Webber, Matthew; (2024) Deep phenotyping of the ageing heart through CMR-ECGI - A cardiac sub-study of the MRC National Survey of Health and Development (NSHD). Doctoral thesis (Ph.D), UCL (University College London).

Text Matthew Webber PhD Feb 2024.pdf - Submitted Version Access restricted to UCL open access staff until 1 March 2029. Download (62MB)

Abstract

BACKGROUND: Cardiac ageing is highly individualised as a result of complex life-course exposures and the accumulation of both overt and subclinical myocardial disease. The National Survey of Health and Development (NSHD) is the world’s longest running birth cohort with continuous follow up and provides a unique opportunity to gain unprecedented insights into the cardiovascular health of the ageing heart. In order to examine the totality of myocardial dysfunction in older age, deep cardiac phenotyping is required through advanced cardiac magnetic resonance imaging (CMR) and non-invasive electrophysiological (EP) mapping. Electrocardiographic imaging (ECGI) non-invasively maps the heart’s electrical activity through multiple leads on the body surface. A safe, quick, affordable, and re-usable ECGI vest is needed to apply to patients undergoing CMR, but current solutions are not suitable for high-throughput use. AIMS: To set up MyoFit46, a cardiac sub-study of the NSHD along with its associated data storage and analysis pipelines and to utilise smart textile technology and semi-automated analysis techniques to fabricate a CMR-ECGI vest in order to generate novel, personalised EP biomarkers that could be used to better risk stratify those at risk of sudden cardiac death. METHODS: The MyoFit46 study protocol was set up and eligible NSHD study participants were prospectively recruited to undertake combined high-density surface ECGI and stress perfusion CMR. In order to perform large-scale clinical research into the pathophysiology of arrhythmogenesis and generate novel biomarkers of the EP derangements in ageing, I invented and patented the world’s first CMR-ECGI vest. The vest provides a safe, affordable, re-usable and non-invasive method for whole heart 3D mapping through ECGI whilst seamlessly integrating it with the multi-parametric myocardial tissue data obtained from CMR. RESULTS: After successfully setting up the study, I went on to recruit, personally scan, report, and analyse data from 204 NSHD participants (mean age 75 years) as well as 27 healthy volunteers (mean age 35 years) used as controls. The first prototype of the CMR-ECGI vest was fabricated using dry textile electrodes and advanced biomaterials along with state-of-the-art semi-automated post-processing pipelines. Healthy volunteer tests showed that the vest was quick to use, safe and well-tolerated in vivo. In 77 older age NSHD participants the vest was used with excellent tolerability and without complications. Accuracy of the entire pipeline was demonstrated by low intra and inter-observer variability and high scan re-scan repeatability. EP parameters obtained by CMR-ECGI tracked markers of diffuse fibrosis (extracellular volume) and inflammation (T2). Through international collaboration combining expertise across cardiac imaging, data science, computer programming, and medical engineering a second prototype of the CMR-ECGI vest was developed to further improve signal quality, performance efficiency and post processing time. This was deployed onto 204 NSHD participants generating segmental EP maps of the whole heart in vivo under physiological conditions. CONCLUSIONS: This thesis describes the most comprehensive CMR imaging protocol ever applied to an older age cohort to date and its seamless integration with ECGI. I brought together advancements in medical engineering and smart textile technology to fabricate, test and patent the CMR-ECGI vest which is now available for large-scale clinical, and research. The vest completes the totality of advanced cardiac phenotyping by layering EP substrate biomarkers to the multi-parametric data generated from CMR, in one complete examination. This novel device along with the biomarkers and phenotypic data generated from this work will provide unprecedented insights into cardiovascular ageing for years to come.

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