Staging of rat liver fibrosis using monoexponential, stretched exponential and diffusion kurtosis models with diffusion weighted imaging- magnetic resonance
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Genwen Hu1, Wen Liang2, Mingxiang Wu1, Queenie Chan3, Yufa Li4, Jianmin Xu1, Liangping Luo5 and Xianyue Quan2
1Department of Radiology, The Second Clinical Medical College of Jinan University, Shenzhen People’s Hospital, Shenzhen 518020, China
2Department of Radiology, Zhujiang Hospital, Southern Medical University, Guangzhou 510282, China
3MR Clinical Science, Philips Healthcare, Hong Kong 20023, China
4Department of Pathology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
5Department of Radiology, The First Affiliated Hospital of Jinan University, Guangzhou 510280, China
Xianyue Quan, email: [email protected]
Liangping Luo, email: [email protected]
Jianmin Xu, email: [email protected]
Keywords: liver fibrosis; diffusion weighted imaging; stretched exponential model; diffusion kurtosis imaging
Received: September 28, 2017 Accepted: December 05, 2017 Published: December 18, 2017
Early diagnosis of liver fibrosis is important. The objective of this study was to explore the characteristics and to assess the accuracy of monoexponential, stretched exponential models (SEM), and diffusion kurtosis imaging (DKI) with diffusion-weighted imaging (DWI)-magnetic resonance imaging (MRI) in various stages of liver fibrosis in two standard rat models induced by carbon tetrachloride (CCl4) and biliary duct ligation (BDL). Parameters (ADC, Dapp, Kapp, DDC, α) were measured with a 3.0T MRI. Liver fibrosis stages (F0–F4) were defined by METAVIR scoring. Parameters (ADC, Dapp, DDC) were found to be negatively associated (r: -0.675~-0.789; P<0.05) with advancement of fibrosis stage. The analysis of receiver operating characteristic (ROC) curves illustrated that the areas under the curves (AUC) for ADC, Dapp, and DDC were 0.687~0.957, 0.805~0.938 and 0.876~1.000, respectively. The study showed that (ADC, Dapp, Kapp, DDC, α) from various diffusion models reflected pathological and physiological tissue changes. We conclude that SEM and DKI may provide more accurate information about diffusion, and non-Gaussian diffusion analysis may be a complementary tool for the assessment of liver fibrosis.
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