Analysis of agreement between radiologists with different levels of CEUS diagnostic experience in CEUSLI-RADS nodule classification: Based on CEUS LI-RADS v2017

Compared to the independent learning CEUS LI-RADS v2017 guidelines, unified and simplified CEUS LI-RADS typical sign images can effectively improve the reliability of diagnosis among radiologists with different levels of experience.

Authors

Institutions

Publication Details

Journal
Medical Ultrasonography
Published
2026-03-02
DOI
https://doi.org/10.11152/mu-4595
Primary Topic
Hepatocellular Carcinoma Treatment and Prognosis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysis of agreement between radiologists with different levels of CEUS diagnostic experience in CEUSLI-RADS nodule classification: Based on CEUS LI-RADS v2017

Minhong Zou, L Wu, Qingjin Zeng, Weizhen Lin et al.
Medical Ultrasonography
Hepatocellular Carcinoma Treatment and Prognosis
article

Analysis of agreement between radiologists with different levels of CEUS diagnostic experience in CEUSLI-RADS nodule classification: Based on CEUS LI-RADS v2017

Minhong Zou, L Wu, Qingjin Zeng, Weizhen Lin, Xiaomei Wang
article en

Abstract

Compared to the independent learning CEUS LI-RADS v2017 guidelines, unified and simplified CEUS LI-RADS typical sign images can effectively improve the reliability of diagnosis among radiologists with different levels of experience.

Medical Ultrasonography
Sun Yat-sen University (CN), Dongguan People’s Hospital (CN), Third Affiliated Hospital of Sun Yat-sen University (CN)
Openalex Percentile: Top 39%
Hepatocellular Carcinoma Treatment and Prognosis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.