Performing liver imaging at a high level: quality and adequacy in LI-RADS.
Cheng William Hong, Guilherme M Cunha, Takeshi Yokoo, Alexandra Roudenko, Zachary S Kelm, Alice Fung, Mustafa R Bashir, Sara Lewis, Cynthia Santillan, Robert Marks and 3 more
Review in Abdominal radiology (New York), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
0numbers the graph read from it
0cells of the map it votes in
1citing 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.
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
13 authors.
Cheng William HongUniversity of California, San Francisco, USA. cheng.hong@ucsf.edu.
Guilherme M CunhaUniversity of Washington, Seattle, USA.
Takeshi YokooThe University of Texas Southwestern Medical Center, Dallas, USA.
Alexandra RoudenkoAllegheny Health Network, Pittsburgh, USA.
Zachary S KelmMayo Clinic, Rochester, USA.
Alice FungOregon Health & Science University, Portland, USA.
Mustafa R BashirDuke University, Durham, USA.
Sara LewisIcahn School of Medicine at Mount Sinai, New York, USA.
Cynthia SantillanUniversity of California, San Diego, USA.
Robert MarksUniversity of California, San Diego, USA.
Claude B SirlinLiver Imaging Group, University of California, San Diego, USA.
Kathryn J FowlerScripps Clinic Medical Group, La Jolla, USA. kathryn.jane.fowler@gmail.com.
Victoria ChernyakColumbia University Irving Medical Center, New York, USA. vichka17@hotmail.com.
Funding
Pediatric Trials in Non-Alcoholic Steatohepatitis (NASH)U01DK061734 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ROHIT LOOMBA · 2002 to 2026
$24.4M
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
San Diego Cirrhosis Clinical Research NetworkU01DK130190 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ROHIT LOOMBA · 2021 to 2026
$2.3M
Fatty liver disease and its determinants in an American Indian Population: the Strong Heart StudyR01DK110096 · NIDDK · TEXAS BIOMEDICAL RESEARCH INSTITUTE · PI COLE, SHELLEY A · 2016 to 2018
$2.3M
Quantitative Ultrasound To Diagnose Nonalcoholic Fatty Liver Disease in Children.R01DK135951 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI CLAUDE B SIRLIN, Jeffrey Barnett Schwimmer · 2024 to 2026
$2.1M
Point-of Care MR Device to Estimate T1 Relaxation Time as a Biomarker of Liver Disease (resubmission)R43EB034626 · NIBIB · LIVIVOS INC. · PI PRADO, PABLO J, SIRLIN, CLAUDE B · 2023 to 2023
$310k
Accurate Point of Care Liver Disease DiagnosticsR43DK135225 · NIDDK · LIVIVOS INC. · PI PRADO, PABLO J, SIRLIN, CLAUDE B · 2022 to 2022
Imaging is critical to HCC management, including surveillance, diagnosis, staging, and treatment response assessment, which requires it be performed consistently at a high level. The Liver Imaging Reporting and Data System (LI-RADS) was developed to standardize the acquisition, interpretation, and reporting of liver imaging, but until now, has not addressed the essential component of exam quality and adequacy. In this manuscript, we discuss the concepts of quality and adequacy and their clinical significance in the setting of HCC diagnostic imaging and treatment response assessment. We describe prior and current efforts to improve image quality and adequacy. We review common sources of image degradation that need to be addressed and the rationale behind LI-RADS technical recommendations. Finally, we offer a glimpse into preliminary efforts to develop an adequacy scoring system and make a call to action for all stakeholders to contribute to this important goal.
Indexed as
Carcinoma, HepatocellularLiver NeoplasmsRadiology Information SystemsHumansAdequacyHCCLI-RADSLiverQuality
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 OpenQuestion graph.
Performing liver imaging at a high level: quality and adequacy in LI-RADS. · full record | OpenQuestion