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Artificial Intelligence Applications in Cardiovascular Magnetic Resonance Imaging: Are We on the Path to Avoiding the Administration of Contrast Media?

In recent years, cardiovascular imaging examinations have experienced exponential growth due to technological innovation, and this trend is consistent with the most recent chest pain guidelines. Contrast media have a crucial role in cardiovascular magnetic resonance (CMR) imaging, allowing for more...

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Detalles Bibliográficos
Autores principales: Cau, Riccardo, Pisu, Francesco, Suri, Jasjit S., Mannelli, Lorenzo, Scaglione, Mariano, Masala, Salvatore, Saba, Luca
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10297403/
https://www.ncbi.nlm.nih.gov/pubmed/37370956
http://dx.doi.org/10.3390/diagnostics13122061
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author Cau, Riccardo
Pisu, Francesco
Suri, Jasjit S.
Mannelli, Lorenzo
Scaglione, Mariano
Masala, Salvatore
Saba, Luca
author_facet Cau, Riccardo
Pisu, Francesco
Suri, Jasjit S.
Mannelli, Lorenzo
Scaglione, Mariano
Masala, Salvatore
Saba, Luca
author_sort Cau, Riccardo
collection PubMed
description In recent years, cardiovascular imaging examinations have experienced exponential growth due to technological innovation, and this trend is consistent with the most recent chest pain guidelines. Contrast media have a crucial role in cardiovascular magnetic resonance (CMR) imaging, allowing for more precise characterization of different cardiovascular diseases. However, contrast media have contraindications and side effects that limit their clinical application in determinant patients. The application of artificial intelligence (AI)-based techniques to CMR imaging has led to the development of non-contrast models. These AI models utilize non-contrast imaging data, either independently or in combination with clinical and demographic data, as input to generate diagnostic or prognostic algorithms. In this review, we provide an overview of the main concepts pertaining to AI, review the existing literature on non-contrast AI models in CMR, and finally, discuss the strengths and limitations of these AI models and their possible future development.
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spelling pubmed-102974032023-06-28 Artificial Intelligence Applications in Cardiovascular Magnetic Resonance Imaging: Are We on the Path to Avoiding the Administration of Contrast Media? Cau, Riccardo Pisu, Francesco Suri, Jasjit S. Mannelli, Lorenzo Scaglione, Mariano Masala, Salvatore Saba, Luca Diagnostics (Basel) Review In recent years, cardiovascular imaging examinations have experienced exponential growth due to technological innovation, and this trend is consistent with the most recent chest pain guidelines. Contrast media have a crucial role in cardiovascular magnetic resonance (CMR) imaging, allowing for more precise characterization of different cardiovascular diseases. However, contrast media have contraindications and side effects that limit their clinical application in determinant patients. The application of artificial intelligence (AI)-based techniques to CMR imaging has led to the development of non-contrast models. These AI models utilize non-contrast imaging data, either independently or in combination with clinical and demographic data, as input to generate diagnostic or prognostic algorithms. In this review, we provide an overview of the main concepts pertaining to AI, review the existing literature on non-contrast AI models in CMR, and finally, discuss the strengths and limitations of these AI models and their possible future development. MDPI 2023-06-14 /pmc/articles/PMC10297403/ /pubmed/37370956 http://dx.doi.org/10.3390/diagnostics13122061 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Cau, Riccardo
Pisu, Francesco
Suri, Jasjit S.
Mannelli, Lorenzo
Scaglione, Mariano
Masala, Salvatore
Saba, Luca
Artificial Intelligence Applications in Cardiovascular Magnetic Resonance Imaging: Are We on the Path to Avoiding the Administration of Contrast Media?
title Artificial Intelligence Applications in Cardiovascular Magnetic Resonance Imaging: Are We on the Path to Avoiding the Administration of Contrast Media?
title_full Artificial Intelligence Applications in Cardiovascular Magnetic Resonance Imaging: Are We on the Path to Avoiding the Administration of Contrast Media?
title_fullStr Artificial Intelligence Applications in Cardiovascular Magnetic Resonance Imaging: Are We on the Path to Avoiding the Administration of Contrast Media?
title_full_unstemmed Artificial Intelligence Applications in Cardiovascular Magnetic Resonance Imaging: Are We on the Path to Avoiding the Administration of Contrast Media?
title_short Artificial Intelligence Applications in Cardiovascular Magnetic Resonance Imaging: Are We on the Path to Avoiding the Administration of Contrast Media?
title_sort artificial intelligence applications in cardiovascular magnetic resonance imaging: are we on the path to avoiding the administration of contrast media?
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10297403/
https://www.ncbi.nlm.nih.gov/pubmed/37370956
http://dx.doi.org/10.3390/diagnostics13122061
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