Mangion, K., Gao, H. , Husmeier, D. , Luo, X. and Berry, C. (2018) Advances in computational modelling for personalised medicine after myocardial infarction. Heart, 104(7), pp. 550-557. (doi: 10.1136/heartjnl-2017-311449) (PMID:29127185)
|
Text
150638.pdf - Accepted Version 647kB |
Abstract
Myocardial infarction (MI) is a leading cause of premature morbidity and mortality worldwide. Determining which patients will experience heart failure and sudden cardiac death after an acute MI is notoriously difficult for clinicians. The extent of heart damage after an acute MI is informed by cardiac imaging, typically using echocardiography or sometimes, cardiac magnetic resonance (CMR). These scans provide complex data sets that are only partially exploited by clinicians in daily practice, implying potential for improved risk assessment. Computational modelling of left ventricular (LV) function can bridge the gap towards personalised medicine using cardiac imaging in patients with post-MI. Several novel biomechanical parameters have theoretical prognostic value and may be useful to reflect the biomechanical effects of novel preventive therapy for adverse remodelling post-MI. These parameters include myocardial contractility (regional and global), stiffness and stress. Further, the parameters can be delineated spatially to correspond with infarct pathology and the remote zone. While these parameters hold promise, there are challenges for translating MI modelling into clinical practice, including model uncertainty, validation and verification, as well as time-efficient processing. More research is needed to (1) simplify imaging with CMR in patients with post-MI, while preserving diagnostic accuracy and patient tolerance (2) to assess and validate novel biomechanical parameters against established prognostic biomarkers, such as LV ejection fraction and infarct size. Accessible software packages with minimal user interaction are also needed. Translating benefits to patients will be achieved through a multidisciplinary approach including clinicians, mathematicians, statisticians and industry partners.
| Item Type: | Articles |
|---|---|
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Berry, Professor Colin and Luo, Professor Xiaoyu and Mangion, Dr Kenneth and Gao, Dr Hao and Husmeier, Professor Dirk |
| Authors: | Mangion, K., Gao, H., Husmeier, D., Luo, X., and Berry, C. |
| College/School: | College of Medical Veterinary and Life Sciences > School of Cardiovascular & Metabolic Health College of Science and Engineering > School of Mathematics and Statistics > Mathematics College of Science and Engineering > School of Mathematics and Statistics > Statistics |
| Journal Name: | Heart |
| Publisher: | BMJ Publishing Group |
| ISSN: | 1355-6037 |
| ISSN (Online): | 1468-201X |
| Published Online: | 10 November 2017 |
| Copyright Holders: | Copyright © 2017 The Authors |
| First Published: | First published in Heart 104(7):550-557 |
| Publisher Policy: | Reproduced in accordance with the publisher copyright policy |
University Staff: Request a correction | Enlighten Editors: Update this record
Funder and Project Information
Funder and Project Information