Diagnostic accuracy of real-time tissue elastography for the staging of liver fibrosis: a meta-analysis
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Updated: Apr 25, 2026

Author Spotlight: Advancing Hepatic Fibrosis Diagnosis Using Magnetic Resonance Elastography and AI
Published on: July 21, 2023
Kunio Kobayashi1, Haruhisa Nakao, Takeshi Nishiyama
1Division of Gastroenterology, Department of Internal Medicine, Aichi Medical University School of Medicine, Nagakute, Japan.
Objective:
To evaluate the overall accuracy of real-time tissue elastography (RTE) for the staging of liver fibrosis.
Methods:
We systematically reviewed 15 studies (1,626 subjects) in which sensitivity and specificity of RTE for liver fibrosis are available. For each cut-off stage of fibrosis, i.e., F ≥ 1, F ≥ 2, F ≥ 3, and F ≥ 4, summary sensitivity and specificity were estimated using a bivariate random-effects model. Publication bias was assessed using funnel plots and Egger's test.
Results:
Summary sensitivity and specificity were 0.79 and 0.76 for F ≥ 2, 0.82 and 0.81 for F ≥ 3, and 0.74 and 0.84 for F ≥ 4, respectively. Meta-regressions revealed scoring methods of RTE and liver diseases in the samples might not influence sensitivity and specificity of RTE. However, the estimated accuracy of RTE might be overestimated due to publication bias (p = 0.004 for F ≥ 2, p < 0.001 for F ≥ 3, and p = 0.002 for F ≥ 4).
Conclusions:
RTE is not highly accurate for any cut-off stage of fibrosis. Compared with findings of meta-analyses on Transient Elastography and Acoustic Radiation Force Impulse imaging, the overall accuracy of RTE seems to be nearly identical for the evaluation of significant liver fibrosis, but less accurate for the evaluation of cirrhosis.
Key Points:
• Non-invasive methods for evaluating liver fibrosis are necessary to replace liver biopsy. • ARFI is as accurate as TE for evaluating liver fibrosis. • RTE may be as accurate as TE and ARFI for fibrosis. • RTE may be less accurate than TE and ARFI for cirrhosis. • The estimated accuracy of RTE may be overestimated by publication bias.
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