An interventional study of Ultrasound and MRI in MASLD and Pediatric, sponsored by Jae Won Choi. Completed at 1 site in South Korea. Open to participants aged 8 Years to 18 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2025-12-04.
Sponsored by Jae Won Choi · Not applicable, Interventional, and Diagnostic
The purpose of this study is to validate an artificial intelligence (AI)-based algorithm that estimates hepatic steatosis using ultrasound (US) B-mode images in pediatric participants with metabolic dysfunction-associated steatotic liver disease (MASLD). The MRI proton density fat fraction (MRI-PDFF) serves as the reference standard for hepatic fat quantification.
1,474 studies on the registry are indexed under Non-alcoholic Fatty Liver Disease; 303 are open to participants now.
This study's enrollment of 50 is below the median of 60 across 1,072 interventional studies indexed under Non-alcoholic Fatty Liver Disease.
Browse Non-alcoholic Fatty Liver Disease studies →This is the only study on the registry with Jae Won Choi as lead sponsor.
Counted across the registry records on this site, refreshed daily.
Exclusion Criteria:
Diagnostic Test: Ultrasound and MRI
Participants undergo same-day liver imaging including conventional B-mode ultrasound, quantitative ultrasound, and magnetic resonance imaging (MRI). Conventional Ultrasound: B-mode imaging performed on three ultrasound systems (Canon Aplio i800, Philips EPIQ, and Supersonic AIXPLORER) to acquire grayscale liver images for artificial intelligence (AI) analysis. Quantitative Ultrasound: Attenuation imaging (ATI) and shear wave elastography/dispersion measurements performed to assess hepatic fat and stiffness. MRI: Proton density fat fraction (PDFF) measurement used as the reference standard for hepatic steatosis quantification. All imaging is performed on the same day for each participant to ensure temporal consistency across modalities and vendors.
Agreement Between AI-Predicted Ultrasound Fat Fraction (AI-USFF) and MRI Proton Density Fat Fraction (MRI-PDFF)
Reference standard: MRI-PDFF (percentage) \- intraclass correlation coefficient (ICC)
Time frame: At time of imaging (single visit)
Correlation Between AI-USFF and MRI-PDFF
Reference standard: MRI-PDFF (percentage) \- Pearson correlation coefficient (r)
Time frame: At time of imaging (single visit)
Diagnostic Performance of AI-USFF for MRI-Based Hepatic Steatosis Grades
The diagnostic performance of AI-USFF for detecting mild, moderate, and severe hepatic steatosis, as defined by MRI-PDFF thresholds, will be evaluated using area under the receiver operating characteristic curve (AUC).
Time frame: At time of imaging (single visit)
Inter-Vendor Reproducibility of AI-USFF
Reproducibility of AI-USFF across the three ultrasound systems are assessed using the intraclass correlation coefficient (ICC \[2,k\]).
Time frame: At time of imaging (single visit)
This study is completed, as verified in Nov 2025. You cannot join it, but the record below documents what was studied.
Get an email when the registry record changes — status, dates, results — or when someone posts here.
Sign in to followQuestions and observations about this study, from anyone following it. Not medical advice, and not a channel to the study team — their contact details are on the registry record.
Sign in to join the discussion. Reading takes no account; posting does. You choose a display name, and a pseudonym is the default.
Nothing here yet. If you are running this trial, taking part in it, or weighing whether to, this is the place to say so.
Non-alcoholic Fatty Liver Disease→