Evidence map›Paper›PMID 33912456›Full record

ArticleFrontiers in oncology2021

Diagnosis of Non-Hepatocellular Carcinoma Malignancies in Patients With Risks for Hepatocellular Carcinoma: CEUS LI-RADS Versus CT/MRI LI-RADS.

Yi-Xin Hu, Jing-Xian Shen, Jing Han, Si-Yue Mao, Ru-Shuang Mao, Qing Li, Fei Li, Zhi-Xing Guo, Jian-Hua Zhou

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
2.7field-weighted citation impact, top 10% of its field
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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. 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

9 authors at 3 institutions in 1 country.

Yi-Xin HuDepartment of Ultrasound, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, and Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
Jing-Xian ShenImage and Minimally Invasive Intervention Center, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, and Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
Jing HanDepartment of Ultrasound, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, and Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
Si-Yue MaoImage and Minimally Invasive Intervention Center, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, and Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
Ru-Shuang MaoDepartment of Ultrasound, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, and Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
Qing LiDepartment of Ultrasound, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, and Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
Fei LiDepartment of Ultrasound, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, and Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
Zhi-Xing GuoDepartment of Ultrasound, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, and Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
Jian-Hua ZhouDepartment of Ultrasound, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, and Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
Sun Yat-sen University Cancer Center · CNState Key Laboratory of Oncology in South ChinaSun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveData regarding direct comparison of contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS) and Computed Tomography/Magnetic Resonance Imaging (CT/MR) LI-RADS in diagnosis of non-hepatocelluar carcinoma (non-HCC) malignancies remain limited. Our study aimed to compare the diagnostic performance of the CEUS LI-RADS version 2017 and CT/MRI LI-RADS v2018 for diagnosing non-HCC malignancies in patients with risks for HCC. MATERIALS AND

methodsIn this retrospective study, 94 liver nodules pathologically-confirmed as non-HCC malignancies in 92 patients at risks for HCC from January 2009 to December 2018 were enrolled. The imaging features and the LI-RADS categories on corresponding CEUS and CT/MRI within 1 month were retrospectively analyzed according to the ACR CEUS LI-RADS v2017 and ACR CT/MRI LI-RADS v2018 by two radiologists in consensus for each algorithm. The sensitivity of LR-M category, inter-reader agreement and inter-modality agreement was compared between these two standardized algorithms.

resultsNinety-four nodules in 92 patients (mean age, 54 years ± 10 [standard deviation] with 65 men [54 years ± 11] and 27 women [54 years ± 8]), including 56 intrahepatic cholangiocarcinomas, 34 combined hepatocellular cholangiocarcinomas, two adenosquamous carcinomas of the liver, one primary hepatic neuroendocrine carcinoma and one hepatic undifferentiated sarcoma were included. On CEUS, numbers of lesions classified as LR-3, LR-4, LR-5 and LR-M were 0, 1, 10 and 83, and on CT/MRI, the corresponding numbers were 3, 0, 14 and 77. There was no significant difference in the sensitivity of LR-M between these two standardized algorithms (88.3% of CEUS vs 81.9% of CT/MRI, p = 0.210). Seventy-seven lesions (81.9%) were classified as the same LI-RADS categories by both standardized algorithms (five for LR-5 and 72 for LR-M, kappa value = 0.307). In the subgroup analysis for ICC and CHC, no significant differences were found in the sensitivity of LR-M category between these two standardized algorithms (for ICC, 94.6% of CEUS vs 89.3% of CT/MRI, p = 0.375; for CHC, 76.5% of CEUS vs 70.6% of CT/MRI, p = 0. 649).

conclusionCEUS LI-RADS v2017 and CT/MRI LI-RADS v2018 showed similar value for diagnosing non-HCC primary hepatic malignancies in patients with risks.

Indexed as

computed tomographycontrast-enhanced ultrasoundliver imaging reporting and data systemmagnetic resonance imagingnon-hepatocelluar carcinoma malignancies

Identifiers

PMID33912456
PMCPMC8074676
OpenAlexW3155754213

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.