A motion-based approach to abdominal clutter reduction

In ultrasound images, clutter is a noise artifact most easily observed in anechoic or hypoechoic regions. It appears as diffuse echoes overlying anatomical structures of diagnostic importance, obscuring tissue borders and reducing image contrast. A novel clutter reduction method for abdominal images is proposed, wherein the abdominal wall is displaced during successive-frame image acquisitions. A region of clutter distal to the abdominal wall was observed to move with the abdominal wall, and finite impulse response (FIR) and blind source separation (BSS) motion filters were implemented to reduce this clutter. The proposed clutter reduction method was tested in simulated and phantom data and applied to fundamental and harmonic in vivo bladder and liver images from 2 volunteers. Results show clutter reductions ranging from 0 to 18 dB in FIR-filtered images and 9 to 27 dB in BSS-filtered images. The contrast-to-noise ratio was improved by 21 to 68% and 44 to 108% in FIR- and BSS-filtered images, respectively. Improvements in contrast ranged from 4 to 12 dB. The method shows promise for reducing clutter in other abdominal images

Comparison of Acoustic Radiation Force Impulse Imaging Derived Carotid Plaque Stiffness with Spatially Registered MRI Determined Composition

Measurements of plaque stiffness may provide important prognostic and diagnostic information to help clinicians distinguish vulnerable plaques containing soft lipid pools from more stable, stiffer plaques. In this preliminary study, we compare in vivo ultrasonic Acoustic Radiation Force Impulse (ARFI) imaging derived measures of carotid plaque stiffness with composition determined by spatially registered Magnetic Resonance Imaging (MRI) in five human subjects with stenosis >50%. Ultrasound imaging was implemented on a commercial diagnostic scanner with custom pulse sequences to collect spatially registered 2D longitudinal B-mode and ARFI images. A standardized, multi-contrast weighted MRI sequence was used to obtain 3D Time of Flight (TOF), T1 weighted (T1W), T2 weighted (T2W), and Proton Density Weighted (PDW) transverse image stacks of volumetric data. The MRI data was segmented to identify lipid, calcium, and normal loose matrix components using commercially available software. 3D MRI segmented plaque models were rendered and spatially registered with 2D B-mode images to create fused ultrasound and MRI volumetric images for each subject. ARFI imaging displacements in regions of interest (ROIs) derived from MRI segmented contours of varying composition were compared. Regions of calcium and normal loose matrix components identified by MRI presented as homogeneously stiff regions of similarly low (typically ≈ 1µm) displacement in ARFI imaging. MRI identified lipid pools >2mm(2), found in three out of five subjects, presented as softer regions of increased displacement that were on average 1.8 times greater than the displacements in adjacent regions of loose matrix components in spatially registered ARFI images. This work provides early evidence supporting the use of ARFI imaging to noninvasively identify lipid regions in carotid artery plaques in vivo that are believed to increase the propensity of a plaque to rupture. Additionally, the results provide early training data for future studies and aid in the interpretation and possible clinical utility of ARFI imaging for identifying the elusive vulnerable plaque