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Meta-Analysis
. 2025 Aug 1;82(2):454-469.
doi: 10.1097/HEP.0000000000001190. Epub 2024 Dec 16.

Diagnostic accuracy of 2D-SWE ultrasound for liver fibrosis assessment in MASLD: A multilevel random effects model meta-analysis

Madalina-Gabriela Indre  1   2   3   4   5 , Dan-Corneliu Leucuta  4 , Monica Lupsor-Platon  4   5 , Laura Turco  1 , Silvia Ferri  2 , Ahmed Hashim  2   6 , Olga Hilda Orasan  4 , Bogdan Procopet  4   5 , Horia Stefanescu  5 , Maria Cristina Morelli  1 , Fabio Piscaglia  2   3 , Federico Ravaioli  2   3
Affiliations
Meta-Analysis

Diagnostic accuracy of 2D-SWE ultrasound for liver fibrosis assessment in MASLD: A multilevel random effects model meta-analysis

Madalina-Gabriela Indre et al. Hepatology. .

Abstract

Background and aims: Metabolic dysfunction-associated steatotic liver disease (MASLD) imposes significant health care burdens. Early detection of advanced fibrosis and cirrhosis in MASLD is essential due to their unfavorable outcomes. This multilevel random-effects meta-analysis aimed to provide the best evidence for the diagnostic accuracy of 2-dimensional shear wave elastography in detecting liver fibrosis in biopsy-proven MASLD.

Approach and results: This study involves systematic search in PubMed/MEDLINE, Embase, Scopus, Web of Science, LILACS, and Cochrane Library electronic databases for full-text articles published in any language up to February 26, 2024. Included studies reported liver stiffness measurement by 2-dimensional shear wave elastography and used histological diagnosis as the gold standard. A linear mixed-effects multiple thresholds model was employed, and summary estimates for sensitivity, specificity (Sp), and summary area under the receiver operator characteristic curve were computed. Twenty observational studies (SuperSonic Imagine, General Electric Healthcare, and Canon Medical Systems) fulfilled the inclusion criteria, comprising 2223 participants with biopsy-proven MASLD. The prevalence of mild fibrosis (F1), significant fibrosis (F2), advanced fibrosis (F3), and cirrhosis (F4) was 30.0%, 18.5%, 17.9%, and 10.9%, respectively. The summary area under the receiver operator characteristic curve [95% CI] in detecting ≥F1, ≥F2, ≥F3, and F4 for all ultrasound machines considered together were 0.82 [0.16-0.98], 0.82 [0.76-0.88], 0.86 [0.77-0.93], and 0.89 [0.80-0.95], respectively. The optimal cutoff values were 6.432 kPa for ≥F1, 8.174 kPa for ≥F2, 9.418 kPa for ≥F3, and 11.548 kPa for F4, respectively.

Conclusions: Our meta-analysis identified optimized cutoffs for fibrosis staging by 2-dimensional shear wave elastography in etiology-specific chronic liver diseases (MASLD), with excellent diagnostic performance, underscoring the potential for standardizing cutoff values.

Keywords: 2-dimensional shear-wave elastography; cirrhosis; liver imaging; metabolic dysfunction–associated steatotic liver disease; noninvasive tests.

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Conflict of interest statement

Bogdan Procopet advises Boehringer Ingelheim International. He is on the speakers’ bureau for AbbVie. Horia Stefanescu is on the speakers’ bureau for General Electric Healthcare and MGT. Fabio Piscaglia advises and is on the speakers’ bureau for AstraZeneca, Eisai, MSD, Siemens Healthineers, and Roche. He consults for and is on the speakers’ bureau for Bracco. He consults for, advises, and is on the speakers’ bureau for Nerviano. He consults for Signant Health. He advises BMS. He is on the speakers’ bureau for Bayer, Esaote, Exact Sciences, Gilead, GE, Ipsen, and Samsung. The remaining authors have no conflicts to report.

Figures

None
Graphical abstract
FIGURE 1
FIGURE 1
PRISMA flow diagram. Abbreviations: GE, General Electric Healthcare; n, number; SSI, SuperSonic Imagine.
FIGURE 2
FIGURE 2
sAUC by multilevel random effects (CICS) model for multiple thresholds data for all US devices together and SuperSonic Imagine (kPa). (A) Mild fibrosis by all US devices; (B) significant fibrosis by all US devices; (C) advanced fibrosis by all US devices; (D) cirrhosis by all US devices; (E) Mild fibrosis by Supersonic Image; (F) significant fibrosis by Supersonic Image; (G) advanced fibrosis by Supersonic Image; (H) cirrhosis by all Supersonic Image. Created in BioRender. Taru, M. (2024) https://BioRender.com/o82f827. Abbreviations: CICS, common random intercept and common slope; F1, mild fibrosis; F2, significant fibrosis; F3, advanced fibrosis; F4, fibrosis; N, number; sAUC, summary area under the receiver operator characteristic curve; Sens, sensitivity; Spec, specificity; US, ultrasound.
FIGURE 3
FIGURE 3
sAUC by multilevel random effects (CICS) model for multiple thresholds data for sensitivity analysis for different subpopulations (kPa). (A) significant fibrosis in Asian studies; (B) advanced fibrosis in Asian studies; (C) cirrhosis in Asian studies; (D) significant fibrosis in type 2 diabetes mellitus; (E) advanced fibrosis in type 2 diabetes mellitus; (F) cirrhosis In type 2 diabetes mellitus; (G) significant fibrosis in obesity; (H) advanced fibrosis in obesity; (I) cirrhosis in obesity. Created in BioRender. Taru, M. (2024) https://BioRender.com/a51n542. Abbreviations: CICS, common random intercept and common slope; F2, significant fibrosis; F3, advanced fibrosis; F4, cirrhosis; N, number; sAUC, summary area under the receiver operator characteristic curve; Sens, sensitivity; Spec, specificity; T2DM, type 2 diabetes mellitus.
FIGURE 4
FIGURE 4
Optimal 2D-SWE cutoff values for differentiating different stages of liver fibrosis in biopsy-proven MASLD. Abbreviations: MASLD, metabolic dysfunction–associated steatotic liver disease; N/A, not available; NPV, negative predictive value; PPV, positive predictive value; sAUC, summary area under the receiver operator characteristic curve.
See this image and copyright information in PMC

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