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Volume 39 Issue 3
Mar.  2023
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Article Navigation >  Journal of Clinical Hepatology  > 2023  >  39(3): 573-579

Value of liver-muscle signal intensity and serum markers in diagnosis of chronic hepatitis B liver fibrosis

DOI: 10.3969/j.issn.1001-5256.2023.03.014

  • Department of Medical Imaging, Affiliated Hospital of Yan'an University, Yan'an, Shaanxi 716000, China

Research funding:

Science and Technology Research and Development Project of Yan'an (2018KS-11)

More Information
  • Corresponding author: HUANG Xiaoqi, 344653354@qq.com (ORCID: 0000-0003-1365-759X)
  • Received Date: 2022-08-01
  • Accepted Date: 2022-09-06
  • Published Date: 2023-03-20
    Abstract
  •   Objective  To investigate the value of liver/muscle ratio (LMR) on susceptibility-weighted imaging (SWI) and serum markers in the diagnosis of the severity of chronic hepatitis B liver fibrosis after grouping based on alanine aminotransferase (ALT) level.  Methods  A retrospective analysis was performed for 255 patients with chronic hepatitis B who attended Affiliated Hospital of Yan'an University from October 2018 to September 2021, and the patients were divided into severe liver fibrosis group (SLF group) and non-severe liver fibrosis group (non-SLF group). The SLF group was defined as liver stiffness measurement (LSM) > 9.0 kPa and ALT level within the normal range or LSM > 12.0 kPa and ALT level greater than 1-5 times of the upper limit of normal. LMR was calculated by measuring the mean SWI value of the liver (SWIliver) and the signal intensity of the erector spinae. The t-test was used for comparison of normally distributed continuous data between two groups, and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two group; the chi-square test was used for comparison of categorical data between two groups. The binary logistic regression analysis was used to investigate the influencing factors for SLF. The receiver operating characteristic (ROC) curve was used to analyze the diagnostic performance of LMR and its combination with serum markers, and the DeLong test was used to compare the difference in the area under the ROC curve (AUC).  Results  Compared with the non-SLF group, the SLF group had significantly higher ALT (Z=-3.569, P < 0.001), aspartate aminotransferase (AST) (Z=-5.495, P < 0.001), hyaluronic acid (HA) (Z=-6.746, P < 0.001), laminin (LN) (Z=-5.459, P < 0.001), type Ⅳ collagen (Ⅳ-C)(Z=-8.470, P < 0.001), type Ⅲ procollagen (PCⅢ) (Z=-6.326, P < 0.001), aspartate aminotransferase-to-platelet ratio index (Z=-9.004, P < 0.001), and FIB-4 (Z=-8.357, P < 0.001) and significantly lower prothrombin time activity (PTA) (t=10.088, P < 0.001), platelet count (t=9.163, P < 0.001), SWIliver (t=2.347, P=0.02), and LMR×10 (Z=-4.447, P < 0.001). PTA, HA, Ⅳ-C, and LMR×10 were independent influencing factors for SLF. LMR×10 had an AUC of 0.675 (95% confidence interval [CI]: 0.614-0.732) in the diagnosis of SLF, which was significantly higher than that of SWIliver (AUC=0.594, 95%CI: 0.531-0.655) (Z=3.984, P < 0.001). PTA+HA+Ⅳ-C+LMR×10 and PTA+HA+Ⅳ-C had an AUC of 0.937 (95%CI: 0.896-0.966) and 0.905 (95%CI: 0.858-0.941), respectively, suggesting that PTA+HA+Ⅳ-C+LMR×10 had a better diagnostic performance than PTA+HA+Ⅳ-C (Z=2.228, P=0.026).  Conclusion  LMR and serum markers can accurately distinguish SLF after grouping based on ALT level. LMR is a quantitative and objective imaging indicator and is better than SWIliver, and it can also improve the diagnostic performance of serum markers for SLF in clinical practice.

     

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