Evidence map›Paper›PMID 39690042›Full record

ArticleUltrasound in medicine & biology2025

Quantitative Liver Fat Assessment by Handheld Point-of-Care Ultrasound: A Technical Implementation and Pilot Study in Adults.

Dorathy Tamayo-Murillo, Jake T Weeks, Cody A Keller, Michael Andre, Celene Gonzalez, Andrew Li, Eduardo Grunvald, Joy Liau, Sedighe Hosseini Shabanan, Tanya Wolfson and 7 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Ultrasound in medicine & biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Identification of Hepatic Fibrosis and Steatosis via A Point-of-Care Transient Elastography System With Integrated AI.Liver international : official journal of the International Association for the Study of the Liver · 2026
    Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors.

Dorathy Tamayo-MurilloDepartment of Radiology, University of California San Diego, La Jolla, CA, USA. Electronic address: dtamayomurillo@health.ucsd.edu.
Jake T WeeksDepartment of Radiology, Liver Imaging Group, University of California San Diego, La Jolla, CA, USA.
Cody A KellerDepartment of Radiology, Liver Imaging Group, University of California San Diego, La Jolla, CA, USA.
Michael AndreDepartment of Radiology, University of California San Diego, La Jolla, CA, USA.
Celene GonzalezDepartment of Radiology, Liver Imaging Group, University of California San Diego, La Jolla, CA, USA.
Andrew LiDepartment of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL, USA.
Eduardo GrunvaldUCSD Center for Advanced Weight Management, Division of General Internal Medicine, University of California San Diego, La Jolla, CA, USA.
Joy LiauDepartment of Radiology, University of California San Diego, La Jolla, CA, USA.
Sedighe Hosseini ShabananDepartment of Radiology, Liver Imaging Group, University of California San Diego, La Jolla, CA, USA.
Tanya WolfsonDepartment of Medicine, Computer And Statistics Laboratory, University of California San Diego, La Jolla, CA, USA.
Jingyi ZuoDepartment of Biomedical Engineering and Mechanics, Virginia Polytechnic Institute and State University, Blackburg, VA, USA.
Adam RobinsonDepartment of Radiology, University of California San Diego, La Jolla, CA, USA.
Carolina Amador CarrascalButterfly Network Inc., Burlington, MA, USA.
Nevada SanchezButterfly Network Inc., Burlington, MA, USA.
Scott B ReederDepartments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine, University of Wisconsin, Madison, WI, USA.
Aiguo HanDepartment of Biomedical Engineering and Mechanics, Virginia Polytechnic Institute and State University, Blackburg, VA, USA.
Claude B SirlinDepartment of Radiology, Liver Imaging Group, University of California San Diego, La Jolla, CA, USA.

Funding

Technical Validation of MRI Biomarkers of Liver FatR01DK088925 · NIDDK · UNIVERSITY OF WISCONSIN-MADISON · PI REEDER, SCOTT B., SIRLIN, CLAUDE B · 2010 to 2021
$7.1M
QUS Technology for Diagnosis and Grading of Hepatic Steatosis in NAFLDR01DK106419 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI LOOMBA, ROHIT, SIRLIN, CLAUDE B · 2015 to 2019
$3.4M
Traning Clinical Scientists in Radiological ImagingT32EB005970 · NIBIB · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Eric Y Chang, Rebecca Ann Rakow-Penner · 2007 to 2026
$3.2M
NIBIB NIH HHS T32 EB005970NIDDK NIH HHS R01 DK088925NIDDK NIH HHS R01 DK106419
6 · The paper itself

Abstract

objectivesTo implement, examine the feasibility of, and evaluate the performance of quantitative ultrasound (QUS) with a handheld point-of-care US (POCUS) device for assessing liver fat in adults. MATERIALS AND

methodsThis prospective IRB-approved, HIPAA-compliant pilot study enrolled adults with overweight or obesity. Participants underwent chemical-shift-encoded magnetic resonance imaging to estimate proton density fat fraction (PDFF) and, within 1 mo, QUS with a POCUS device by expert sonographers and novice operators (no prior US scanning experience). Radiofrequency data from the liver collected with the POCUS device were analyzed offline using probe-specific calibrations to estimate two QUS parameters: attenuation coefficient (AC) and backscatter coefficient (BSC). Area under the receiver operating characteristic curve (AUC) of each parameter was estimated for classifying presence/absence of hepatic steatosis (defined as PDFF ≥ 5%). Spearman rank correlation between each parameter and PDFF was estimated and its significance assessed.

resultsOf 18 participants (mean age, 43 y ± 14; 17 women), 8 had hepatic steatosis (PDFF ≥ 5%). Both AC and BSC classified hepatic steatosis accurately with AUCs of 0.96-0.97 for expert and 0.88-0.89 for novice operators (p < 0.01 for all) and correlated significantly with PDFF with rho's of 0.65-0.69 for expert and 0.58-0.65 for novice operators (p < 0.02 for all).

conclusionQUS can be implemented on a POCUS device and can be performed by expert or novice operators after limited training in adults with overweight or obesity with promising initial results.

Indexed as

Fatty LiverPoint-of-Care SystemsAdultFeasibility StudiesFemaleHumansLiverMaleMiddle AgedObesityPilot ProjectsProspective StudiesUltrasonographyBiomarkersDiagnosisFatty liverMagnetic resonance imagingUltrasonography

Identifiers

PMID39690042
PMCPMC12258410

What Socratic holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.