Chun Lap Pang

Abstract

Predicting cardiovascular events is an important subject in the developed world as it is a major cause of morbidity and mortality. Identifying those at risk of developing cardiovascular disease is key as there are treatments available to reduce the risk of future events. The most well-known prediction tool is the Framingham Risk Score (FRS), a multivariate cardiovascular risk prediction model. The Framingham cohort identified some of the most fundamental risk factors that shape modern cardiovascular prevention, however, it is not a perfect model. The imperfect nature of cardiovascular risk prediction based on FRS forms the starting point of this research journey. In the search for a better prediction tool, a logical approach would be to improve on an existing model, rather than ‘reinventing the wheel’. This philosophy underpins this piece of work, which focuses on finding a tool that improves identification of subclinical disease. From my clinical practice in radiology, the value of cardiovascular CT biomarkers became an obvious area to investigate. Over the course of my research, I realised both cardiovascular (CVD) risk prediction models and CVD CT biomarkers have evolved over a similar period. The scope of my research demanded my attention to focus on FRS as a base model, though there are many other CVD risk prediction models. Similarly, there are multiple cardiovascular CT biomarkers that have been proposed. The best studied CT biomarker in terms of predicting CVD events is undoubtedly coronary calcium score (CACS). Considering the evolving nature of CT technology and the deeper understanding of CVD pathophysiology, there are two other up-and-coming biomarkers, namely thoracic calcium score (TACS) and coronary artery stenosis, which broaden the scope of investigating potentially useful biomarkers. Embedding CT biomarkers within Framingham Risk Score formed the framework investigation. Derived from this was a journey of discovery that led me to learn the rapidly expanding knowledge of prognosis research. My initial investigation was conducting a systematic review and meta-analysis of the incremental value of discussed CT biomarkers. This was followed by investigating the reporting standard of the Framingham Model within the realm of incremental value added by CT biomarkers. Finally, performing a feasibility study to look at whether the coronary arteries can be assessed during routine oncological whole-body CT imaging. I would like to illustrate and share my learning in the subsequent chapters.

Keywords

cardiovascular risk prediction, cardiac computed tomography, incremental value

Document Type

Thesis

Publication Date

2020

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