Abstract
Introduction The aims of the present study are to evaluate the potential of high-resolution black-blood MRI (hr-bb-cMRI) to differentiate common cervical arteriopathies and to evaluate interobserver reproducibility. Methods Forty-three consecutive patients with distinct cervical arteriopathies were examined with cervical hr-bb-cMRI at 3.0 Te with fat-saturated pre- and post-contrast T1w, T2w, and TOF images using dedicated carotid surface coils at our institution. Twenty-three patients had atherosclerotic disease, causing significant stenosis in 12 patients while 11 patients had moderate stenosis. Eight patients presented with cervical vasculitis, and five patients had arterial dissection. Furthermore, seven control subjects with no evidence of carotid disease were included. Two experienced readers blinded to all clinical information reviewed all MR images and classified both carotid and vertebral arteries as affected either by atherosclerosis, dissection, vasculitis, or no disease. Finally, a consensus reading was performed. Results On a per-vessel level, test performance parameters (sensitivity, specificity, positive predictive value, negative predictive value) were 95, 97.7, 92.9, and 98.5 % for atherosclerotic disease;91, 100, 100, and 98.7% for vasculitis;and 100, 100, 100, and 100 % for dissection, respectively. On a perpatient level, performance parameters were 95.7, 85.7, 97.2, and 85.7 % for the diagnosis of atherosclerosis and 100, 100, 100, and 100 % for the diagnosis of dissection and of vasculitis, respectively. Accuracy rates were all above 95 % for all entities. There was a high agreement between observers both in a per-vessel (kappa = 0.83) and in a per-patient analysis (kappa= 0.82). Conclusion This study demonstrates that hr-bb-cMRI is able to non-invasively differentiate between the most common cervical arteriopathies with an excellent interreader reproducibility.
Item Type: | Journal article |
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Faculties: | Medicine |
Subjects: | 600 Technology > 610 Medicine and health |
ISSN: | 0028-3940 |
Language: | English |
Item ID: | 46247 |
Date Deposited: | 27. Apr 2018, 08:10 |
Last Modified: | 04. Nov 2020, 13:23 |