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Numerical simulations of carotid MRI quantify the accuracy in measuring atherosclerotic plaque components in vivo
Author(s) -
Nieuwstadt Harm A.,
Geraedts Tom R.,
Truijman Martine T. B.,
Kooi M. Eline,
Lugt Aad,
Steen Anton F. W.,
Wentzel Jolanda J.,
Breeuwer Marcel,
Gijsen Frank J. H.
Publication year - 2014
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.24905
Subject(s) - intraclass correlation , magnetic resonance imaging , fibrous cap , ground truth , segmentation , medicine , in vivo , radiology , biomedical engineering , reproducibility , computer science , pathology , mathematics , artificial intelligence , statistics , microbiology and biotechnology , biology
Purpose Atherosclerotic carotid plaques can be quantified in vivo by MRI. However, the accuracy in segmentation and quantification of components such as the thin fibrous cap (FC) and lipid‐rich necrotic core (LRNC) remains unknown due to the lack of a submillimeter scale ground truth. Methods A novel approach was taken by numerically simulating in vivo carotid MRI providing a ground truth comparison. Upon evaluation of a simulated clinical protocol, MR readers segmented simulated images of cross‐sectional plaque geometries derived from histological data of 12 patients. Results MR readers showed high correlation ( R ) and intraclass correlation (ICC) in measuring the luminal area ( R = 0.996, ICC = 0.99), vessel wall area ( R = 0.96, ICC = 0.94) and LRNC area ( R = 0.95, ICC = 0.94). LRNC area was underestimated (mean error, −24%). Minimum FC thickness showed a mediocre correlation and intraclass correlation ( R = 0.71, ICC = 0.69). Conclusion Current clinical MRI can quantify carotid plaques but shows limitations for thin FC thickness quantification. These limitations could influence the reliability of carotid MRI for assessing plaque rupture risk associated with FC thickness. Overall, MRI simulations provide a feasible methodology for assessing segmentation and quantification accuracy, as well as for improving scan protocol design. Magn Reson Med 72:188–201, 2014. © 2013 Wiley Periodicals, Inc .