Li, W;
Lazarus, A;
Gao, H;
Martinez-Naharro, A;
Fontana, M;
Hawkins, P;
Biswas, S;
... Luo, X; + view all
(2020)
Analysis of Cardiac Amyloidosis Progression Using Model-Based Markers.
Frontiers in Physiology
, 11
, Article 324. 10.3389/fphys.2020.00324.
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Abstract
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 the clinical deterioration can be crucial in developing effective treatments. However, to date the progression of cardiac amyloidosis is poorly characterized. There is an urgent need to identify key predictors for 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 Center at the Royal Free in London. Using mechanical modeling 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 remodeling 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.
| Type: | Article |
|---|---|
| Title: | Analysis of Cardiac Amyloidosis Progression Using Model-Based Markers |
| Location: | Switzerland |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.3389/fphys.2020.00324 |
| Publisher version: | https://doi.org/10.3389/fphys.2020.00324 |
| Language: | English |
| Additional information: | Copyright © 2020 Li, Lazarus, Gao, Martinez-Naharro, Fontana, Hawkins, Biswas, Janiczek, Cox, Berry, Husmeier and Luo. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (http://creativecommons.org/licenses/by/4.0/). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
| Keywords: | MRI, cardiac amyloidosis, classification, left ventricle, model-based markers, shape analysis, strain and stress |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine > Inflammation |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10099040 |
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