Cardiac magnetic resonance radiomics reveal differential impact of sex, age, and vascular risk factors on cardiac structure and myocardial tissue

dc.contributor.authorRaisi-Estabragh, Zahra
dc.contributor.authorJaggi, Akshay
dc.contributor.authorGkontra, Polyxeni
dc.contributor.authorMcCracken, Celeste
dc.contributor.authorAung, Nay
dc.contributor.authorMunroe, Patricia B.
dc.contributor.authorNeubauer, Stefan
dc.contributor.authorHarvey, Nicholas C.
dc.contributor.authorLekadir, Karim, 1977-
dc.contributor.authorPetersen, Steffen E.
dc.date.accessioned2026-02-27T11:11:46Z
dc.date.available2026-02-27T11:11:46Z
dc.date.issued2021-12-22
dc.date.updated2026-02-27T11:11:47Z
dc.description.abstractBackground: Cardiovascular magnetic resonance (CMR) radiomics analysis provides multiple quantifiers of ventricular shape and myocardial texture, which may be used for detailed cardiovascular phenotyping. Objectives: We studied variation in CMR radiomics phenotypes by age and sex in healthy UK Biobank participants. Then, we examined independent associations of classical vascular risk factors (VRFs: smoking, diabetes, hypertension, high cholesterol) with CMR radiomics features, considering potential sex and age differential relationships. Design: Image acquisition was with 1.5 Tesla scanners (MAGNETOM Aera, Siemens). Three regions of interest were segmented from short axis stack images using an automated pipeline: right ventricle, left ventricle, myocardium. We extracted 237 radiomics features from each study using Pyradiomics. In a healthy subset of participants (n = 14,902) without cardiovascular disease or VRFs, we estimated independent associations of age and sex with each radiomics feature using linear regression models adjusted for body size. We then created a sample comprising individuals with at least one VRF matched to an equal number of healthy participants (n = 27,400). We linearly modelled each radiomics feature against age, sex, body size, and all the VRFs. Bonferroni adjustment for multiple testing was applied to all p-values. To aid interpretation, we organised the results into six feature clusters. Results: Amongst the healthy subset, men had larger ventricles with dimmer and less texturally complex myocardium than women. Increasing age was associated with smaller ventricles and greater variation in myocardial intensities. Broadly, all the VRFs were associated with dimmer, less varied signal intensities, greater uniformity of local intensity levels, and greater relative presence of low signal intensity areas within the myocardium. Diabetes and high cholesterol were also associated with smaller ventricular size, this association was of greater magnitude in men than women. The pattern of alteration of radiomics features with the VRFs was broadly consistent in men and women. However, the associations between intensity based radiomics features with both diabetes and hypertension were more prominent in women than men. Conclusions: We demonstrate novel independent associations of sex, age, and major VRFs with CMR radiomics phenotypes. Further studies into the nature and clinical significance of these phenotypes are needed.
dc.format.extent15 p.
dc.format.mimetypeapplication/pdf
dc.identifier.idgrec721471
dc.identifier.issn2297-055X
dc.identifier.urihttps://hdl.handle.net/2445/227634
dc.language.isoeng
dc.publisherFrontiers Media
dc.relation.isformatofReproducció del document publicat a: https://doi.org/10.3389/fcvm.2021.763361
dc.relation.ispartofFrontiers in Cardiovascular Medicine, 2021, vol. 8, p. 1972
dc.relation.urihttps://doi.org/10.3389/fcvm.2021.763361
dc.rightscc-by (c) Raisi-Estabragh, Z. et al., 2021
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceArticles publicats en revistes (Matemàtiques i Informàtica)
dc.subject.classificationImatges per ressonància magnètica
dc.subject.classificationVisió per ordinador
dc.subject.classificationAprenentatge automàtic
dc.subject.otherMagnetic resonance imaging
dc.subject.otherComputer vision
dc.subject.otherMachine learning
dc.titleCardiac magnetic resonance radiomics reveal differential impact of sex, age, and vascular risk factors on cardiac structure and myocardial tissue
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion

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