High diagnostic performance of time-resolved MR angiography in spinal arteriovenous shunts. Issue 161 (April 2023) - Cao, Lizhen; Feng, Yueshan; Yu, Jiaxing; Ma, Yongjie; Zhang, Mo; Yao, Xinyu; Liu, Jiabin; Ye, Ming; He, Chuan; Li, GuiLin; Hong, Tao; Ling, Feng; et al.
Highlights: TR-MRA has high sensitivity and NPV for SAVSs and SDAVSs. TR-MRA can correctly classify SAVSs. For SDVASs, TR-MRA has high accuracy in the detection of feeding arteries. Abstract: Background and purpose: In comparison with the limited efficacy of conventional MR imaging and the invasiveness of catheter-based digital subtraction angiography (DSA), time-resolved MR angiography (TR-MRA) has been proposed as a promising examination for early diagnosis of spinal arteriovenous shunts (SAVSs). This paper aims to investigate the diagnostic performance of TR-MRA with scan parameters optimized for SAVSs evaluation in a large number of patients. Methods: One hundred patients with suspected SAVSs were enrolled. Each patient underwent preoperative TR-MRA with optimized scan parameters followed by DSA. The presence or absence of SAVS, the types and the angioarchitecture of SAVSs in the TR-MRA images were diagnostically analyzed. Results: Among the final 97 patients, 80 cases (82.5 %) were diagnosed and classified by TR-MRA as spinal cord arteriovenous shunts (SCAVSs; n = 22), spinal dural arteriovenous shunts (SDAVSs; n = 48), and spinal extradural arteriovenous shunts (SEDAVSs; n = 10). The agreement for classifying SAVSs between TR-MRA and DSA was excellent (κ = 0.91). The sensitivity, specificity, PPV, NPV, and accuracy of TR-MRA for the diagnosis of SAVSs were 100 % (95 % CI, 94.3–100.0 %), 76.5 % (95 % CI, 49.8–92.2 %), 95.2 % (95 % CI, 87.6–98.5 %), 100 % (95 % CI, 71.7–100.0 %), and 95.9 % (95 % CI, 89.9–98.4 %). The accuracy rates of TR-MRA for the detection of feeding arteries were 75.9 %, 91.7 %, and 80.0 % for SCAVSs, SDAVSs, and SEDAVSs respectively. Conclusion: Time-resolved MR angiography showed excellent diagnostic performance for SAVSs screening. Additionally, this method can classify SAVSs and identify feeding arteries in SDAVSs with high diagnostic accuracy.