Ultrasonic characterization of the nonlinear properties of canine livers by measuring shear wave speed and axial strain with increasing portal venous pressure

Abstract

Elevated hepatic venous pressure is the primary source of complications in advancing liver disease. Ultrasound imaging is ideal for potential noninvasive hepatic pressure measurements as it is widely used for liver imaging. Specifically, ultrasound based stiffness measures may be useful for clinically monitoring pressure, but the mechanism by which liver stiffness increases with hepatic pressure has not been well characterized. This study is designed to elucidate the nonlinear properties of the liver during pressurization by measuring both hepatic shear wave speed (SWS) and strain with increasing pressure. Tissue deformation during hepatic pressurization was tracked in 8 canine livers using successively acquired 3-D B-mode volumes and compared with concurrently measured SWS. When portal venous pressure was increased from clinically normal (0–5 mmHg) to pressures representing highly diseased states at 20 mmHg, the liver was observed to expand with axial strain measures up to 10%. At the same time, SWS estimates were observed to increase from 1.5–2 m/s at 0–5 mmHg (baseline) to 3.25–3.5 m/s at 20 mmHg.

Ultrasound Shear Wave Elastography Helps Discriminate Low‐grade From High‐grade Bowel Wall Fibrosis in Ex Vivo Human Intestinal Specimens

“…This phenomenon, which is likely due to differences in bowel wall collagen and water content, has been demonstrated in a Crohn disease animal model, 11 and further investigations in human patients are needed. A recent study by Rotemberg et al 20 demonstrated that the liver behaves in a nonlinear manner with internal pressurization, with substantial increases in shear wave speed measurements from baseline. Sarvazyan et al 18 suggested that tissue nonlinearity as assessed by shear wave imaging may be another useful acoustic biomarker that could yield potentially important diagnostic information in human tissues.…”

Material Characterization of in Vivo and in Vitro Porcine Brain Using Shear Wave Elasticity

“…Anatomical and mechanical variation at the micron scale of ARF excitation is small. Reduction in complexity can capture simple behavioral response and the isotropic, elastic model has been used successfully to describe several other viscoelastic organs (Rotemberg et al, 2013; Vappou et al, 2006). We appreciate the limitations of applying linear elastic assumptions for organs such as the brain and we have strong incentives to characterize distortion and diminishing shear wave profiles in lossy tissues as well as examine viscoelasticity with higher order mathematical models.…”

“…Ultrasound is also lower cost and higher accessibility. Clinical studies have yielded consistent information in relatively homogenous tissues including breast, prostate, heart, and cervix (Carlson et al, 2014; Hsu et al, 2007; Li et al, 2009; Svensson and Amiras, 2006; Zhai et al, 2012), and SWEI has gained clinical acceptance for non-invasive staging of fibrosis in the liver (Palmeri et al, 2011, 2008) and experiments have demonstrated hepatic stiffening as a function of portal pressure (Rotemberg et al, 2013, 2012). Shear wave imaging has also recently seen implementation in the brain to determine material properties (Macé et al, 2011).…”

Material characterization of in vivo and in vitro porcine brain using shear wave elasticity

“…We hypothesized that stiffness would track similarly to the changes seen in pressure volume index as a function of cerebral perfusion pressure and ICP [16]. But, the observation that the brain did not display any variation under increased ICP is in line with liver stiffening observed with pressurization under constraint [10,11].…”

“…Over the micro scale this reduction of complexity can capture simple behavioral response; however gross structural and mechanical differentials seen in the brain effect properties on every scale. This consideration will eventually lead us to apply higher order, viscoelastic models to our ultrasound datasets [4,10,11,15].…”