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Combined T1-mapping and tissue tracking analysis predicts severity of ischemic injury following acute STEMI—an Oxford Acute Myocardial Infarction (OxAMI) study
Early risk stratification after ST-segment–elevation myocardial infarction (STEMI) is of major clinical importance. Strain quantifies myocardial deformation and can demonstrate abnormal global and segmental myocardial function in acute ischaemia. Native T1-mapping allows assessment of the severity o...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6598944/ https://www.ncbi.nlm.nih.gov/pubmed/30778713 http://dx.doi.org/10.1007/s10554-019-01542-8 |
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author | Wamil, Malgorzata Borlotti, Alessandra Liu, Dan Briosa e Gala, André Bracco, Alessia Alkhalil, Mohammad De Maria, Giovanni Luigi Piechnik, Stefan K. Ferreira, Vanessa M. Banning, Adrian P. Kharbanda, Rajesh K. Neubauer, Stefan Choudhury, Robin P. Channon, Keith M. Dall’Armellina, Erica |
author_facet | Wamil, Malgorzata Borlotti, Alessandra Liu, Dan Briosa e Gala, André Bracco, Alessia Alkhalil, Mohammad De Maria, Giovanni Luigi Piechnik, Stefan K. Ferreira, Vanessa M. Banning, Adrian P. Kharbanda, Rajesh K. Neubauer, Stefan Choudhury, Robin P. Channon, Keith M. Dall’Armellina, Erica |
author_sort | Wamil, Malgorzata |
collection | PubMed |
description | Early risk stratification after ST-segment–elevation myocardial infarction (STEMI) is of major clinical importance. Strain quantifies myocardial deformation and can demonstrate abnormal global and segmental myocardial function in acute ischaemia. Native T1-mapping allows assessment of the severity of acute ischemic injury, however its clinical applicability early post MI is limited by the complex dynamic changes happening in the myocardium post MI. We aimed to explore relationship between T1-mapping and feature tracking imaging, to establish whether combined analysis of these parameters could predict recovery after STEMI. 96 STEMI patients (aged 60 ± 11) prospectively recruited in the Oxford Acute Myocardial Infarction (OxAMI) study underwent 3T-CMR scans acutely (within 53 ± 32 h from primary percutaneous coronary intervention) and at 6 months (6M). The imaging protocol included: cine, ShMOLLI T1-mapping and late gadolinium enhancement (LGE). Segments were divided in the infarct, adjacent and remote zones based on the presence of LGE. Peak circumferential (Ecc) and radial (Err) strain was assessed using cvi42 software. Acute segmental strain correlated with segmental T1-mapping values (T1 vs. Err − 0.75 ± 0.25, p < 0.01; T1 vs. Ecc 0.72 ± 0.32, p < 0.01) and with LGE segmental injury (LGE vs. Err − 0.56 ± 0.29, p < 0.01; LGE vs. Ecc 0.54 ± 0.35, p < 0.01). Moreover, acute segmental T1 and strain predicted segmental LGE transmurality on 6M scans (p < 0.001, r = 0.5). Multiple regression analysis confirmed combined analysis of global Ecc and T1-mapping was significantly better than either method alone in predicting final infarct size at 6M (r = 0.556 vs r = 0.473 for global T1 only and r = 0.476 for global Ecc only, p < 0.001). This novel CMR method combining T1-mapping and feature tracking analysis of acute CMR scans predicts LGE transmurality and infarct size at 6M following STEMI. |
format | Online Article Text |
id | pubmed-6598944 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-65989442019-07-18 Combined T1-mapping and tissue tracking analysis predicts severity of ischemic injury following acute STEMI—an Oxford Acute Myocardial Infarction (OxAMI) study Wamil, Malgorzata Borlotti, Alessandra Liu, Dan Briosa e Gala, André Bracco, Alessia Alkhalil, Mohammad De Maria, Giovanni Luigi Piechnik, Stefan K. Ferreira, Vanessa M. Banning, Adrian P. Kharbanda, Rajesh K. Neubauer, Stefan Choudhury, Robin P. Channon, Keith M. Dall’Armellina, Erica Int J Cardiovasc Imaging Original Paper Early risk stratification after ST-segment–elevation myocardial infarction (STEMI) is of major clinical importance. Strain quantifies myocardial deformation and can demonstrate abnormal global and segmental myocardial function in acute ischaemia. Native T1-mapping allows assessment of the severity of acute ischemic injury, however its clinical applicability early post MI is limited by the complex dynamic changes happening in the myocardium post MI. We aimed to explore relationship between T1-mapping and feature tracking imaging, to establish whether combined analysis of these parameters could predict recovery after STEMI. 96 STEMI patients (aged 60 ± 11) prospectively recruited in the Oxford Acute Myocardial Infarction (OxAMI) study underwent 3T-CMR scans acutely (within 53 ± 32 h from primary percutaneous coronary intervention) and at 6 months (6M). The imaging protocol included: cine, ShMOLLI T1-mapping and late gadolinium enhancement (LGE). Segments were divided in the infarct, adjacent and remote zones based on the presence of LGE. Peak circumferential (Ecc) and radial (Err) strain was assessed using cvi42 software. Acute segmental strain correlated with segmental T1-mapping values (T1 vs. Err − 0.75 ± 0.25, p < 0.01; T1 vs. Ecc 0.72 ± 0.32, p < 0.01) and with LGE segmental injury (LGE vs. Err − 0.56 ± 0.29, p < 0.01; LGE vs. Ecc 0.54 ± 0.35, p < 0.01). Moreover, acute segmental T1 and strain predicted segmental LGE transmurality on 6M scans (p < 0.001, r = 0.5). Multiple regression analysis confirmed combined analysis of global Ecc and T1-mapping was significantly better than either method alone in predicting final infarct size at 6M (r = 0.556 vs r = 0.473 for global T1 only and r = 0.476 for global Ecc only, p < 0.001). This novel CMR method combining T1-mapping and feature tracking analysis of acute CMR scans predicts LGE transmurality and infarct size at 6M following STEMI. Springer Netherlands 2019-02-16 2019 /pmc/articles/PMC6598944/ /pubmed/30778713 http://dx.doi.org/10.1007/s10554-019-01542-8 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Original Paper Wamil, Malgorzata Borlotti, Alessandra Liu, Dan Briosa e Gala, André Bracco, Alessia Alkhalil, Mohammad De Maria, Giovanni Luigi Piechnik, Stefan K. Ferreira, Vanessa M. Banning, Adrian P. Kharbanda, Rajesh K. Neubauer, Stefan Choudhury, Robin P. Channon, Keith M. Dall’Armellina, Erica Combined T1-mapping and tissue tracking analysis predicts severity of ischemic injury following acute STEMI—an Oxford Acute Myocardial Infarction (OxAMI) study |
title | Combined T1-mapping and tissue tracking analysis predicts severity of ischemic injury following acute STEMI—an Oxford Acute Myocardial Infarction (OxAMI) study |
title_full | Combined T1-mapping and tissue tracking analysis predicts severity of ischemic injury following acute STEMI—an Oxford Acute Myocardial Infarction (OxAMI) study |
title_fullStr | Combined T1-mapping and tissue tracking analysis predicts severity of ischemic injury following acute STEMI—an Oxford Acute Myocardial Infarction (OxAMI) study |
title_full_unstemmed | Combined T1-mapping and tissue tracking analysis predicts severity of ischemic injury following acute STEMI—an Oxford Acute Myocardial Infarction (OxAMI) study |
title_short | Combined T1-mapping and tissue tracking analysis predicts severity of ischemic injury following acute STEMI—an Oxford Acute Myocardial Infarction (OxAMI) study |
title_sort | combined t1-mapping and tissue tracking analysis predicts severity of ischemic injury following acute stemi—an oxford acute myocardial infarction (oxami) study |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6598944/ https://www.ncbi.nlm.nih.gov/pubmed/30778713 http://dx.doi.org/10.1007/s10554-019-01542-8 |
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