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Quantitative fat and R2* mapping in vivo to measure lipid-rich necrotic core and intraplaque hemorrhage in carotid atherosclerosis
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2016 (English)In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594Article in journal (Refereed) Published
Abstract [en]

Purpose: The aim of this work was to quantify the extent of lipid-rich necrotic core (LRNC) and intraplaque hemorrhage (IPH) in atherosclerotic plaques. Methods: Patients scheduled for carotid endarterectomy underwent four-point Dixon and T1-weighted magnetic resonance imaging (MRI) at 3 Tesla. Fat and R2* maps were generated from the Dixon sequence at the acquired spatial resolution of 0.60×0.60×0.70mm voxel size. MRI and three-dimensional (3D) histology volumes of plaques were registered. The registration matrix was applied to segmentations denoting LRNC and IPH in 3D histology to split plaque volumes in regions with and without LRNC and IPH. Results: Five patients were included. Regarding volumes of LRNC identified by 3D histology, the average fat fraction by MRI was significantly higher inside LRNC than outside: 12.64±0.2737% versus 9.294±0.1762% (mean±standard error of the mean [SEM]; P<0.001). The same was true for IPH identified by 3D histology, R2* inside versus outside IPH was: 71.81±1.276 s-1 versus 56.94±0.9095 s-1 (mean±SEM; P<0.001). There was a strong correlation between the cumulative fat and the volume of LRNC from 3D histology (R2=0.92) as well as between cumulative R2* and IPH (R2=0.94). Conclusion: Quantitative mapping of fat and R2* from Dixon MRI reliably quantifies the extent of LRNC and IPH.

Place, publisher, year, edition, pages
John Wiley & Sons, 2016.
Keyword [en]
Atherosclerosis, Carotid artery, Magnetic resonance imaging, Quantitative mapping
National Category
Medical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-195547DOI: 10.1002/mrm.26359OAI: oai:DiVA.org:kth-195547DiVA: diva2:1048611
Note

QC 20161121

Available from: 2016-11-21 Created: 2016-11-03 Last updated: 2016-11-21Bibliographically approved

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Moreno, Samuel Boiso
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School of Technology and Health (STH)
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