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Combined spatiotemporal and frequency-dependent shear wave elastography enables detection of vulnerable carotid plaques as validated by MRI
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Medical Imaging.ORCID iD: 0000-0003-1002-2070
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2020 (English)In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 10, no 1, article id 403Article in journal (Refereed) Published
Abstract [en]

Fatal cerebrovascular events are often caused by rupture of atherosclerotic plaques. However, rupture-prone plaques are often distinguished by their internal composition rather than degree of luminal narrowing, and conventional imaging techniques might thus fail to detect such culprit lesions. In this feasibility study, we investigate the potential of ultrasound shear wave elastography (SWE) to detect vulnerable carotid plaques, evaluating group velocity and frequency-dependent phase velocities as novel biomarkers for plaque vulnerability. In total, 27 carotid plaques from 20 patients were scanned by ultrasound SWE and magnetic resonance imaging (MRI). SWE output was quantified as group velocity and frequency-dependent phase velocities, respectively, with results correlated to intraplaque constituents identified by MRI. Overall, vulnerable lesions graded as American Heart Association (AHA) type VI showed significantly higher group and phase velocity compared to any other AHA type. A selection of correlations with intraplaque components could also be identified with group and phase velocity (lipid-rich necrotic core content, fibrous cap structure, intraplaque hemorrhage), complementing the clinical lesion classification. In conclusion, we demonstrate the ability to detect vulnerable carotid plaques using combined SWE, with group velocity and frequency-dependent phase velocity providing potentially complementary information on plaque characteristics. With such, the method represents a promising non-invasive approach for refined atherosclerotic risk prediction.

Place, publisher, year, edition, pages
Nature Research , 2020. Vol. 10, no 1, article id 403
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Medical Engineering
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URN: urn:nbn:se:kth:diva-267772DOI: 10.1038/s41598-019-57317-7PubMedID: 31942025Scopus ID: 2-s2.0-85077940693OAI: oai:DiVA.org:kth-267772DiVA, id: diva2:1411584
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QC 20200304

Available from: 2020-03-04 Created: 2020-03-04 Last updated: 2020-05-11Bibliographically approved

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Marlevi, DavidLarsson, Matilda

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