Volume 15 Supplement 1
Simultaneous intracranial angiography and intraplaque hemorrhage imaging using SNAP
© Wang et al; licensee BioMed Central Ltd. 2013
Published: 30 January 2013
Intracranial atherosclerotic disease (IAD) accounts for 9-15% of all stroke incidents in the US , and the ratio is even higher in some racial groups . Although angiography based imaging remains the prevalent diagnostic tool for IAD detection, it's unable to detect high risk lesions via direct visualization of the vessel wall. Lesions with intraplaque hemorrhage (IPH) on the carotid arteries have been associated with significantly increased clinical symptoms and plaque progress. An imaging tool that can detect both the luminal stenosis and high risk vessel wall disease is of clinical importance for IAD patient management. In this study, the recently proposed SNAP  technique was particularly optimized to simultaneously detect luminal stenosis and IPH for IAD patients.
The SNAP technique was optimized toward the M1 segment of the middle cerebral arteries as it is the most frequent target of IADs. The optimized sequence has a shifted IR slab with a coverage of 25 cm.
One healthy volunteer and 3 patients with diagnosed IAD were recruited in this study. All MR scans were performed using a 3T whole body scanner (Philips Achieva, R3.21, the Netherlands) with an 8-ch brain coil. Geometrically matched SNAP and TOF scans were conducted on all subjects for easy comparison. For both scans, 1×1×1 mm3 isotropic resolution was acquired for a 160×160×50 mm3 FOV, the images were then zero-padded to 0.5×0.5×0.5 mm3 isotropic resolution. The SNAP images were reconstructed to allow MRA-only or MRA-IPH joint views, using a method described before .
The SNAP technique is for the first time optimized and applied to the intracranial artery atherosclerotic disease imaging. It promises to offer a unique approach to detect both luminal stenosis and high-risk intraplaque hemorrhage lesions for patients with IAD.
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.