title: Quantifying hepatic fibrosis using a biexponential model of diffusion weighted imaging in ex vivo liver specimens.
abstract: The purpose of this study was to evaluate the non-Gaussian behavior of diffusion related signal decay of the ex vivo murine liver tissues from a dietary model of hepatic fibrosis. To this end, a biexponential formalism was used to model high b-value diffusion imaging (up to 3500 s/mm(2)), the findings of which were correlated with liver histopathology and compared to a simple monoexponential model. The presence of a major, fast diffusing component and a minor, slow diffusing component was demonstrated. With increasing hepatic fibrosis, the fractional contribution of the fast diffusing component decreased, as did the diffusion coefficient of the fast diffusing component. Strong correlation between the degrees of liver fibrosis and a two-predictor regression model incorporating parameters of the biexponential model was found. Using Akaike's Information Criterion analyses, the biexponential model resulted in an improved fit of the high b-value diffusion data when compared to the monoexponential model.
authors.affiliation: Department of Radiology, Boston University Medical Center, Boston, MA 02218, USA. stephan.anderson@bmc.org
authors.forename: Stephan W
authors.initials: SW
authors.lastname: Anderson
authors.forename: Brian
authors.initials: B
authors.lastname: Barry
authors.forename: Jorge A
authors.initials: JA
authors.lastname: Soto
authors.forename: Al
authors.initials: A
authors.lastname: Ozonoff
authors.forename: Michael
authors.initials: M
authors.lastname: O'Brien
authors.forename: Hernan
authors.initials: H
authors.lastname: Jara
mesh_terms: D000818:Animals; D004058:Diffusion; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D005355:Fibrosis; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008099:Liver / Q000473:pathology*; D008103:Liver Cirrhosis / Q000473:pathology*; D008297:Male; D051379:Mice; D008810:Mice, Inbred C57BL; D015233:Models, Statistical; D012044:Regression Analysis