Assessing the phenotypes of cardiovascular disease: The multimodality imaging approach

Cardiovascular diseases remain the leading cause of global mortality, driven by the ageing population and the inherent complexity of vascular anatomy and hemodynamics. This doctoral thesis presents a comprehensive, multimodal imaging approach designed to enhance clinical decision-making, procedural accuracy, and long-term outcomes. It integrates three core pillars: advanced three-dimensional imaging with computational fluid dynamics, detailed phenotyping of epicardial coronary artery disease using noninvasive and invasive modalities, and a multimodality strategy to diagnose and manage coronary microvascular dysfunction. Novel metrics, such as a cumulative plaque burden index (CPBi), left ventricular myocardial blood flow percentage (LV%MYO), and microvascular resistance reserve (MRR), are introduced and validated. Collectively, this thesis recognises significant limitations and unmet needs in cardiovascular disease phenotyping while underscoring the transformative potential of multimodal imaging and computational tools, paving the way for more precise, patient-specific diagnostic and therapeutic strategies. This thesis is structured into three interrelated parts, each addressing a distinct facet of cardiovascular phenotyping: Part A: Advanced 3D Imaging and Computational Fluid Dynamics (Chapters 2–6) Reviews the evolution of virtual, augmented, and mixed realities in cardiovascular medicine and demonstrates their application—together with patient-specific CFD modeling—in planning complex interventions such as coronary bypass surgery, graft sizing, and managing iatrogenic aortic dissection. Part B: Phenotyping Epicardial Coronary Artery Disease (Chapters 7–12) Explores how noninvasive coronary computed tomography angiography (CCTA), fractional flow reserve derived from CT, invasive pressure-wire pullbacks, and intravascular ultrasound can classify focal versus diffuse atherosclerosis. Highlights include the Heart Team paradigm, regional trends in stable chest-pain evaluation, the LV%MYO metric for revascularisation completeness, pressure gradient indices in FFR/iFR discordance, the impact of elevated lipoprotein(a), and the AI-driven CPBi. Part C: Multimodality Investigation of Coronary Microvascular Dysfunction (Chapters 13–20) Investigates the prevalence, mechanisms, and prognostic significance of microvascular dysfunction in ST-elevation myocardial infarction and angina with non-obstructive coronaries (ANOCA). Combines invasive indices (IMR, CFR, MRR), continuous thermodilution, exercise stress testing, novel biomarkers (TMAO), and the impact of severe COVID-19. Critically appraises angiography-derived IMR methodologies. A concluding chapter synthesises findings and outlines future research directions, emphasising personalised, image-guided therapies tailored to specific cardiovascular phenotypes.

Funder

University of Galway

Publisher

University of Galway

Rights

CC BY-NC-ND

cbn

Collections

University of Galway Theses (PhD Theses)