Evidence map›Paper›PMID 40126795›Full record

Observational studyLa Radiologia medica2025

The role of contrast-enhanced ultrasound in the radiological classification of liver observations identified by CT and MRI.

Hui Huang, Dan-Ni He, Rui-Fang Lu, Wen-Juan Tong, Ying Wang, Si Qin, Rong Wen, Shao-Hong Wu, Si-Min Ruan, Guang-Jian Liu and 6 more

Abstract readMulticenter StudyObservational Study
PubMed Publisher
In one paragraph

Observational study in La Radiologia medica, 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. Review
  2. Review
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

16 authors.

Hui Huang *Department of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Laboratory, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, No. 58 Zhongshan Rd 2, Guangzhou, 510080, People's Republic of China.
Dan-Ni He *Department of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Laboratory, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, No. 58 Zhongshan Rd 2, Guangzhou, 510080, People's Republic of China.
Rui-Fang Lu *Department of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Laboratory, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, No. 58 Zhongshan Rd 2, Guangzhou, 510080, People's Republic of China.
Wen-Juan Tong *Department of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Laboratory, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, No. 58 Zhongshan Rd 2, Guangzhou, 510080, People's Republic of China.
Ying Wang *Department of Medical Ultrasound, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People's Republic of China.
Si QinDepartment of Medical Ultrasonics, the Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, People's Republic of China.
Rong WenDepartment of Medical Ultrasound, the First Affiliated Hospital of Guangxi Medical University, No 6 Shuangyong Road, Nanning, 530021, Guangxi, People's Republic of China.
Shao-Hong WuDepartment of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Laboratory, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, No. 58 Zhongshan Rd 2, Guangzhou, 510080, People's Republic of China.
Si-Min RuanDepartment of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Laboratory, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, No. 58 Zhongshan Rd 2, Guangzhou, 510080, People's Republic of China.
Guang-Jian LiuDepartment of Medical Ultrasonics, the Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, People's Republic of China.
Ming-De LuDepartment of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Laboratory, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, No. 58 Zhongshan Rd 2, Guangzhou, 510080, People's Republic of China.
Ming KuangDepartment of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Laboratory, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, No. 58 Zhongshan Rd 2, Guangzhou, 510080, People's Republic of China.
Wei WangDepartment of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Laboratory, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, No. 58 Zhongshan Rd 2, Guangzhou, 510080, People's Republic of China.
Mei-Qing ChengDepartment of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Laboratory, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, No. 58 Zhongshan Rd 2, Guangzhou, 510080, People's Republic of China. chengmq@mail.sysu.edu.cn.
Hong YangDepartment of Medical Ultrasound, the First Affiliated Hospital of Guangxi Medical University, No 6 Shuangyong Road, Nanning, 530021, Guangxi, People's Republic of China. yanghong@gxmu.edu.cn.
Li-Da ChenDepartment of Medical Ultrasonics, Ultrasomics Artificial Intelligence X-Laboratory, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, No. 58 Zhongshan Rd 2, Guangzhou, 510080, People's Republic of China. chenlda@mail.sysu.edu.cn.

Funding

National Natural Science Foundation of China 82171960National Natural Science Foundation of China 82272076National Natural Science Foundation of China 82371983Natural Science Foundation of Guangdong Province 2024A1515220047
6 · The paper itself

Abstract

BACKGROUND &

aimsTimely and accurate diagnosis of hepatocellular carcinoma (HCC) is essential for improving patient outcomes and guiding treatment. This multicenter study aimed to optimize the diagnostic workflow for HCC through a step-wise combination of CT/MRI and contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS).

methodsThis was a multicenter, retrospective analysis of prospectively recruited high-risk HCC participants with liver observations from 4 institutions, between January 2017 and December 2021. These participants initially underwent CT/MRI followed by CEUS, with observations categorized according to CT/MRI/CEUS LI-RADS. Three step-wise diagnostic strategies were evaluated, starting with CT/MRI and followed by CEUS, and compared to CT/MRI LI-RADS alone. Performance metrics included AUC, accuracy, sensitivity, specificity, PPV, and NPV, using pathology or over one year of follow-up as standards. The impact on clinical decisions was measured by false-negative, false-positive, and biopsy rates.

resultsOf 1264 participants, 874 (69%) were confirmed as HCC. The step-wise strategies outperformed CT/MRI LI-RADS. Strategy-3, which involved subsequent CEUS for CT/MRI LR-3/4 observations, significantly improved sensitivity (88.8% vs. 79.9%, P < 0.001) while maintaining comparable specificity (88.2% vs. 91.3%, P > 0.05). Strategy-3 reduced biopsy rate (31.5-22.4%, P = 0.028) and decreased false-negative rate (20.1-11.2%, P < 0.001). Additionally, 96% (55/57) of CT/MRI LR-3 and 97% (77/79) of CT/MRI LR-4 observations were accurately diagnosed and treated as HCC, with 61% (74/121) of CT/MRI LR-4 observations avoiding biopsy with CEUS-assisted.

conclusionA step-wise approach using CT/MRI followed by CEUS for LR-3/4 observations improved the diagnostic performance and further refined clinical decision-making in HCC.

trial registrationClinical Trial Registration Number: ChiCTR-DDD-16010089.

Indexed as

Carcinoma, HepatocellularContrast MediaLiver NeoplasmsMagnetic Resonance ImagingTomography, X-Ray ComputedAgedFemaleHumansMaleMiddle AgedRetrospective StudiesSensitivity and SpecificityUltrasonographyContrast MediaBiopsyComputed tomographyContrast-enhanced ultrasoundHepatocellular carcinomaMagnetic resonance imaging

Identifiers

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Registered trials

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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.