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Multiscale lung ventilation modeling in health and disease. (Modélisation multi-échelle du poumon dans des cas sains et pathologiques)

The lungs contain a tree through which the air flows. It supplies a porous region, the parenchyma, where gas exchanges with blood take place. Some pathologies affect the tree structure or the parenchyma integrity. They can induce ventilation defects or increased respiratory efforts. In vivo-studies are complex and mathematical modeling can provide some insights on the lung behavior, the pathologies’ impacts or the efficiency of treatments.In the first part of this thesis, we propose a ventilation model of the lung based on a mechanical description. A 0D tree is strongly coupled to a 3D parenchyma model. We show the influence of chosen boundary conditions as well as tree or parenchyma alterations on the ventilation distribution. Results are compared with those provided by a simpler model, often used in the literature.In a second part, we use the tree-parenchyma coupled model to investigate how breathing gas mixtures less dense than air would potentially reduce efforts and ensure a better ventilation. To that end, we build an asthmatic tree model.In the next part, we develop an approach to get insights on severe constrictions distribution based on the analysis of dynamic lung ventilation images. To do so, the coupled ventilation model is used along with a machine learning technique.Finally, two prospective works are presented. First, we propose extensions to the ventilation models introduced in the first part as a step towards spriometry modeling. The last study is part of a global perspective that aims at getting insights on the lung geometry based on simple measurements on the patient’s body.