Context & Objectives
The lungs are the primary organs of the respiratory system in humans and many animals, responsible for molecular exchanges between external air and internal blood through mechanical ventilation. They have an extraordinary complex architecture, with the inherent fractal structure of the bronchial and blood vessel trees, as well as the hierarchical structure of the parenchyma. Lung biomechanics has been extensively studied by physiologists, experimentally as well as theoretically, from the air flow, blood flow and tissue stress points of view, laying the ground for our current fundamental understanding of the relationship between function and mechanical behavior. However, many questions remain, notably in the intricate coupling between the multiple constituents, between the many phenomena taking place at different spatial and temporal scales in health and disease, and these fundamental questions represent real clinical challenges, as pulmonary diseases are an important health burden.
The MΞDISIM team, joint between the Solid Mechanics Laboratory of École Polytechnique and INRIA has recently developed a lung model [1] based on a general formulation of poromechanics [2]. The model can be personalized for a given patient by assimilating clinical data, with the aim of providing computational tools to clinicians for better diagnosing and in fine treating patients suffering from various pulmonary diseases [3]. This work has been funded notably by an ANR Young Investigator grant (PI: Martin Genet) and an ANR COVID grant (PI: Pierre-Yves Brillet, APHP & Université Sorbonne Paris Nord/INSERM).
The project associated with the present PhD offer, funded by a European Innovation Council Pathfinder Open grant (PI: Xavier Maître, Université Paris-Saclay/CNRS), aims at developing low-field 3D magnetic resonance spirometry for advanced regional exploration of respiratory diseases. This would allow more widespread, totally innocuous and fully dynamics lung in vivo imaging, compared to the current state of the art based on expensive, ionizing and mostly static computed tomography scanners. This will however represent significant change to our modeling approach (from quasi-static to dynamic) and associated data assimilation pipeline (from computed tomography to magnetic resonance images), which will be the main objective of this PhD.
Keywords
Poromechanics; Pulmonary Biomechanics; Image-based Modeling; Finite Element Method; Data assimilation
Candidate profile
The candidate will have to master continuum mechanics (with, if possible, knowledge of finite strains & biomechanics) and numerical methods (notably the finite element method & integration schemes). He/She will also have an interest in the application in pulmonology, especially for interacting with clinical collaborators.
Work environment
The thesis will take place within the MΞDISIM team (joint between École Polytechnique & Inria and within the Solid Mechanics Laboratory), on the École Polytechnique campus. It will be in tight collaboration with other members of the EIC project, notably Télécom SudParis (Catalin Fetita) & Paris-Saclay University (Xavier Maître). It will be directed by Martin Genet, in direct collaboration with Dominique Chapelle. It could start in 2023, and could be preceded by an M2 internship.