Quantitative Ultrasound(DeepUSFF) vs MRI-PDFF for Liver Fat Assessment in MASLD
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: Quantitative ultrasound (DeepUSFF).
- Who it may be relevant to
- Registry conditions: Metabolic Dysfunction-Associated Steatotic Liver Disease, Hepatic Steatosis, Liver Disease Parenchymal. Basic parameters: from 18 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- United States, South Korea
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Unsure about the terms? Read our patient guide →
Official title
Evaluation of a Quantitative Ultrasound Model(DeepUSFF) for Liver Fat Quantification in Patients With Metabolic Dysfunction-Associated Steatotic Liver Disease: A Multicenter Prospective Study Using MRI-PDFF as the Reference Standard
Overview
This multicenter prospective study aims to evaluate the correlation between quantitative ultrasound fat fraction (USFF) and MRI-PDFF (Proton Density Fat Fraction) for liver fat quantification in patients with metabolic dysfunction-associated steatotic liver disease (MASLD). The study will compare the diagnostic accuracy of quantitative ultrasound imaging against MRI-PDFF as the reference standard.
Detailed description
Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a common liver disease requiring accurate assessment for treatment planning and monitoring. While liver biopsy remains the gold standard, it is invasive with potential complications. MRI-PDFF has emerged as an accurate non-invasive method, but it is expensive and has limited accessibility. Quantitative ultrasound techniques using RF data have been developed to provide objective liver fat assessment.
Objective: To prospectively evaluate the correlation between quantitative ultrasound-derived fat fraction (DeepUSFF) and MRI-PDFF in patients with suspected MASLD across different ethnicities and varying degrees of hepatic steatosis.
Methods: This prospective multicenter study will recruit 62 patients (31 from each participating center) suspected of having MASLD. All participants will undergo both quantitative ultrasound examination and non-contrast liver MRI within one week. The primary endpoint is the correlation coefficient between ultrasound fat fraction and MRI-PDFF. Secondary endpoints include diagnostic accuracy metrics and inter-observer reproducibility.
Interventions
- Device Quantitative ultrasound (DeepUSFF)
\*\*Novel Quantitative Ultrasound Technology Assessment\*\* This study evaluates Samsung Medison's proprietary DeepUSFF (Deep Learning-based Ultrasound Fat Fraction) technology, a next-generation quantitative ultrasound method for liver fat assessment that differs from conventional ultrasound approaches in several key aspects: advanced RF data analysis, proprietary technology, standardized protocol, direct MRI-PDFF correlation, specific MSALD poopulation and multicenter design.
Primary outcome measures
- Correlation between Ultrasound Fat Fraction and MRI-PDFF [Time frame: At enrollment (single time point assessment)]
- Correlation between Ultrasound Fat Fraction and MRI-PDFF [Time frame: At enrollment (single time point assessment)]
Eligibility criteria
Inclusion criteria
- Patients with clinically suspected MASLD based on abnormal ultrasound or liver function tests requiring liver ultrasound or MRI examination
- BMI ≥25 kg/m² or waist circumference >90 cm (male) or >80 cm (female), suggesting high likelihood of fatty liver disease
- Living liver transplant donors requiring preoperative liver ultrasound or MRI examination
- Age ≥18 years
- Understanding and signing informed consent
Exclusion criteria
- Significant alcohol consumption in the past 2 years:
Male: ≥30-60g/day average alcohol intake Female: ≥20-50g/day average alcohol intake
-Chronic liver disease:
Histological diagnosis of chronic liver disease HBsAg positive Anti-HCV positive Other suspected chronic liver diseases
-Liver failure:
Serum albumin <3.2 g/dL INR >1.3 Direct bilirubin >1.3 mg/dL
- History of esophageal varices, ascites, hepatic encephalopathy, or acute biliary obstruction
- History of liver cancer diagnosis or treatment
- History of liver surgery
- Pregnancy
- Inability to obtain adequate liver ultrasound imaging:
Patient cooperation impossible Inadequate image acquisition as determined by investigator
-Inability to obtain adequate liver MRI imaging: Patient cooperation impossible Severe obesity preventing MRI examination MRI contraindications (cardiac pacemaker, etc.) Other factors preventing adequate imaging as determined by investigator
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Allocation
- N/A
- Model
- Single group
- Masking
- Open label
- Primary purpose
- Diagnostic
Study locations
United States · 1 center
- southwoods imaging (Northeastern Ohio Radiology Research and Education Fund ) — Boardman
South Korea · 1 center
- Seoul National University Hospital — Seoul
Publications
- Xie WJ, Zhang B. Learning the Formation Mechanism of Domain-Level Chromatin States with Epigenomics Data. Biophys J. 2019 May 21;116(10):2047-2056. doi: 10.1016/j.bpj.2019.04.006. Epub 2019 Apr 11. PMID 31053260
- Fan C, Shen M, Nussinov Z, Liu Z, Sun Y, Liu YY. Reply to: Deep reinforced learning heuristic tested on spin-glass ground states: The larger picture. Nat Commun. 2023 Sep 14;14(1):5659. doi: 10.1038/s41467-023-41108-w. No abstract available. PMID 37709759
- Zhou G, Qin Y, Petticord D, Qiao X, Jiang M. Plant-ant interactions mediate herbivore-induced conspecific negative density dependence in a subtropical forest. Sci Total Environ. 2024 Jun 1;927:172163. doi: 10.1016/j.scitotenv.2024.172163. Epub 2024 Apr 1. PMID 38569958
Identifiers
NCT: NCT07192159 · 2503-162-1625