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Multiparametric US for Identifying Metabolic Dysfunction-associated Steatohepatitis: A Prospective Multicenter Study.

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Multiparametric ultrasound accurately predicts metabolic dysfunction-associated steatohepatitis (MASH) in patients with fatty liver disease. A combined model using attenuation coefficient, ALT, and INR shows good diagnostic performance.

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Area of Science:

  • Hepatology
  • Medical Imaging
  • Diagnostic Ultrasound

Background:

  • Noninvasive evaluation of metabolic dysfunction-associated fatty liver disease (MAFLD) is crucial.
  • Multicenter studies on multiparametric ultrasound for MAFLD assessment are limited.
  • Accurate prediction of metabolic dysfunction-associated steatohepatitis (MASH) is needed.

Purpose of the Study:

  • To assess multiparametric ultrasound, including attenuation imaging (ATI) and 2D shear-wave elastography (SWE).
  • To evaluate the ability of these techniques in predicting MASH in MAFLD patients.
  • To determine diagnostic performance regardless of hepatitis B virus infection status.

Main Methods:

  • Prospective, cross-sectional, multicenter study of 424 adults with MAFLD.
  • Multiparametric ultrasound (ATI and 2D SWE) and liver biopsy were performed.
  • Multivariable logistic regression and ROC curve analysis were used for risk factor assessment and diagnostic performance evaluation.

Main Results:

  • Attenuation coefficient (AC), ALT, and INR were independently associated with MASH.
  • A combined model (AC, ALT, INR) achieved AUCs of 0.85 (training) and 0.77 (validation) for MASH prediction.
  • Good diagnostic performance was observed across subgroups with and without diabetes or hepatitis B virus infection.

Conclusions:

  • A combined model incorporating AC, ALT level, and INR demonstrates significant ability to predict MASH in MAFLD patients.
  • Multiparametric ultrasound offers a promising noninvasive approach for MASH assessment in MAFLD.
  • This multicenter study provides robust evidence for the clinical utility of this combined model.