exploration of physiologically relevant parameter space associated with the bio-heat transfer of parallel vessels bundles. We analyze thermal significance with various previously proposed criteria. Optimal transfer configurations are found to depend on the vascular density and Péclet numbers. The relevance of these findings for bio-heat modeling in tissues is discussed

In-vitro to in-vivo acetaminophen hepatotoxicity extrapolation using classical schemes, pharmaco-dynamic models and a multiscale spatial-temporal liver twin

International audienceIn vitro to in vivo extrapolation represents a critical challenge in toxicology. In this paper we explore extrapolation strategies for acetaminophen (APAP) based on mechanistic models, comparing classical homogeneous compartment pharmaco-dynamic (PD) models and a multiscale digital twin model resolving liver microarchitecture at cellular resolution. The models integrate consensus detoxification reactions in each individual hepatocyte. We study the consequences of the two model types on the extrapolation and show in which cases these models perform better than the classical extrapolation strategy that is based either on the maximal drug concentration (Cmax) or the area under the pharmaco-kinetic curve (AUC) of the drug blood concentration. We find that an CL-model based on a well-mixed blood compartment is sufficient to correctly predict the in vivo toxicity from in vitro data. However, the ST-model that integrates more experimental information requires a change of at least one parameter to obtain the same prediction,indicating that spatial compartmentalization may indeed be an important factor