Four-Dimensional Cardiac Magnetic Resonance Analysis in Patients with Atrial Fibrillation

Atrial fibrillation (AF) is a common cardiac arrhythmia characterized by disorganized electrical activity leading to irregular contractions and impaired cardiac output. AF significantly elevates the risk of thromboembolic stroke, primarily due to thrombus formation in the left atrium (LA) and left atrial appendage (LAA). while electrophysiological mechanisms of AF are well defined, the LA structural and functional remodelling drives AF onset, persistence, and stroke risk remains incompletely understood. Building on this, the LA plays a pivotal role in cardiac performance by facilitating ventricular filling through passive expansion and active contraction. Pathological remodelling characterized by dilation, fibrosis, and mechanical dysfunction can impair contractility and alter intra-atrial flow dynamics, predisposing to blood stasis and thrombogenesis. However, conventional risk stratification tools, such as CHA₂DS₂-VASc, inadequately capture these biomechanical and structural determinants of stroke risk, underscoring the need for more comprehensive, imaging-based predictive models. In response to these limitations, recent advancements in cardiac imaging, particularly four-dimensional (4D) flow magnetic resonance imaging (MRI), enable detailed assessment of time-resolved three-dimensional blood flow within the LA. This technique allows quantitative visualization of intra-atrial flow patterns, wall shear stress, and stasis, providing novel insights into the interplay between atrial morphology, flow physiology, and thromboembolic potential. Complementary techniques such as late gadolinium enhancement (LGE) MRI further delineate atrial fibrosis and tissue remodelling, offering additional prognostic value. This thesis investigates the utility of 4D flow cardiac MRI in evaluating LA remodelling and hemodynamics among patients with atrial fibrillation prior to catheter ablation. It critically examines existing clinical risk models and explores integrating advanced imaging biomarkers with traditional predictors to enhance stroke risk stratification. Through a multidisciplinary approach combining cardiovascular imaging, computational analysis, and clinical cardiology, this work aims to advance precision risk prediction in AF, improve patient selection for therapy, and ultimately reduce stroke incidence in this high-risk population.

Name thesis:degree_name

Master of Science (MSc)

Discipline thesis:degree_discipline

Medicine – Cardiovascular/Respiratory Science

Grantor dc:publisher.institution

Cumming School of Medicine

Year dc:date.issued

2026

Author dc:creator

• Sheitt, Hana

Advisors dc:contributor.advisor

• Garcia Flores, Julio
• White, James

Committee members dc:contributor.committeemember

• Duff, Henry
• Nygren, Andres
• Fine, Nowell

• Cardiac MRI

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

en

DOI

https://dx.doi.org/10.11575/PRISM/51187

OAI identifier oai:identifier

oai:ucalgary.scholaris.ca:1880/124353