An ovine in vivo framework for tracheobronchial stent analysis

Donnacha J McGrath*, Anja Lena Thiebes, Christian G Cornelissen, Mary B O'Shea, Barry O'Brien, Stefan Jockenhoevel, Mark Bruzzi, Peter E McHugh*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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.

Original languageEnglish
Pages (from-to)1535-1553
Number of pages19
JournalBiomechanics and modeling in mechanobiology
Volume16
Issue number5
Early online date19 Apr 2017
DOIs
Publication statusPublished - Oct 2017

Keywords

  • Biomechanical
  • Lung
  • Tracheobronchial
  • Nitinol
  • Stenting
  • Finite element method
  • DEFORMABLE IMAGE REGISTRATION
  • LUNG MOTION
  • AIRWAY
  • MODELS
  • BRONCHOSCOPY
  • SIMULATION
  • PREDICTION
  • STRESSES
  • TRACHEA
  • DESIGN

Fingerprint

Dive into the research topics of 'An ovine in vivo framework for tracheobronchial stent analysis'. Together they form a unique fingerprint.

Cite this