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Multiparametric US for the Evaluation of Chronic Liver Disease

An early and accurate detection of liver steatosis is important because metabolic dysfunction-associated steatotic liver (MASLD) is associated with several metabolic comorbidities that are risk factors for cardiovascular diseases. Moreover, the literature suggests that fibrosis progression may occur not only in patients with metabolic dysfunction-associated steatotic hepatitis (MASH) but also in those with “benign” liver steatosis. Therefore, tools that non-invasively assess liver fat content and liver fibrosis are of great interest not only for the diagnosis but also for follow-up and prognostication. Algorithms for a quantitative estimation of liver fat content are commercially available and most of them are based on the evaluation of the US attenuation coefficient. Multiple clinical studies, mostly performed with ATI (Canon Medical Systems), have demonstrated good accuracy and reproducibility of these new algorithms for fat quantification. For a few years, liver stiffness assessment with the shear wave elastography (SWE) techniques is considered a reliable substitute for liver biopsy in several clinical scenarios, including MASLD. Guidelines regarding the use of the SWE techniques for the staging of liver fibrosis have been released. For the US evaluation of MASLD, scores that combine US parameters have also been recently propose

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Speaker

Dr. Giovanna Ferraioli

Reference Doctor, Ultrasound Unit

Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, Policlinico San Matteo, University of Pavia, Italy

Course Information

By the end of this session, delegates will

  • Understand the clinical importance of early liver steatosis detection in Chronic Liver Disease.
  • Gain familiarity with non-invasive tools like US algorithms and SWE techniques for assessing liver fat and fibrosis in MASLD diagnosis and management.

This educational talk was created in February 2024. All information contained in this session was correct at the time of distribution.

Disclaimer: Appearing on the Medical Imaging Academy does not represent a commercial partnership or interest from the speaker. The views herein do not represent the views of Canon Medical Systems Ltd.

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