Shear wave arrival time estimates correlate with local speckle pattern

Single track location shear wave elasticity imaging (STL-SWEI) is immune to speckle bias, but the quality of the images is depth-dependent. We hypothesize that plane wave imaging can reduce the depth dependency of STL-SWEI. To test this hypothesis, we developed a novel technique known as plane-wave single track location shear wave elasticity imaging (pSTL-SWEI). To evaluate the pSTL-SWEI’s potential, we performed studies on phantoms and excised murine pancreatic tumors. The mean shear wave speeds (SWS) measured with STL-SWEI and pSTL-SWEI were similar. However, the elastographic signal-to-noise ratio (SNRe ) of pSTL-SWEI elastograms was noticeably higher than that produced with STL-SWEI. Specifically, we observed an improvement in SNRe ranging from 39.9%−55.1%, depending on tissue stiffness. The spatial resolution of pSTL-SWEI elastograms was 2.7%−12.1% lower than that produced with STL-SWEI. pSTL-SWEI elastograms displayed higher contrast-to-noise ratio (CNRe ) than those produced with STL-SWEI, especially when imaging was performed with low push pulse intensities and low pulse durations.

Section: Discussionmentioning

confidence: 99%

Plane-Wave Imaging Improves Single-Track Location Shear Wave Elasticity Imaging

Ahmed

Gerber

McAleavey

et al. 2018

“…In the final case, the noise is applied evenly but a tracking error (consisting of AWGN) is introduced in the data to simulate speckle bias. The standard deviation of the tracking error is set to 0.5 mm to provide an order of magnitude consistent with the RMS tracking errors presented in our previous work [16]. This added tracking error is used to simulate the single and multiple tracking location configurations.…”

Section: Methodsmentioning

confidence: 98%

“…e − k i ( ω )( x 0 + x e ) models the transformation between the initial ARF exciation and S 1 ( ω ) with x 0 is the distance between the pushing location and the tracking location, and random variable x e is the error in x 0 due to speckle bias. This speckle bias arises due to the fact that bright speckle is preferentially tracked when the shear wave velocity is being determined via Window Normalized Cross-Correlation (WNCC) of the original RF data [13], [16]. This bright speckle need not be along the beam axis and, therefore, our actual tracking location is truly x 0 + x e .…”

Section: Theorymentioning

confidence: 99%

Single tracking location acoustic radiation force impulse viscoelasticity estimation (STL-VE): A method for measuring tissue viscoelastic parameters

Langdon

Elegbe

McAleavey

2015

Single Tracking Location (STL) Shear wave Elasticity Imaging (SWEI) is a method for detecting elastic differences between tissues. It has the advantage of intrinsic speckle bias suppression compared to Multiple Tracking Location (MTL) variants of SWEI. However, the assumption of a linear model leads to an overestimation of the shear modulus in viscoelastic media. A new reconstruction technique denoted Single Tracking Location Viscosity Estimation (STL-VE) is introduced to correct for this overestimation. This technique utilizes the same raw data generated in STL-SWEI imaging. Here, the STL-VE technique is developed by way of a Maximum Likelihood Estimation (MLE) for general viscoelastic materials. The method is then implemented for the particular case of the Kelvin-Voigt Model. Using simulation data, the STL-VE technique is demonstrated and the performance of the estimator is characterized. Finally, the STL-VE method is used to estimate the viscoelastic parameters of ex-vivo bovine liver. We find good agreement between the STL-VE results and the simulation parameters as well as between the liver shear wave data and the modeled data fit.

“…[44]. Speckle bias is a source of arrival time estimation noise that is not captured by the CRLB model.…”

Section: Analysis Of Errorsmentioning

confidence: 99%

“…When tissue motion is tracked, the system is more sensitive to the areas of constructive interference. Therefore, the wave arrival times for a particular beam location are biased towards the bright speckle [44]. The magnitude of this bias is determined by the size of the point spread function (PSF) of the system, as speckle size is correlated with PSF size.…”

Section: Analysis Of Errorsmentioning

confidence: 99%

On System-Dependent Sources of Uncertainty and Bias in Ultrasonic Quantitative Shear-Wave Imaging

Deng

Rouze

Palmeri

et al. 2016

Ultrasonic quantitative shear wave imaging methods have been developed over the last decade to estimate tissue elasticity by measuring the speed of propagating shear waves following acoustic radiation force excitation. This work discusses eight sources of uncertainty and bias arising from ultrasound system dependent parameters in ultrasound shear wave speed (SWS) measurements. Each of the eight sources of error are discussed in the context of a linear, isotropic, elastic, homogeneous medium, combining previously reported analyses with Field II simulations, full-wave 2D acoustic propagation simulations and experimental studies. Errors arising from both spatial and temporal sources lead to errors in SWS measurements. Arrival time estimation noise, speckle bias, hardware fluctuations, and phase aberration cause uncertainties (variance) in SWS measurements, while pulse repetition frequency and beamforming errors, as well as coupling medium sound speed mismatch, cause biases in SWS measurements (accuracy errors). Calibration of the sources of bias is an important step in the development of shear wave imaging systems. In a well-calibrated system, where the sources of bias are minimized, and averaging over an ROI is employed to reduce the sources of uncertainty, a SWS error < 3% can be expected.