OBJECTIVE: The objective of our study was to assess a protocol of study of carotid atherosclerosis coupling vascular wall imaging and luminal imaging in the same examination and to evaluate the accuracy of high-resolution MRI with a neurovascular coil in carotid plaque characterization. SUBJECTS AND METHODS: Thirty-two consecutive patients with 34 carotid artery stenoses were prospectively enrolled. MRI was performed on a 1.5-T unit. Plaque assessment was performed starting with a diffusion-weighted sequence and followed by a fat-suppressed T1-weighted sequence; after contrast-enhanced MR angiography (CE-MRA), all patients were evaluated with a T1-weighted 3D high-resolution sequence. Carotid plaques were classified as type A, having a large lipid-necrotic core; type B, being a complex fibrotic-calcified plaque with soft content (mixed plaque); or type C, being a fibrotic-calcified plaque (hard). Additional features indicative of vulnerable plaque such as intraplaque hemorrhage (IPH), ulceration, and severe stenosis were registered. MR findings were compared with surgical specimens. RESULTS: MRI correctly identified 11 of 13 type A, eight of 11 type B, and eight of 10 type C plaques (sensitivity, 84.6%, 72.7%, and 80%, respectively). In the identification of lipid-necrotic core plaque, MRI showed a sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 84.6%, 100%, 100%, and 91.3%, respectively (κ = 0.87). For reordering all plaques in two groups (i.e., soft vs nonsoft) in the identification of soft plaques, MRI had a sensitivity, specificity, PPV, and NPV of 83.3%, 80%, 90.9%, and 66.7%, respectively (κ = 0.59). IPH, ulcers, and severe stenosis were detected in eight of eight, 11 of 13, and 25 of 25 cases, respectively. CONCLUSION: In patients with carotid atherosclerosis, ongoing CE-MRA with a neurovascular coil for the simultaneous detection of unstable plaques is feasible. Our MR protocol accurately identifies the major features of vulnerable plaque.
OBJECTIVE: The objective of our study was to assess a protocol of study of carotid atherosclerosis coupling vascular wall imaging and luminal imaging in the same examination and to evaluate the accuracy of high-resolution MRI with a neurovascular coil in carotid plaque characterization. SUBJECTS AND METHODS: Thirty-two consecutive patients with 34 carotid artery stenoses were prospectively enrolled. MRI was performed on a 1.5-T unit. Plaque assessment was performed starting with a diffusion-weighted sequence and followed by a fat-suppressed T1-weighted sequence; after contrast-enhanced MR angiography (CE-MRA), all patients were evaluated with a T1-weighted 3D high-resolution sequence. Carotid plaques were classified as type A, having a large lipid-necrotic core; type B, being a complex fibrotic-calcified plaque with soft content (mixed plaque); or type C, being a fibrotic-calcified plaque (hard). Additional features indicative of vulnerable plaque such as intraplaque hemorrhage (IPH), ulceration, and severe stenosis were registered. MR findings were compared with surgical specimens. RESULTS: MRI correctly identified 11 of 13 type A, eight of 11 type B, and eight of 10 type C plaques (sensitivity, 84.6%, 72.7%, and 80%, respectively). In the identification of lipid-necrotic core plaque, MRI showed a sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 84.6%, 100%, 100%, and 91.3%, respectively (κ = 0.87). For reordering all plaques in two groups (i.e., soft vs nonsoft) in the identification of soft plaques, MRI had a sensitivity, specificity, PPV, and NPV of 83.3%, 80%, 90.9%, and 66.7%, respectively (κ = 0.59). IPH, ulcers, and severe stenosis were detected in eight of eight, 11 of 13, and 25 of 25 cases, respectively. CONCLUSION: In patients with carotid atherosclerosis, ongoing CE-MRA with a neurovascular coil for the simultaneous detection of unstable plaques is feasible. Our MR protocol accurately identifies the major features of vulnerable plaque.
Authors: A A Appel; C-Y Chou; J C Larson; Z Zhong; F J Schoen; C M Johnston; E M Brey; M A Anastasio Journal: Br J Radiol Date: 2013-01 Impact factor: 3.039
Authors: Jai Jai Shiva Shankar; Jingwen Zhang; Marlise dos Santos; Howard Lesiuk; Ravi Mohan; Cheemun Lum Journal: Neuroradiology Date: 2012-04-21 Impact factor: 2.804
Authors: M Tang; X Yan; J Gao; L Li; X Zhe; Xin Zhang; F Jiang; J Hu; N Ma; K Ai; Xiaoling Zhang Journal: AJNR Am J Neuroradiol Date: 2022-07-21 Impact factor: 4.966