PHENOTYPING RIGHT VENTRICULAR STRUCTURE AND FUNCTION USING ECHOCARDIOGRAPHY AND CARDIAC MAGNETIC RESONANCE IN ARRHYTHMOGENIC RIGHT VENTRICULAR CARDIOMYOPATHY
dc.contributor.advisor | Rick, Steeds | |
dc.contributor.author | Aljehani, Areej | |
dc.date.accessioned | 2025-08-21T09:29:37Z | |
dc.date.issued | 2025 | |
dc.description | Arrhythmogenic right ventricular cardiomyopathy ARVC) is a rare inherited disease characterised by an increased risk of ventricular arrhythmias and sudden cardiac death often presenting before structural changes are apparent. Early detection and risk stratification for major adverse cardiac events are crucial to improving patient outcomes. However, limited data exist on identifying patients at high risk for MACE. This thesis aimed to comprehensively characterise, over time, a cohort of ARVC patients from a large tertiary university centre, with a focus on advanced cardiovascular imaging findings. It encompassed both retrospective and prospective studies across different disease stages of ARVC. We identified significant differences between definite and early stages of ARVC, with structural progression strongly associated with an increased risk of MACE. Notably, advanced imaging techniques, particularly strain imaging, demonstrated superior performance in detecting structural abnormalities and predicting MACE compared to conventional imaging parameters. Exercise-derived strain imaging showed superior diagnostic value compared to conventional resting measures. These findings highlight the importance of incorporating advanced imaging tools into the routine assessment and risk stratification of ARVC patients to enable early intervention and improve long-term outcomes. | |
dc.description.abstract | Arrhythmogenic right ventricular cardiomyopathy ARVC) is a rare inherited disease characterised by an increased risk of ventricular arrhythmias and sudden cardiac death often presenting before structural changes are apparent. Early detection and risk stratification for major adverse cardiac events are crucial to improving patient outcomes. However, limited data exist on identifying patients at high risk for MACE. This thesis aimed to comprehensively characterise, over time, a cohort of ARVC patients from a large tertiary university centre, with a focus on advanced cardiovascular imaging findings. It encompassed both retrospective and prospective studies across different disease stages of ARVC. We identified significant differences between definite and early stages of ARVC, with structural progression strongly associated with an increased risk of MACE. Notably, advanced imaging techniques, particularly strain imaging, demonstrated superior performance in detecting structural abnormalities and predicting MACE compared to conventional imaging parameters. Exercise-derived strain imaging showed superior diagnostic value compared to conventional resting measures. These findings highlight the importance of incorporating advanced imaging tools into the routine assessment and risk stratification of ARVC patients to enable early intervention and improve long-term outcomes. | |
dc.format.extent | 233 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14154/76233 | |
dc.language.iso | en | |
dc.publisher | Saudi Digital Library | |
dc.subject | rrhythmogenic right ventricular cardiomyopathy | |
dc.subject | Ventricular arrhythmias | |
dc.subject | Sudden cardiac death | |
dc.subject | Major adverse cardiac events | |
dc.subject | Risk stratification | |
dc.subject | Advanced cardiovascular imaging | |
dc.subject | Echocardiography | |
dc.subject | Cardiac magnetic resonance | |
dc.subject | Strain imaging | |
dc.subject | Exercise-derived strain imaging | |
dc.subject | Prognosis | |
dc.title | PHENOTYPING RIGHT VENTRICULAR STRUCTURE AND FUNCTION USING ECHOCARDIOGRAPHY AND CARDIAC MAGNETIC RESONANCE IN ARRHYTHMOGENIC RIGHT VENTRICULAR CARDIOMYOPATHY | |
dc.type | Thesis | |
sdl.degree.department | Cardiovascular Sciences | |
sdl.degree.discipline | Medical Sciences | |
sdl.degree.grantor | University of Birmingham | |
sdl.degree.name | DOCTOR OF PHILOSOPHY |