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Multi-modality cardiac imaging in the management of diabetic heart disease
Diabetic heart disease is a major healthcare problem. Patients with diabetes show an excess of death from cardiovascular causes, twice as high as the general population and those with diabetes type 1 and longer duration of the disease present with more severe cardiovascular complications. Premature...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9669908/ https://www.ncbi.nlm.nih.gov/pubmed/36407437 http://dx.doi.org/10.3389/fcvm.2022.1043711 |
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author | Wamil, Malgorzata Goncalves, Marcos Rutherford, Alexander Borlotti, Alessandra Pellikka, Patricia Ann |
author_facet | Wamil, Malgorzata Goncalves, Marcos Rutherford, Alexander Borlotti, Alessandra Pellikka, Patricia Ann |
author_sort | Wamil, Malgorzata |
collection | PubMed |
description | Diabetic heart disease is a major healthcare problem. Patients with diabetes show an excess of death from cardiovascular causes, twice as high as the general population and those with diabetes type 1 and longer duration of the disease present with more severe cardiovascular complications. Premature coronary artery disease and heart failure are leading causes of morbidity and reduced life expectancy. Multimodality cardiac imaging, including echocardiography, cardiac computed tomography, nuclear medicine, and cardiac magnetic resonance play crucial role in the diagnosis and management of different pathologies included in the definition of diabetic heart disease. In this review we summarise the utility of multi-modality cardiac imaging in characterising ischaemic and non-ischaemic causes of diabetic heart disease and give an overview of the current clinical practice. We also describe emerging imaging techniques enabling early detection of coronary artery inflammation and the non-invasive characterisation of the atherosclerotic plaque disease. Furthermore, we discuss the role of MRI-derived techniques in studying altered myocardial metabolism linking diabetes with the development of diabetic cardiomyopathy. Finally, we discuss recent data regarding the use of artificial intelligence applied to large imaging databases and how those efforts can be utilised in the future in screening of patients with diabetes for early signs of disease. |
format | Online Article Text |
id | pubmed-9669908 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-96699082022-11-18 Multi-modality cardiac imaging in the management of diabetic heart disease Wamil, Malgorzata Goncalves, Marcos Rutherford, Alexander Borlotti, Alessandra Pellikka, Patricia Ann Front Cardiovasc Med Cardiovascular Medicine Diabetic heart disease is a major healthcare problem. Patients with diabetes show an excess of death from cardiovascular causes, twice as high as the general population and those with diabetes type 1 and longer duration of the disease present with more severe cardiovascular complications. Premature coronary artery disease and heart failure are leading causes of morbidity and reduced life expectancy. Multimodality cardiac imaging, including echocardiography, cardiac computed tomography, nuclear medicine, and cardiac magnetic resonance play crucial role in the diagnosis and management of different pathologies included in the definition of diabetic heart disease. In this review we summarise the utility of multi-modality cardiac imaging in characterising ischaemic and non-ischaemic causes of diabetic heart disease and give an overview of the current clinical practice. We also describe emerging imaging techniques enabling early detection of coronary artery inflammation and the non-invasive characterisation of the atherosclerotic plaque disease. Furthermore, we discuss the role of MRI-derived techniques in studying altered myocardial metabolism linking diabetes with the development of diabetic cardiomyopathy. Finally, we discuss recent data regarding the use of artificial intelligence applied to large imaging databases and how those efforts can be utilised in the future in screening of patients with diabetes for early signs of disease. Frontiers Media S.A. 2022-11-03 /pmc/articles/PMC9669908/ /pubmed/36407437 http://dx.doi.org/10.3389/fcvm.2022.1043711 Text en Copyright © 2022 Wamil, Goncalves, Rutherford, Borlotti and Pellikka. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). 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. |
spellingShingle | Cardiovascular Medicine Wamil, Malgorzata Goncalves, Marcos Rutherford, Alexander Borlotti, Alessandra Pellikka, Patricia Ann Multi-modality cardiac imaging in the management of diabetic heart disease |
title | Multi-modality cardiac imaging in the management of diabetic heart disease |
title_full | Multi-modality cardiac imaging in the management of diabetic heart disease |
title_fullStr | Multi-modality cardiac imaging in the management of diabetic heart disease |
title_full_unstemmed | Multi-modality cardiac imaging in the management of diabetic heart disease |
title_short | Multi-modality cardiac imaging in the management of diabetic heart disease |
title_sort | multi-modality cardiac imaging in the management of diabetic heart disease |
topic | Cardiovascular Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9669908/ https://www.ncbi.nlm.nih.gov/pubmed/36407437 http://dx.doi.org/10.3389/fcvm.2022.1043711 |
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