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Characterizing non‐gaussian, high b‐value diffusion in liver fibrosis: Stretched exponential and diffusional kurtosis modeling
Author(s) -
Anderson Stephan W.,
Barry Brian,
Soto Jorge,
Ozonoff Al,
O'Brien Michael,
Jara Hernan
Publication year - 2014
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.24234
Subject(s) - kurtosis , akaike information criterion , gaussian , exponential function , diffusion , diffusion mri , nuclear magnetic resonance , magnetic resonance imaging , materials science , mathematics , physics , statistics , medicine , radiology , mathematical analysis , thermodynamics , quantum mechanics
Purpose To employ the stretched exponential and diffusional kurtosis models to study the non‐Gaussian behavior of diffusion‐related signal decay of the liver in an animal model of hepatic fibrosis. Materials and Methods High b‐value diffusion imaging data (up to 3500 s/mm 2 ) of ex vivo murine liver specimens was acquired using a 9.4 T MRI scanner. A simple monoexponential model as well as the stretched exponential and diffusional kurtosis models were employed to analyze the diffusion data, the results of which were correlated with liver histopathology. Results Strong correlations between histopathological assessments of hepatic fibrosis and parameters derived from the stretched exponential and diffusional kurtosis models were found. Using Akaike's Information Criterion (AIC) analyses, the kurtosis model was found to result in an improved fit of the high b‐value diffusion data when compared to both the monoexponential and stretched exponential models. Conclusion The use of diffusional kurtosis or stretched exponential models, applied to the characterization of the non‐Gaussian behavior of the molecular diffusion of liver exhibited over an extended b‐factor range, affords the potential for an increased capability of magnetic resonance imaging (MRI) in the characterization of chronic liver disease. J. Magn. Reson. Imaging 2014;39:827–834. © 2013 Wiley Periodicals, Inc .