Improved Endocardial Border Definition with Short-Lag Spatial Coherence (SLSC) Imaging

Abstract

Clutter is a problematic noise artifact in a variety of ultrasound applications. Clinical tasks complicated by the presence of clutter include detecting cancerous lesions in abdominal organs (e.g. livers, bladders) and visualizing endocardial borders to assess cardiovascular health. In this dissertation, an analytical expression for contrast loss due to clutter is derived, clutter is quantified in abdominal images, and sources of abdominal clutter are identified. Novel clutter reduction methods are also presented and tested in abdominal and cardiac images. One of the novel clutter reduction methods is Short-Lag Spatial Coherence (SLSC) imaging. Instead of applying a conventional delay-and-sum beamformer to measure the amplitude of received echoes and form B-mode images, the spatial coherence of received echoes are measured to form SLSC images. The world's first SLSC images of simulated, phantom, and in vivo data are presented herein. They demonstrate reduced clutter and improved contrast, contrast-to-noise, and signal-to-noise ratios compared to conventional B-mode images. In addition, the resolution characteristics of SLSC images are quantified and compared to resolution in B-mode images. A clinical study with 14 volunteers was conducted to demonstrate that SLSC imaging offers 19-33% improvement in the visualization of endocardial borders when the quality of B-mode images formed from the same echo data was poor. There were no statistically significant improvements in endocardial border visualization with SLSC imaging when the quality of matched B-mode images was medium to good.