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Comparison of single-sequence T1w TFE MRI with multisequence MRI for the quantification of lipid-rich necrotic core in atherosclerotic plaque

  • Vincent C. Cappendijk
  • , Sylvia Heeneman
  • , Alfons G. H. Kessels
  • , Kitty B. J. M. Cleutjens
  • , Geert Willem H. Schurink
  • , Rob J. Th J. Welten
  • , Werner H. Mess
  • , Robert-Jan van Suylen
  • , Tim Leiner
  • , Mat J. A. P. Daemen
  • , Jos M. A. van Engelshoven
  • , M. Eline Kooi

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

To prospectively determine the accuracy of semiquantitative analysis of the amount of lipid-rich necrotic core (LRNC) in atherosclerotic plaque using multi- as well as single-sequence T1-weighted (w) turbo field echo (TFE) MRI. Histology served as a reference standard. Sixty-four symptomatic patients with carotid stenosis > or =70% were included and underwent endarterectomy after an MRI scan. Two MRI readers classified relative signal intensities in regions of interest in the vessel wall. The amount of LRNC was determined semiquantitatively using an algorithm based on fixed combinations of multiple MR pulse sequences as well as solely based on T1w TFE images. Interreader agreement was expressed by intraclass correlation coefficients (ICCs). Agreement between MRI and histology was determined by linear regression (R). Interreader reproducibility for quantification of LRNC was high (ICC, 95% confidence interval [CI]): multisequence 0.86 (0.77-0.94), and single sequence 0.91 (0.85-0.95). There was good agreement between MRI and histology for both MR readers for quantification based on multisequence as well as single sequence MRI, 0.80 <or = R <or = 0.85 (P <0.0001). The amount of LRNC using single-sequence T1w TFE MRI is a reproducible, accurate, and fast way to quantify LRNC in carotid atherosclerotic plaque
Original languageEnglish
Pages (from-to)1347-1355
JournalJournal of magnetic resonance imaging
Volume27
Issue number6
DOIs
Publication statusPublished - 2008

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This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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