Computational fluid dynamics as aid tool for the management of aortic wall diseases

Aortic aneurysms and dissections are pathological conditions affecting the aorta. Despite being different in clinical presentation, these pathologies share a high mortality rate, as well as a lack of reliable prognostic predictors. Local fluid dynamics is assumed to play a role in aortic patho-physiology and to be a key factor responsible for aortic weakening and expansion. In this context, the numerical modeling of aortic hemodynamics, by means of image-based computational fluid dynamics (CFD), gives access to patient-specific flow-related information that may complement medical imaging in the assessment of individual aortas and support outcomes prediction. Moreover, the deformability of the aortic wall appears to be related to its strength: areas at elevated strain may, therefore, indicate structural weakening. Based on these understandings, this research work proposes the use of hemodynamic descriptors, derived from CFD simulations, to correlate local altered flow patterns with aortic remodeling and weakening, and ultimately help defining a rationale for improved rupture risk stratification. Wall shear stress-based hemodynamic descriptors were used to retrospectively assess a population of uncomplicated type B aortic dissections (ADs) with known individual outcomes. The effect of rigid versus moving wall assumption on aortic flow patterns was explored by means of fluid-structure interaction (FSI) simulation. The results highlighted the need for a patient-tailored approach when evaluating ADs, and showed the potential of CFD-derived hemodynamics to complement anatomical assessment and assist outcomes prediction. The inclusion of wall motion in the simulation of a type B AD, led to differences in value for the hemodynamic wall descriptors, however, regions of interest with respect to altered flow patterns were consistently localized by both the CFD and FSI models. Finally, a combined CFD and in-vivo strain analysis approach was developed to assess local weakening and rupture risk for a population of AAAs. A novel index, Regional Rupture Potential, was defined and proved able to capture aortic regional weakening. This thesis demonstrated the importance of accessing hemodynamic information when assessing individual aortas with prognostic purposes, along with the potential of a novel combined approach to improve aortic assessment for risk stratification.

Name thesis:degree_name

Doctor of Philosophy (PhD)

Discipline thesis:degree_discipline

Engineering – Biomedical

Grantor dc:publisher.institution

Schulich School of Engineering

Year dc:date.issued

2019

Author dc:creator

• Forneris, Arianna

Advisor dc:contributor.advisor

• Di Martino, Elena S.

Committee members dc:contributor.committeemember

• Frayne, Richard
• Wood, David H.

• Biomechanics
• Computational fluid dynamics
• Aorta
• Aortic wall diseases
• Medical imaging

Statement dc:rights

• University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.

Language dc:language.iso

eng

DOI

http://dx.doi.org/10.11575/PRISM/37216

OAI identifier oai:identifier

oai:ucalgary.scholaris.ca:1880/111167