About the Project
Cardiovascular magnetic resonance imaging (CMR) is the gold standard for delineating cardiac structure and function. From a standard set of long- and short-axis cine acquisitions global measures of left ventricular (LV) end-diastolic volume (EDV), end-systolic volume (ESV), stroke volume (SV) and ejection fraction (EF) are readily calculated.1 However, cardiac disease processes affect the heart non-uniformly. Examples include focal septal/apical hypertrophy with reduced strain in hypertrophic cardiomyopathy and replacement fibrosis, wall thinning and akinesia in an infarct-related coronary artery territory. Novel imaging biomarkers that quantify this cardiac variability can potentially aid the diagnosis of subclinical disease, more precisely risk stratify and further improve prediction of treatment response.2 The high resolution and detail of CMR makes it an ideal modality to assess cardiac heterogeneity.
Background:
Heterogeneity biomarkers on CMR: Limited heterogeneity biomarkers have been investigated and none are routinely measured in standard clinical CMR protocols. This is despite T1-, T2-weighted and contrast-enhanced sequences’ sensitivity to altered tissue composition and the ability of CMR strain imaging to quantify regional differences in directional strain.3-5 For example, in two case-control studies, Nakamori et al. and Baessler et al. derived the mean absolute deviation of the standard deviations (SD) of segmental T1 and T2 measurements from a 16-segment LV model (MadSD) as global markers of tissue heterogeneity. T1 and T2 MadSD values were significantly greater in non-ischaemic cardiomyopathy and acute myocarditis versus healthy controls respectively.6,7
The National Institutes of Health and World Health Organisation broadly define a biomarker as an objectively measurable and reproducible substance or process that differentiates normal from abnormal biological processes, predicts outcomes and monitors response to treatment.8-10 To fulfil these criteria, proof-of-concept CMR measures of heterogeneity must now be comprehensively tested and benchmarked in large population samples, thus harnessing the use of data for information that are currently hidden or not used to full potential.
UK Biobank: Prospective cohort studies that examine the association between patient genotype, phenotype, environmental exposures and disease pathogenesis and outcomes now include baseline CMR scans.11 The UK Biobank (UKBB) is one of the largest prospective cohort studies; it includes an original half a million people aged 40-69 years and recruited between 2006-10 across the UK with detailed baseline sociodemographic, anthropometric, biochemical and genotype characteristics. Comprehensive follow-up and outcome data continues to be collected.12 The UKBB sets itself apart through a target 10- to 100-fold more baseline CMR as part of a multi-modality imaging sub-study.13-15
One of the greatest values of CMR-enhanced epidemiology studies derives from the ability to investigate cardiovascular risk factors and subclinical cardiac disease at a population level. The hope is that early diagnosis with highly sensitive and specific imaging biomarkers (e.g. LV mass to volume ratio) and early preventative measures can pre-empt the development of overt disease.16,17
Limitations of advanced CMR sequences, including LGE, tissue tagging with harmonic phase imaging, T1- and T2-mapping in population studies are that of fewer available CMR datasets, patient contra-indications, longer processing time and lack of standardisation.11,12 In contrast, cine images with myocardial feature-tracking (CMR-FT) can derive novel heterogeneity biomarkers, including regional variability in wall thickness and strain as part of a standard CMR dataset in the UKBB.13-15 Thus, the UKBB is an excellent data source to test and validate CMR heterogeneity imaging biomarkers. These biomarkers will become even easier and quicker to analyse with the recent rapid integration of artificial intelligence technology and allow utilisation in clinical practice.
Original hypothesis
Our long-term goal is to develop clinically translatable heterogeneity imaging biomarkers on CMR. Our central hypothesis is that disease states increase cardiac shape, textural and functional heterogeneity and that these markers are measurable and reproducible to facilitate earlier diagnosis and improved prognostication.
Aim 1: To develop biomarkers that assess heterogeneity in LV morphology, tissue composition and deformation by establishing reference ranges, assessing the intra- and inter-observer variability and test-retest variability.
Aim 2: To determine if heterogeneity biomarkers can discriminate health from cardiovascular (CV) risk factors and prevalent myocardial disease. We hypothesise that the biomarkers will improve our understanding of cardiovascular risk factor profiles and disease phenotypes.
Aim 3: To determine the prognostic power of heterogeneity biomarkers for incident CV disease in diverse populations. We hypothesise that the biomarkers will provide independent predictive information beyond standard clinical risk prediction models, facilitating earlier detection of sub-clinical and clinical disease.
Notice on Equality, Diversity and Inclusion:
Barts and The London School of Medicine and Dentistry aims to promote an organisational culture that is respectful and inclusive irrespective of age, disability, gender reassignment, ethnicity, marriage or civil partnership, pregnancy and maternity, race, sex and religion or belief. Moreover, it seeks to ensure that intersectionality is recognised, with explicit acknowledgement of the interconnected nature of social identities including race, class and sex, where these facets can create overlapping levels of discrimination or disadvantage.
Privacy Statement – sharing personal data with HARP
When you apply to the Trust for PhD support, or at any time afterwards, where you also apply to the Health Advances in Underrepresented Populations and Diseases PhD programme (“HARP”), the Trust will share your personal information with the Directors of HARP and with the other organisations involved in that programme, namely Queen Mary University of London, City University of London, Barts Charity, Barts Health NHS Trust and East London Foundation Trust. This may involve sharing your completed application forms, including equality monitoring information, as well as your name and contact details, your CV, details of your skills, education and experience, your proposed areas of study, and other information supporting your application. Your personal data will be shared for the purposes of evaluating your application and, if your application is successful, to administer your participation in the HARP doctoral training programme.
References
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2. Baessler B. Noncontrast Quantitative Imaging Biomarkers Reflecting Myocardial Tissue Heterogeneity: The Future of Cardiac Magnetic Resonance Imaging? JACC Cardiovasc Imaging. 2020 Sep;13(9):1931-1933.
3. Messroghli DR, Moon JC, Ferreira VM, Grosse-Wortmann L, He T, Kellman P, Mascherbauer J, Nezafat R, Salerno M, Schelbert EB, Taylor AJ, Thompson R, Ugander M, van Heeswijk RB, Friedrich MG. Clinical recommendations for cardiovascular magnetic resonance mapping of T1, T2, T2* and extracellular volume: A consensus statement by the Society for Cardiovascular Magnetic Resonance (SCMR) endorsed by the European Association for Cardiovascular Imaging (EACVI). J Cardiovasc Magn Reson. 2017 Oct 9;19(1):75.
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