Descrizione del progetto
Un modello innovativo per studiare la dinamica respiratoria dei polmoni
Il progetto BREATHE, finanziato dall’UE, si propone di sviluppare il primo modello computazionale completo del sistema respiratorio, basato sui recenti progressi nella simulazione ad alte prestazioni. La strategia sfrutterà il modello recente di un solutore di flusso incomprimibile pronto per la scala exa, che sarà modificato per eventuali sfide specifiche del polmone e includerà capacità di catturare l’interazione dei tessuti e il trasporto di gas. La zona respiratoria sarà rappresentata da mezzi poroelastici multifase con confini pleurici specifici, e la circolazione polmonare accoppiata sarà rappresentata da una rete dimensionale ridotta incorporata e da fasi aggiuntive. L’individualizzazione del modello e l’adattamento alle condizioni di progressione della malattia saranno ottenuti utilizzando un nuovo approccio di apprendimento probabilistico. Il sistema di modelli sviluppato fornirà informazioni sui processi dinamici nei polmoni umani per gli scienziati biomedici e i professionisti.
Obiettivo
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.
Campo scientifico
- 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
Parole chiave
Programma(i)
Argomento(i)
Meccanismo di finanziamento
ERC-ADG - Advanced GrantIstituzione ospitante
80333 Muenchen
Germania