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Erschienen in: Acta Mechanica Sinica 2/2017

10.03.2017 | Research Paper

Optimal flow conditions of a tracheobronchial model to reengineer lung structures

verfasst von: Stefano Casarin, Federico Aletti, Giuseppe Baselli, Marc Garbey

Erschienen in: Acta Mechanica Sinica | Ausgabe 2/2017

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Abstract

The high demand for lung transplants cannot be matched by an adequate number of lungs from donors. Since fully ex-novo lungs are far from being feasible, tissue engineering is actively considering implantation of engineered lungs where the devitalized structure of a donor is used as scaffold to be repopulated by stem cells of the receiving patient. A decellularized donated lung is treated inside a bioreactor where transport through the tracheobronchial tree (TBT) will allow for both deposition of stem cells and nourishment for their subsequent growth, thus developing new lung tissue. The key concern is to set optimally the boundary conditions to utilize in the bioreactor. We propose a predictive model of slow liquid ventilation, which combines a one-dimensional (1-D) mathematical model of the TBT and a solute deposition model strongly dependent on fluid velocity across the tree. With it, we were able to track and drive the concentration of a generic solute across the airways, looking for its optimal distribution. This was given by properly adjusting the pumps’ regime serving the bioreactor. A feedback system, created by coupling the two models, allowed us to derive the optimal pattern. The TBT model can be easily invertible, thus yielding a straightforward flow/pressure law at the inlet to optimize the efficiency of the bioreactor.

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Metadaten
Titel
Optimal flow conditions of a tracheobronchial model to reengineer lung structures
verfasst von
Stefano Casarin
Federico Aletti
Giuseppe Baselli
Marc Garbey
Publikationsdatum
10.03.2017
Verlag
The Chinese Society of Theoretical and Applied Mechanics; Institute of Mechanics, Chinese Academy of Sciences
Erschienen in
Acta Mechanica Sinica / Ausgabe 2/2017
Print ISSN: 0567-7718
Elektronische ISSN: 1614-3116
DOI
https://doi.org/10.1007/s10409-017-0644-0

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