Abstract
Tracheobronchial stents are most commonly used to restore patency to airways stenosed by tumour growth. Currently all tracheobronchial stents are associated with complications such as stent migration, granulation tissue formation, mucous plugging and stent strut fracture. The present work develops a computational framework to evaluate tracheobronchial stent designs in vivo. Pressurised computed tomography is used to create a biomechanical lung model which takes into account the in vivo stress state, global lung deformation and local loading from pressure variation. Stent interaction with the airway is then evaluated for a number of loading conditions including normal breathing, coughing and ventilation. Results of the analysis indicate that three of the major complications associated with tracheobronchial stents can potentially be analysed with this framework, which can be readily applied to the human case. Airway deformation caused by lung motion is shown to have a significant effect on stent mechanical performance, including implications for stent migration, granulation formation and stent fracture.
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Acknowledgements
The research leading to these results has received funding from the European Union’s Seventh Framework Programme (FP7/2007-2013 under grant agreement \(\hbox {n} {^{\circ }}\) NMP3-SL-2012-280915) PulmoStent. Funding from the College of Engineering and Informatics at NUI Galway through a College Scholarship is also acknowledged, along with funding support provided by the Structured Ph.D. Programme in Biomedical Engineering and Regenerative Medicine (BMERM). Funded under the Programme for Research in Third-Level Institutions (PRTLI) Cycle 5 (Strand 2) and co-funded under the European Regional Development Fund (ERDF). The authors wish to acknowledge the SFI/HEA Irish Centre for High-End Computing (ICHEC) for the provision of computational facilities and support.
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McGrath, D.J., Thiebes, A.L., Cornelissen, C.G. et al. An ovine in vivo framework for tracheobronchial stent analysis. Biomech Model Mechanobiol 16, 1535–1553 (2017). https://doi.org/10.1007/s10237-017-0904-8
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DOI: https://doi.org/10.1007/s10237-017-0904-8