Analysis of cardiac amyloidosis progression using model-based markers

Li, W. et al. (2020) Analysis of cardiac amyloidosis progression using model-based markers. Frontiers in Physiology, 11, 324. (doi: 10.3389/fphys.2020.00324) (PMID:32425806) (PMCID:PMC7203577)

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Deposition of amyloid in the heart can lead to cardiac dilation and impair its pumping ability. This ultimately leads to heart failure with worsening symptoms of breathlessness and fatigue due to the progressive loss of elasticity of the myocardium. Biomarkers linked to clinical deterioration can be crucial in developing effective treatments. However, to date progression of cardiac amyloidosis is poorly characterized, and there is an urgent need to identify key features that can predict the disease progression and cardiac tissue function. In this proof of concept study, we estimate a group of new markers based on mathematical models of the left ventricle derived from routine clinical magnetic resonance imaging and follow-up scans from the National Amyloidosis Centre at the Royal Free in London. Using mechanical modelling and statistical classification, we show that it is possible to predict disease progression. Our predictions agree with clinical assessments in a double-blind test in six out of the seven sample cases studied. Importantly, we find that multiple factors need to be used in the classification, which includes mechanical, geometrical and shape features. No single marker can yield reliable prediction given the complexity of the growth and remodelling process of diseased hearts undergoing high-dimensional shape changes. Our approach is promising in terms of clinical translation but the results presented should be interpreted with caution due to the small sample size.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Luo, Professor Xiaoyu and Li, Dr Wenguang and Husmeier, Professor Dirk and Gao, Dr Hao and Berry, Professor Colin and Lazarus, Dr Alan
Authors: Li, W., Lazarus, A., Gao, H., Martinez De Azcona Naharro, A., Fontana, M., Hawkins, P., Biswas, S., Janiczek, R., Cox, J., Berry, C., Husmeier, D., and Luo, X.
College/School:College of Medical Veterinary and Life Sciences > School of Cardiovascular & Metabolic Health
College of Science and Engineering > School of Engineering > Systems Power and Energy
College of Science and Engineering > School of Mathematics and Statistics > Mathematics
College of Science and Engineering > School of Mathematics and Statistics > Statistics
Journal Name:Frontiers in Physiology
Publisher:Frontiers Media
ISSN (Online):1664-042X
Copyright Holders:Copyright © 2020 Li, Lazarus, Gao, Martinez-Naharro, Fontana, Hawkins, Biswas, Janiczek, Cox, Berry, Husmeier and Luo
First Published:First published in Frontiers in Physiology 11:324
Publisher Policy:Reproduced under a Creative Commons licence

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
172141EPSRC Centre for Multiscale soft tissue mechanics with application to heart & cancerRaymond OgdenEngineering and Physical Sciences Research Council (EPSRC)EP/N014642/1M&S - Mathematics
303231A whole-heart model of multiscale soft tissue mechanics and fluid structureinteraction for clinical applications (Whole-Heart-FSI)Xiaoyu LuoEngineering and Physical Sciences Research Council (EPSRC)EP/S020950/1M&S - Mathematics
190831First steps towards modelling myocardial infarction (a computed MI Physiome): A case-control study of novel biomechanical parameters in acute MI survivors with left ventricular dysfunction.Colin BerryBritish Heart Foundation (BHF)PG/14/64/31043Institute of Cardiovascular & Medical Sciences
190350Validation and significance of myocardial haemorrhage revealed by "bright blood" T2-weighted MRI in heart attack survivors: a prospective cohort study.Colin BerryBritish Heart Foundation (BHF)PG/11/2/28474Institute of Cardiovascular & Medical Sciences
305655Inference of cardio-mechanical parameters in real time: moving mathematical modelling into the clinicDirk HusmeierThe Royal Society of Edinburgh (ROYSOCED)62335M&S - Statistics