Description du projet
Modèle innovant pour étudier la dynamique respiratoire pulmonaire
Le projet BREATHE, financé par l’UE, vise à développer le premier modèle informatique complet du système respiratoire, basé sur les avancées récentes de la simulation haute performance. La stratégie s’appuiera sur un modèle récent d’un solveur de flux incompressible prêt pour l’exascale qui sera modifié pour les défis spécifiques aux poumons et comprendra des capacités permettant de capturer l’interaction tissulaire et le transport de gaz. La zone respiratoire sera représentée par des milieux poroélastiques multiphases avec des limites pleurales spécifiques, et la circulation pulmonaire couplée sera représentée par un réseau dimensionnel réduit intégré et des phases supplémentaires. L’individualisation du modèle et l’adaptation aux conditions de progression de la maladie seront réalisées à l’aide d’une nouvelle approche d’apprentissage probabiliste. Le système modèle développé fournira des informations sur les processus dynamiques dans les poumons humains pour les scientifiques et les praticiens biomédicaux.
Objectif
While the human lung is undoubtedly an essential organ, and respiratory diseases are leading causes of death and disability in the world, there still exist a lot of mysteries wrt vital processes. The main reason for this is the complete lack of measurement methods or medical imaging techniques that would allow to study dynamic processes in essential parts of a living human lung. While this would be a perfect setup for computational modeling, existing models suffer from severe constraints disabling them to unveil those essential secrets. This project aims to build on a number of most promising recent advances in modeling and high-performance simulation to present the first comprehensive computational model of the respiratory system. For this purpose, it builds upon a recent exascale-ready incompressible flow solver, toughen it up for lung specific challenges and enrich it with multiphysics capabilities to capture tissue interaction and gas transport. Parts of the respiratory zone will be represented by multiphase poroelastic media and novel pleural boundary conditions will be developed. The coupled pulmonary circulation will be included and represented by an embedded reduced dimensional network and additional phases. In order to appropriately individualize the model and also being able to adapt it during disease progression, a novel physics-based probabilistic learning approach will be developed. This will allow to use most of the very diverse and scarce data in clinical settings. Finally, special models will be developed to bridge to the micro scale. The models developed and studied here will provide unprecedented insights for biomedical scientists, and practitioners at the same time, and will help to substantially reduce elaborate animal and multicenter studies. This will be a crucial step in order to establish a shift of paradigm in health care. Novel models/tools developed here will also be very useful in other areas of biomedical engineering and beyond.
Champ scientifique
- medical and health sciencesclinical medicinepneumology
- medical and health sciencesmedical biotechnology
- medical and health scienceshealth sciencesinfectious diseasesRNA virusescoronaviruses
- natural sciencesbiological sciencesbiophysics
- natural sciencescomputer and information sciencescomputational sciencemultiphysics
Mots‑clés
Programme(s)
Thème(s)
Régime de financement
ERC-ADG - Advanced GrantInstitution d’accueil
80333 Muenchen
Allemagne