Endovascular aortic repair (EVAR) is a minimally invasive alternative to open surgery for the treatment of aortic aneurysms (AA). However, standard EVAR is not applicable to complex AA with involvement of vital branches, which could be occluded by the endograft. As an emerging technique, the concept of multiple overlapping uncovered stents (MOUS) have been proposed to manage complex lesions. MOUS was used to modulate the flow pattern inside the aneurysm sac, and promote the thrombus formation followed by the aneurysm shrinkage. In this dissertation, we sought to investigate the mechanism of MOUS-induced flow modulation and key factors associated with the success of this novel technique: - The mechanical behaviour of AA was characterised by uniaxial material tests (Chapter 4). A Bayesian framework was proposed for material constants identification. They were found correlated to the microstructure of tissue fibre network and were capable in differentiating tissue types. - Solid-to-solid interaction and one-way fluid-solid interaction (FSI) analysis was performed based on patient-specific computer tomography angiography (Chapters 5&6). Structural stress concentrations were observed within the landing zones, which increased with the number of stents deployed. In the parameter studies (Chapter 6), the overall porosity was identified as the dominant factor of the flow-diverting outcome, while cross-stent structures of MOUS had limited influence. - The pathological effect of structural stress concentration induced by an implanted device was further studied in rabbit models (Chapter 7). The wall structural stress and fluid shear stress were obtained from FSI analysis based on magnetic resonance imaging (MRI), and correlated to plaque characteristics. Both high structural stress and low fluid shear stress were found correlated to plaque initialisation and increased inflammation. Overall, MOUS modulates the blood flow with robust performance under different overlapping patterns. Image-based biomechanical analysis can optimise MOUS design and can contribute to personalised pre-surgery planning.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:763905 |
| Date | January 2019 |
| Creators | Wang, Shuo |
| Contributors | Teng, Zhongzhao ; Gillard, Jonathan |
| Publisher | University of Cambridge |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | https://www.repository.cam.ac.uk/handle/1810/288381 |
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