OBJECTIVE: This scoping review maps the landscape of quantitative ultrasound (QUS) techniques for hepatic fat assessment, emphasizing their physical principles, signal-processing strategies, technological implementations, reference standards, and sources of variability, and highlights their potential to advance noninvasive liver imaging in metabolic dysfunction-associated steatotic liver disease. Methods: Following JBI methodology and reporting in accordance with the PRISMA-ScR checklist, a comprehensive search was conducted in PubMed, MEDLINE, ScienceDirect, and Scopus for studies published from January 2010 to October 2025. Human studies evaluating QUS-based methods for hepatic fat quantification in the context of MASLD were included. Screening and data extraction were performed using standardized procedures, with iterative refinement of the data-charting framework. Results: Out of 1,265 identified records, 150 studies were included. The body of literature has evolved from initial proof-of-concept and signal-processing investigations to more recent research emphasizing clinical relevance, reproducibility, and real-world use. Publication activity rose significantly after around 2018, coinciding with the commercial release of QUS technologies. The most common methods were based on attenuation coefficients, followed by approaches using backscattering coefficients, speed-of-sound estimation, envelope statistics, and combined multiparametric techniques. Recently, MRI-PDFF has become the preferred reference standard in validation studies, whereas liver biopsy and the controlled attenuation parameter have been used less often as primary comparison methods. Conclusions: Hepatic QUS is a diverse and rapidly evolving field encompassing multiple methodological categories grounded in distinct physical principles. Although QUS offers a physically grounded and clinically promising framework for noninvasive hepatic fat assessment, substantial heterogeneity in acquisition protocols, implementation, and reporting limits comparability across platforms. Greater standardization, improved inter-manufacturer reproducibility, and further development of robust multiparametric approaches are essential to enhance its clinical utility in the management of MASLD. .
Albuquerque et al. (Wed,) studied this question.