OBJECTIVE: This study evaluates the ability of MRI to quantify all major carotid atherosclerotic plaque components in vivo. METHODS AND RESULTS: Thirty-one subjects scheduled for carotid endarterectomy were imaged with a 1.5T scanner using time-of-flight-, T1-, proton density-, and T2-weighted images. A total of 214 MR imaging locations were matched to corresponding histology sections. For MRI and histology, area measurements of the major plaque components such as lipid-rich/necrotic core (LR/NC), calcification, loose matrix, and dense (fibrous) tissue were recorded as percentages of the total wall area. Intraclass correlation coefficients (ICCs) were computed to determine intrareader and inter-reader reproducibility. MRI measurements of plaque composition were statistically equivalent to those of histology for the LR/NC (23.7 versus 20.3%; P=0.1), loose matrix (5.1 versus 6.3%; P=0.1), and dense (fibrous) tissue (66.3% versus 64%; P=0.4). Calcification differed significantly when measured as a percentage of wall area (9.4 versus 5%; P<0.001). Intrareader and inter-reader reproducibility was good to excellent for all tissue components, with ICCs ranging from 0.73 to 0.95. CONCLUSIONS: MRI-based tissue quantification is accurate and reproducible. This application can be used in therapeutic clinical trials and in prospective longitudinal studies to examine carotid atherosclerotic plaque progression and regression.
OBJECTIVE: This study evaluates the ability of MRI to quantify all major carotid atherosclerotic plaque components in vivo. METHODS AND RESULTS: Thirty-one subjects scheduled for carotid endarterectomy were imaged with a 1.5T scanner using time-of-flight-, T1-, proton density-, and T2-weighted images. A total of 214 MR imaging locations were matched to corresponding histology sections. For MRI and histology, area measurements of the major plaque components such as lipid-rich/necrotic core (LR/NC), calcification, loose matrix, and dense (fibrous) tissue were recorded as percentages of the total wall area. Intraclass correlation coefficients (ICCs) were computed to determine intrareader and inter-reader reproducibility. MRI measurements of plaque composition were statistically equivalent to those of histology for the LR/NC (23.7 versus 20.3%; P=0.1), loose matrix (5.1 versus 6.3%; P=0.1), and dense (fibrous) tissue (66.3% versus 64%; P=0.4). Calcification differed significantly when measured as a percentage of wall area (9.4 versus 5%; P<0.001). Intrareader and inter-reader reproducibility was good to excellent for all tissue components, with ICCs ranging from 0.73 to 0.95. CONCLUSIONS: MRI-based tissue quantification is accurate and reproducible. This application can be used in therapeutic clinical trials and in prospective longitudinal studies to examine carotid atherosclerotic plaque progression and regression.
Authors: R van 't Klooster; O Naggara; R Marsico; J H C Reiber; J-F Meder; R J van der Geest; E Touzé; C Oppenheim Journal: AJNR Am J Neuroradiol Date: 2012-03-22 Impact factor: 3.825
Authors: Fabien Hyafil; Andreas Schindler; Dominik Sepp; Tilman Obenhuber; Anna Bayer-Karpinska; Tobias Boeckh-Behrens; Sabine Höhn; Marcus Hacker; Stephan G Nekolla; Axel Rominger; Martin Dichgans; Markus Schwaiger; Tobias Saam; Holger Poppert Journal: Eur J Nucl Med Mol Imaging Date: 2015-10-03 Impact factor: 9.236
Authors: Mauricio S Galizia; Alex Barker; Yihua Liao; Jeremy Collins; James Carr; Mary M McDermott; Michael Markl Journal: Eur Radiol Date: 2013-12-11 Impact factor: 5.315
Authors: Tjun Y Tang; Simon P S Howarth; Sam R Miller; Martin J Graves; Jean-Marie U-King-Im; Rikin A Trivedi; Zhi Yong Li; Stewart R Walsh; Andrew P Brown; Peter J Kirkpatrick; Michael E Gaunt; Jonathan H Gillard Journal: J Neurol Neurosurg Psychiatry Date: 2007-06-19 Impact factor: 10.154
Authors: Mihály Károlyi; Harald Seifarth; Gary Liew; Christopher L Schlett; Pál Maurovich-Horvat; Paul Stolzmann; Guangping Dai; Shuning Huang; Craig J Goergen; Masataka Nakano; Fumiyuki Otsuka; Renu Virmani; Udo Hoffmann; David E Sosnovik Journal: JACC Cardiovasc Imaging Date: 2013-03-14