Multiparametric MRI combined with liver volume for quantitative evaluation of liver function in patients with cirrhosis
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    Abdominal Imaging - Original Article
    P: 547-554
    November 2022

    Multiparametric MRI combined with liver volume for quantitative evaluation of liver function in patients with cirrhosis

    Diagn Interv Radiol 2022;28(6):547-554
    1. Department of Radiology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, PR China
    2. Department of Biomedical Engineering, the Key Laboratory of Biomedical Information Engineering of the Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi’an, PR China
    3. The Third Hospital of Hebei Medical University, the Key Laboratory of Biomedical Information Engineering of the Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi’an, PR China
    No information available.
    No information available
    Received Date: 20.01.2022
    Accepted Date: 09.06.2022
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    ABSTRACT

    PURPOSE

    We aimed to establish a liver function evaluation model by combining multiparametric magnetic resonance imaging (MRI) with liver volume (LV) and further verify the effectiveness of the model to evaluate liver function.

    METHODS

    This retrospective study included 101 consecutive cirrhosis patients (69 cases for modeling group and 32 cases for validation group) who underwent gadoxetic acid-enhanced MRI. Five signal intensity parameters were obtained by measuring the signal intensities of the liver, spleen, and erector spinae before and 20 minutes after gadoxetic acid disodium enhancement. The diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) were obtained from intravoxel incoherent motion diffusion-weighted imaging. The LV parameters (Vliver, Vspleen, and Vliver/Vspleen) were obtained using 3-dimensional image generation software. The most effective parameter was selected from each of the 3 methods, and a multivariate regression model for liver function evaluation was established and validated.

    RESULTS

    In the modeling group, relative enhancement (RE), D*, and Vliver/Vspleen showed significant differences among the different liver function groups (P < .001). Receiver operating characteristic analysis showed that these parameters had the highest area under the curve (AUC) values for distinguishing Child-Pugh A from Child-Pugh B and C groups (0.917, 0.929, and 0.885, respectively). The following liver function model was obtained by multivariate regression analysis: F(x)=3.96 − 1.243 (RE) − 0.034 (D*) − 0.080 (Vliver/Vspleen) (R2=0.811, P < .001). In the patients with cirrhosis, the F(x) of Child-Pugh A, B, and C were 1.16 ± 0.44, 1.95 ± 0.29, and 2.79 ± 0.38, respectively. In the validation group, the AUC for F(x) to distinguish Child-Pugh A from Child-Pugh B and C was 0.973.

    CONCLUSION

    Combining multiparametric MRI with LV effectively distinguished patients with different ChildPugh grades. This model could hence be useful as a novel radiological marker to estimate the liver function.

    References

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