Cardiac magnetic resonance radiomics: basic principles and clinical perspectives

Radiomics is a novel image analysis technique, whereby voxel-level information is extracted from digital images and used to derive multiple numerical quantifiers of shape and tissue character. Cardiac magnetic resonance (CMR) is the reference imaging modality for assessment of cardiac structure and...

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Authors: Raisi-Estabragh, Zahra, Izquierdo, Cristián, Campello Román, Víctor Manuel, Martin Isla, Carlos, Jaggi, Akshay, Harvey, Nicholas C., Lekadir, Karim, 1977-, Petersen, Steffen E.
Format: article
Status:Versión aceptada para publicación
Publication Date:2020
Country:España
Institution:Universidad de Barcelona
Repository:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/174752
Online Access:https://hdl.handle.net/2445/174752
Access Level:Open access
Keyword:Ressonància magnètica
Diagnòstic per la imatge
Aprenentatge automàtic
Magnetic resonance
Diagnostic imaging
Machine learning
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spelling Cardiac magnetic resonance radiomics: basic principles and clinical perspectivesRaisi-Estabragh, ZahraIzquierdo, CristiánCampello Román, Víctor ManuelMartin Isla, CarlosJaggi, AkshayHarvey, Nicholas C.Lekadir, Karim, 1977-Petersen, Steffen E.Ressonància magnèticaDiagnòstic per la imatgeAprenentatge automàticMagnetic resonanceDiagnostic imagingMachine learningRadiomics is a novel image analysis technique, whereby voxel-level information is extracted from digital images and used to derive multiple numerical quantifiers of shape and tissue character. Cardiac magnetic resonance (CMR) is the reference imaging modality for assessment of cardiac structure and function. Conventional analysis of CMR scans is mostly reliant on qualitative image analysis and basic geometric quantifiers. Small proof-of-concept studies have demonstrated the feasibility and superior diagnostic accuracy of CMR radiomics analysis over conventional reporting. CMR radiomics has the potential to transform our approach to defining image phenotypes and, through this, improve diagnostic accuracy, treatment selection, and prognostication. The purpose of this article is to provide an overview of radiomics concepts for clinicians, with particular consideration of application to CMR. We will also review existing literature on CMR radiomics, discuss challenges, and consider directions for future work.Oxford University Press2020info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersioninfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://hdl.handle.net/2445/174752Articles publicats en revistes (Matemàtiques i Informàtica)reponame:Dipòsit Digital de la UBinstname:Universidad de BarcelonaInglésReproducció del document publicat a: https://doi.org/10.1093/ehjci/jeaa028European Heart Journal-Cardiovascular Imaging, 2020, vol. 21, num. 4, p. 349-356https://doi.org/10.1093/ehjci/jeaa028info:eu-repo/grantAgreement/EC/H2020/825903(c) cc-by Raisi Estabragh, Zahra et al., 2020http://creativecommons.org/licenses/by/3.0/es/info:eu-repo/semantics/openAccessoai:diposit.ub.edu:2445/1747522026-05-27T06:46:51Z
dc.title.none.fl_str_mv Cardiac magnetic resonance radiomics: basic principles and clinical perspectives
title Cardiac magnetic resonance radiomics: basic principles and clinical perspectives
spellingShingle Cardiac magnetic resonance radiomics: basic principles and clinical perspectives
Raisi-Estabragh, Zahra
Ressonància magnètica
Diagnòstic per la imatge
Aprenentatge automàtic
Magnetic resonance
Diagnostic imaging
Machine learning
title_short Cardiac magnetic resonance radiomics: basic principles and clinical perspectives
title_full Cardiac magnetic resonance radiomics: basic principles and clinical perspectives
title_fullStr Cardiac magnetic resonance radiomics: basic principles and clinical perspectives
title_full_unstemmed Cardiac magnetic resonance radiomics: basic principles and clinical perspectives
title_sort Cardiac magnetic resonance radiomics: basic principles and clinical perspectives
dc.creator.none.fl_str_mv Raisi-Estabragh, Zahra
Izquierdo, Cristián
Campello Román, Víctor Manuel
Martin Isla, Carlos
Jaggi, Akshay
Harvey, Nicholas C.
Lekadir, Karim, 1977-
Petersen, Steffen E.
author Raisi-Estabragh, Zahra
author_facet Raisi-Estabragh, Zahra
Izquierdo, Cristián
Campello Román, Víctor Manuel
Martin Isla, Carlos
Jaggi, Akshay
Harvey, Nicholas C.
Lekadir, Karim, 1977-
Petersen, Steffen E.
author_role author
author2 Izquierdo, Cristián
Campello Román, Víctor Manuel
Martin Isla, Carlos
Jaggi, Akshay
Harvey, Nicholas C.
Lekadir, Karim, 1977-
Petersen, Steffen E.
author2_role author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Ressonància magnètica
Diagnòstic per la imatge
Aprenentatge automàtic
Magnetic resonance
Diagnostic imaging
Machine learning
topic Ressonància magnètica
Diagnòstic per la imatge
Aprenentatge automàtic
Magnetic resonance
Diagnostic imaging
Machine learning
description Radiomics is a novel image analysis technique, whereby voxel-level information is extracted from digital images and used to derive multiple numerical quantifiers of shape and tissue character. Cardiac magnetic resonance (CMR) is the reference imaging modality for assessment of cardiac structure and function. Conventional analysis of CMR scans is mostly reliant on qualitative image analysis and basic geometric quantifiers. Small proof-of-concept studies have demonstrated the feasibility and superior diagnostic accuracy of CMR radiomics analysis over conventional reporting. CMR radiomics has the potential to transform our approach to defining image phenotypes and, through this, improve diagnostic accuracy, treatment selection, and prognostication. The purpose of this article is to provide an overview of radiomics concepts for clinicians, with particular consideration of application to CMR. We will also review existing literature on CMR radiomics, discuss challenges, and consider directions for future work.
publishDate 2020
dc.date.none.fl_str_mv 2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
info:eu-repo/semantics/publishedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/174752
url https://hdl.handle.net/2445/174752
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Reproducció del document publicat a: https://doi.org/10.1093/ehjci/jeaa028
European Heart Journal-Cardiovascular Imaging, 2020, vol. 21, num. 4, p. 349-356
https://doi.org/10.1093/ehjci/jeaa028
info:eu-repo/grantAgreement/EC/H2020/825903
dc.rights.none.fl_str_mv (c) cc-by Raisi Estabragh, Zahra et al., 2020
http://creativecommons.org/licenses/by/3.0/es/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv (c) cc-by Raisi Estabragh, Zahra et al., 2020
http://creativecommons.org/licenses/by/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Oxford University Press
publisher.none.fl_str_mv Oxford University Press
dc.source.none.fl_str_mv Articles publicats en revistes (Matemàtiques i Informàtica)
reponame:Dipòsit Digital de la UB
instname:Universidad de Barcelona
instname_str Universidad de Barcelona
reponame_str Dipòsit Digital de la UB
collection Dipòsit Digital de la UB
repository.name.fl_str_mv
repository.mail.fl_str_mv
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