Repeatability of cardiac magnetic resonance radiomics: a multi-centre multi-vendor test-retest study

dc.contributor.authorRaisi-Estabragh, Zahra
dc.contributor.authorGkontra, Polyxeni
dc.contributor.authorJaggi, Akshay
dc.contributor.authorCooper, Jackie
dc.contributor.authorAugusto, João
dc.contributor.authorBhuva, Anish N.
dc.contributor.authorDavies, Rhodri H.
dc.contributor.authorManisty, Charlotte H.
dc.contributor.authorMoon, James C.
dc.contributor.authorMunroe, Patricia B.
dc.contributor.authorHarvey, Nicholas C.
dc.contributor.authorLekadir, Karim, 1977-
dc.contributor.authorPetersen, Steffen E.
dc.date.accessioned2023-02-22T10:22:12Z
dc.date.available2023-02-22T10:22:12Z
dc.date.issued2020-12-02
dc.date.updated2023-02-22T10:22:12Z
dc.description.abstractAims: To evaluate the repeatability of cardiac magnetic resonance (CMR) radiomics features on test-retest scanning using a multi-centre multi-vendor dataset with a varied case-mix. Methods and Results: The sample included 54 test-retest studies from the VOLUMES resource (thevolumesresource.com). Images were segmented according to a pre-defined protocol to select three regions of interest (ROI) in end-diastole and end-systole: right ventricle, left ventricle (LV), and LV myocardium. We extracted radiomics shape features from all three ROIs and, additionally, first-order and texture features from the LV myocardium. Overall, 280 features were derived per study. For each feature, we calculated intra-class correlation coefficient (ICC), within-subject coefficient of variation, and mean relative difference. We ranked robustness of features according to mean ICC stratified by feature category, ROI, and cardiac phase, demonstrating a wide range of repeatability. There were features with good and excellent repeatability (ICC ≥ 0.75) within all feature categories and ROIs. A high proportion of first-order and texture features had excellent repeatability (ICC ≥ 0.90), however, these categories also contained features with the poorest repeatability (ICC < 0.50). Conclusion: CMR radiomic features have a wide range of repeatability. This paper is intended as a reference for future researchers to guide selection of the most robust features for clinical CMR radiomics models. Further work in larger and richer datasets is needed to further define the technical performance and clinical utility of CMR radiomics.
dc.format.mimetypeapplication/pdf
dc.identifier.idgrec721475
dc.identifier.issn2297-055X
dc.identifier.urihttps://hdl.handle.net/2445/193924
dc.language.isoeng
dc.publisherFrontiers Media
dc.relation.isformatofReproducció del document publicat a: https://doi.org/10.3389/fcvm.2020.586236
dc.relation.ispartofFrontiers in Cardiovascular Medicine, 2020, vol. 7
dc.relation.urihttps://doi.org/10.3389/fcvm.2020.586236
dc.rightscc-by (c) Raisi-Estabragh, Zahra et al., 2020
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourceArticles publicats en revistes (Matemàtiques i Informàtica)
dc.subject.classificationImatges per ressonància magnètica
dc.subject.classificationDades massives
dc.subject.classificationAlgorismes computacionals
dc.subject.otherMagnetic resonance imaging
dc.subject.otherBig data
dc.subject.otherComputer algorithms
dc.titleRepeatability of cardiac magnetic resonance radiomics: a multi-centre multi-vendor test-retest study
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion

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