Publications by authors named "Samantha L Lipman"

This work discusses challenges we have encountered in acquiring reproducible measurements of shear wave speed (SWS) in the median nerve and suggests methods for improving reproducibility. First, procedural acquisition challenges are described, including nerve echogenicity, transducer pressure and transmit focal depth. Second, we present an iterative, radon sum-based algorithm that was developed specifically for measuring the SWS in median nerves.

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Shear wave elasticity imaging (SWEI) characterizes the mechanical properties of human tissues to differentiate healthy from diseased tissue. Commercial scanners tend to reconstruct shear wave speeds for a region of interest using time-of-flight methods reporting a single shear wave speed (or elastic modulus) to the end user under the assumptions that tissue is elastic and shear wave speeds are not dependent on the frequency content of the shear waves. Human tissues, however, are known to be viscoelastic, resulting in dispersion and attenuation.

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Conventional multiple-track-location shear wave elasticity imaging (MTL-SWEI) is a powerful tool for noninvasively estimating tissue elasticity. The resolution and noise levels of MTL-SWEI systems, however, are limited by ultrasound speckle. Single-track-location SWEI (STL-SWEI) is a novel variant which fixes the position of the tracking beam and modulates the push location to effectively cancel out the effects of speckle-induced bias.

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Shear waves propagating through interfaces where there is a change in stiffness cause reflected waves that can lead to artifacts in shear wave speed (SWS) reconstructions. Two-dimensional (2-D) directional filters are commonly used to reduce in-plane reflected waves; however, SWS artifacts arise from both in- and out-of-imaging-plane reflected waves. Herein, we introduce 3-D shear wave reconstruction methods as an extension of the previous 2-D estimation methods and quantify the reduction in image artifacts through the use of volumetric SWS monitoring and 4-D-directional filters.

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Prostate cancer (PCa) is the most common non-cutaneous malignancy among men in the United States and the second leading cause of cancer-related death. Multi-parametric magnetic resonance imaging (mpMRI) has gained recent popularity to characterize PCa. Acoustic Radiation Force Impulse (ARFI) imaging has the potential to aid PCa diagnosis and management by using tissue stiffness to evaluate prostate zonal anatomy and lesions.

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