Blind Source Separation-Based Motion Detector for Imaging Super-Paramagnetic Iron Oxide (SPIO) Particles in Magnetomotive Ultrasound Imaging

In magnetomotive ultrasound (MMUS) imaging, an oscillating external magnetic field displaces tissue loaded with super-paramagnetic iron oxide (SPIO) particles. The induced motion is on the nanometer scale, which makes its detection and its isolation from background motion challenging. Previously, a frequency and phase locking (FPL) algorithm was used to suppress background motion by subtracting magnetic field off (B-off) from on (B-on) data. Shortcomings to this approach include long tracking ensembles and the requirement for B-off data. In this paper, a novel blind source separation-based FPL (BSS-FPL) algorithm is presented for detecting motion using a shorter ensemble length (EL) than FPL and without B-off data. MMUS imaging of two phantoms containing an SPIO-laden cubical inclusion and one control phantom was performed using an open-air MMUS system. When background subtraction was used, contrast and contrast to noise ratio (CNR) were, respectively, 1.20±0.20 and 1.56±0.34 times higher in BSS-FPL as compared to FPL-derived images for EL < 3.5 s. However, contrast and CNR were similar for BSS-FPL and FPL for EL ≥ 3.5 s. When only B-on data was used, contrast and CNR were 1.94 ± 0.21 and 1.56 ± 0.28 times higher, respectively, in BSS-FPL as compared to FPL-derived images for all ELs. Percent error in the estimated width and height was 39.30% ± 19.98% and 110.37% ± 6.5% for FPL and was 7.30% ± 7.6% and 16.21% ± 10.29% for BSS-FPL algorithm. This paper is an important step toward translating MMUS imaging to in vivo application, where long tracking ensembles would increase acquisition time and B-off data may be misaligned with B-on due to physiological motion

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

Effect of model thrombus volume and elastic modulus on magnetomotive ultrasound signal under pulsatile flow

Direct ultrasonic imaging of arterial and venous thrombi could aid in diagnosis and treatment planning by providing rapid and cost-effective measurements of thrombus volume and elastic modulus. Toward this end, it was demonstrated that open-air magnetomotive ultrasound (MMUS) provides specific contrast to superparamagnetic iron oxide-labeled model thrombi embedded in gelatin-based blood vessel-mimicking flow phantoms. MMUS was performed on model thrombi in the presence of pulsatile flow that mimics cardiac-induced motion found in real vasculature. The MMUS signal and contrast-to-noise ratio (CNR) were measured across a range of physiologically relevant thrombus volumes and elastic moduli. Model thrombus volumes as small as 0.5 ml were shown to be detectable (CNR > 1) over the entire range of elastic moduli tested (3.5-40 kPa). It was also found that MMUS signal and CNR are increased with increasing thrombus volume (r = 0.99) and decreasing elastic modulus (r =-0.81), while variations in pulsatile flow rate had little effect. These findings demonstrate that MMUS has promise as a direct in vivo thrombosis imaging modality for quantifying thrombus volume and stiffness