Postcontrast susceptibility-weighted imaging: a novel technique for the detection of arteriovenous shunting in vascular malformations of the brain.

摘要

BACKGROUND AND PURPOSE: The purpose of this study was to determine the utility of postcontrast susceptibility-weighted MRI (PCSWI) in the evaluation of vascular malformations of the brain (BVM). METHODS: We retrospectively evaluated PCSWI and digital subtraction angiography data from 16 consecutive patients with known or suspected BVM, which had been entered into a prospectively maintained database during a 1-year period. There had been no intervening treatment or change in patients' symptoms between the PCSWI and digital subtraction angiography studies. The use of PCSWI in the detection of arteriovenous shunting was compared with that of routine noncontrast susceptibility-weighted imaging, time-of-flight MR angiography, and contrast-enhanced MR angiography using digital subtraction angiography results as the reference standard. The presence of arteriovenous shunting in PCSWI or susceptibility-weighted imaging sequences was defined by the presence of abnormal signal hyperintensity in the venous structures adjacent to the BVM. RESULTS: A total of 17 BVMs were identified by digital subtraction angiography (9 newly diagnosed arteriovenous malformations, 3 dural arteriovenous fistulas, 4 treated arteriovenous malformations with residual arteriovenous shunting, and 1 complex developmental venous anomaly). PCSWI was 100% sensitive and 100% specific with 100% positive predictive value and 100% negative predictive value for the detection of arteriovenous shunting in these BVMs. The PCSWI/susceptibility-weighted imaging signal intensity ratio in the most prominent early draining venous structure was 1.2+/-0.32. CONCLUSIONS: PCSWI appears to be superior to susceptibility-weighted imaging, time-of-flight MR angiography, and contrast-enhanced MR angiography in detecting arteriovenous shunting in BVMs and may be useful in the initial diagnosis and follow-up of patients with BVMs.