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DOI 10.1016/j.lfs.2020.118710

Медицинская библиотека · Life sciences · 2020

Novel imaging-based approaches for predicting the hepatic venous pressure gradient in a porcine model of liver cirrhosis and portal hypertension.

Ma Yujia, Dong Deshuo, Gong Zheng, Yan Bin, Guo Qiyong

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Аннотация

AIMS: Hepatic venous pressure gradient (HVPG) is critical for staging and prognosis prediction of portal hypertension (PH). However, HVPG measurement has limitations (e.g., invasiveness). This study examined the value of non-invasive, imaging-based approaches including magnetic resonance elastography (MRE) and intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) for the prediction of HVPG in a porcine model of liver cirrhosis and PH.

MAIN

METHODS

Male Bama miniature pigs were used to establish a porcine model of liver cirrhosis and PH induced by embolization. They were randomly assigned to an experimental group (n = 12) and control group (n = 3). HVPG was examined before and after transjugular intrahepatic portosystemic shunt (TIPS). MRE and IVIM-DWI were performed to obtain quantitative parameters including liver stiffness (LS) in MRE, tissue diffusivity (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) in IVIM-DWI. The correlation between HVPG and the parameters was assessed.

KEY FINDINGS: LS values were significantly greater in the experimental group, while f values were significantly decreased at 4, 8, and 12 weeks after embolization compared to the control group. Furthermore, HVPG was significantly lower immediately after versus before TIPS. In parallel, LS and f values showed significant alterations after TIPS, and these changes were consistent with a reduction in HVPG. Spearman analysis revealed a significant correlation between the parameters (LS and f) and HVPG. The equation was eventually generated for prediction of HVPG.

SIGNIFICANCE: The findings show a good correlation between HVPG and the quantitative parameters; thus, imaging-based techniques have potential as non-invasive methods for predicting HVPG.

Для цитирования: Ma Yujia, Dong Deshuo, Gong Zheng, Yan Bin, Guo Qiyong. Novel imaging-based approaches for predicting the hepatic venous pressure gradient in a porcine model of liver cirrhosis and portal hypertension.. Life sciences. 2020. DOI: 10.1016/j.lfs.2020.118710.

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