Atherosclerosis is one of the major causes for carotid artery disease. It can cause severe narrowing or even occlusion of the vessel restricting blood flow to the brain and resulting in perfusion deficits and stroke.¹ Being able to characterize the type of plaque will have an immediate impact on not only the diagnosis of carotid artery atherosclerosis but also on the choice of treatment for the patient. Quantitative susceptibility mapping (QSM) has been widely used in brain as a method to quantify the tissue susceptibility.² The susceptibility difference between the vessel wall, hemorrhage (or thrombosis), calcium and surrounding tissue makes QSM a powerful tool for characterizing atherosclerosis. Due to complex structures in the neck, such as the presence of bone and air, existing methods for neck QSM have several limitations. The purpose of this study was to find a reliable method for data collection in order to use QSM to detect carotid plaque and recognize vulnerable features.Data acquisition: One healthy volunteer was imaged on a 3T scanner (MAGNETOM Verio, Siemens Healthcare, Erlangen, Germany) using a three-echo 3D SWI sequence. The imaging parameters were: TE₁=7.5 ms, TE₂=10 ms, TE₃=12.5 ms, TR=23 ms, FA=20°, BW=504 Hz/pixel, voxel size=0.5×0.5×2 mm³ and matrix size=320×320×64. A series of 7 patients was imaged using a five-echo 3D SWI sequence and a 2D TSE black-blood sequence. The imaging parameters for the 3D SWI sequence were: TEs 5, 7.5, 10, 12.5 and 15 ms, TR=26ms, FA=20°, BW=504 Hz/pixel, voxel size=0.5×0.5×2 mm³ and matrix size=320×320×40. The imaging parameters for the 2D TSE sequence were TE=59ms, TR=4000ms, FA=160°, BW=407 Hz/pixel, voxel size=0.3×0.3×2 mm³ and matrix size=512×512×18. Data processing: The following steps were performed to generate susceptibility maps using MATLAB: 1) phase unwrapping using the Catalytic Multiecho Phase Unwrapping Scheme (CAMPUS) algorithm;³ 2) a mask was generated from original magnitude images with unity for regions inside and surrounding the vessel wall, and zero for other regions, and used to extract the vessel in the unwrapped phase images; 3) a regional 2D polynomial fitting was performed in the vessel region to remove background field induced by the global geometry, air-tissue interfaces and any field inhomogeneities; and 4) an inverse filter was applied to the resulting phase images to generate susceptibility maps.⁴The vessel wall of the heathy volunteer was clearly seen in the susceptibility maps (Figure 1). Susceptibility changes inside the wall indicate there were calcified atherosclerosis (Figure 2) and the geometry agreed with black-blood images (Figure 3). A second example shows a dark potentially thrombotic region (Figure 4) that is shown to be hemorrhagic from the susceptibility (Figure 5). The latter may represent the advanced stage of vulnerable plaque.Imaging vessel wall with susceptibility weighted imaging (SWI) and phase was originally suggested some years ago and demonstrated in the vessels in the leg.⁵ Our preliminary results suggest that a multi-echo SWI approach with regional 2D polynomial fitting method is promising for imaging the carotid vessel wall and atherosclerosis. Further studies to better remove background fields and more clearly represent unaliased data around the plaque should lead to a more robust and easy to use approach clinically. Further work in patients comparing QSM and ex vivo histological analysis is necessary to determine the accuracy of this method.