Basi-parallel anatomic scanning (BPAS-MRI) compared with high-resolution MRI for the diagnosis of vertebrobasilar artery abnormalities.

Journal: European Journal Of Radiology
Published:
Abstract

Objective: To investigate the utility of basi-parallel anatomic scanning magnetic resonance imaging (BPAS-MRI) for the diagnosis of vertebrobasilar artery lesions.

Methods: From October 2017-November 2018, 105 consecutive patients with abnormal configuration of the vertebrobasilar artery on time-of-flight magnetic resonance angiography (TOF-MRA) were enrolled. Conventional high-resolution MRI combined with TOF-MRA were performed to diagnose lesions and were used as the standard for sensitivity and specificity determination. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of BPAS-MRI combined with TOF-MRA were calculated. The consistencies between the two methods were evaluated by kappa test.

Results: Of the 105 patients, 45 were diagnosed with arteriosclerosis, 46 with vertebral artery dysplasia, 11 with artery dissection or dissecting aneurysm, and 3 as simple dilatation. Results Compared with conventional high-resolution MRI combined with TOF-MRA, for vertebrobasilar arteriosclerosis, the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of BPAS-MRI combined with TOF-MRA were 95.6 %, 95.0 %, 93.5 %, 96.6 % and 95.2 %, respectively and kappa value was 0.903. For vertebral artery dysplasia, they were 100 %, 96.6 %, 95.8 %, 100 %, and 98.1 %, respectively and kappa value was 0.961. For vertebrobasilar artery dissection or dissection aneurysm, they were 81.8 %, 96.8 %, 97.8 %, 75.0 % and 95.2 %, respectively and kappa value was 0.756.

Conclusions: BPAS-MRI can show the outer contour of the vertebrobasilar artery system. Combined with TOF-MRA, it may be used to differentiate among vertebrobasilar artery abnormalities, and be used in hospitals where conventional high-resolution MRI is not feasible.

Authors
Jiao Liu, Lili Zhao, Li Yao, Xiaohui Li, Tao Li, Heying Wang, Xiaoya Wang, Yating Jian, Man Sun, Ye Li, Meijuan Dang, Yiheng Zhang, Yulun Wu, Guilian Zhang