Assessment of hepatic fibrosis with magnetic resonance elastography.

By M. Yin, J. Talwalkar, K. Glaser, Armando Manduca, R. Grimm, P. Rossman, J. Fidler, R. Ehman. Clinical Gastroenterology and Hepatology, 2007

964 citations recorded by the source corpus.

Subfields: Epidemiology, Physiology, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/38706395dc70ce820035dcc5785568816d406c92

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Epidemiology

1. Laurent Castéra
2. Y. Sumida
3. X. Forns

In Physiology

1. Clifford R. Jack Jr.

In Radiology, Nuclear Medicine and Imaging

1. Joshua D. Trzasko
2. Clifford R. Jack Jr.
3. Thomas L. Chenevert

Citations in the corpus

• Non-invasive evaluation of liver fibrosis using transient elastography. (2008, background): “Preliminary studies in human subjects have confirmed the feasibility of these techniques for quantitative assessment of hepatic fibrosis [66–70].”
• Magnetic Resonance Imaging More Accurately Classifies Steatosis and Fibrosis in Patients With Nonalcoholic Fatty Liver Disease Than Transient Elastography. (2016, methodology): “0-T imagers (GE Healthcare, Milwaukee, WI, USA) located at several different clinical sites on our campus; a two-dimensional MRE protocol was used, similar to one previously described in the literature between December 2013 and April 2015 [23].”
• Magnetic Resonance Elastography of Liver: Technique, Analysis and Clinical Applications (2013, background): “MRE has also been shown to be useful for differentiating between various stages of fibrosis (25,37,38).”
• MAGNETIC RESONANCE ELASTOGRAPHY: A REVIEW (2010, background): “The required vibrations are again produced by the Lorentz force, but the static magnetic field is from a devoted permanent magnet present in the acoustic speaker (Yin et al., 2007; Asbach et al., 2008).”
• Quantitative magnetic resonance imaging phantoms: A review and the need for a system phantom (2018, background): “Examples of MR biomarkers include tumor volume (4–6), brain volume (7–10), functional network connectivity (11–13), isotropic (14,15) or anisotropic (16,17) water diffusion constants (18), local metabolite concentrations (10,15,19,20), blood flow fields (21–23), fat fraction (24–27), lung function (”