Evidence map›Paper›PMID 38357604›Full record

ReviewJournal of biomedical physics & engineering2024

Evidence Supporting Diagnostic Value of Liver Imaging Reporting and Data System for CT- and MR Imaging-based Diagnosis of Hepatocellular Carcinoma: A Systematic Review and Meta-analysis.

Hayder Suhail Najm Alareer, Arvin Arian, Maryam Fotouhi, Hayder Jasim Taher, Ayoob Dinar Abdullah

Open access · goldAbstract readReview
In one paragraph

Review in Journal of biomedical physics & engineering, 2024. 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, top 67% 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

1 citing paper in PubMed, 0 citations in OpenAlex.

  1. 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

5 authors at 3 institutions in 2 countries.

Hayder Suhail Najm AlareerDepartment of Radiology, College of Health and Medical Technology, Al-Ayen University, Thi-Qar, 64001, Iraq.
Arvin ArianCancer Institute ADIR, Tehran University of Medical Sciences (TUMS), Tehran, Iran.
Maryam FotouhiQuantitative MR Imaging and Spectroscopy Group (QMISG), Research Centre for Molecular and Cellular Imaging (RCMCI), Advanced Medical Technologies and Equipment Institute (AMTEI), Tehran University of Medical Sciences (TUMS), Tehran, Iran.
Hayder Jasim TaherDepartment of Radiology, Hilla University College, Babylon, Iraq.
Ayoob Dinar AbdullahDepartment of Radiology Technology, Al-Manara College for Medical Sciences, Missan, Iraq.
Tehran University of Medical Sciences · IRThi Qar University · IQUniversity of Babylon · IQ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Based on the Liver Imaging Data and Reporting System (LI-RADS) guidelines, Hepatocellular Carcinoma (HCC) can be diagnosed using imaging criteria in patients at risk of HCC. Objective: This study aimed to assess the diagnostic value of LI-RADS in high-risk patients with HCC. Material and Methods: This systematic review is conducted on international databases, including Google Scholar, Web of Science, PubMed, Embase, PROQUEST, and Cochrane Library, with appropriate keywords. Using the binomial distribution formula, the variance of each study was calculated, and all the data were analyzed using STATA version 16. The pooled sensitivity and specificity were determined using a random-effects meta-analysis approach. Also, we used the chi-squared test and I Results: The pooled sensitivity was estimated at 0.80 (95% CI 0.76-0.84). According to different types of Liver Imaging Reporting and Data Systems (LI-RADS), the highest pooled sensitivity was in version 2018 (0.83 (95% CI 0.79-0.87) (I Conclusion: LI-RADS can assist radiologists in achieving the required sensitivity and specificity in high-risk patients suspected to have HCC. Therefore, this strategy can serve as an appropriate tool for identifying HCC.

Indexed as

CarcinomaCTHepatocellularLI-RADSMagnetic Resonance Imaging

Identifiers

PMID38357604
PMCPMC10862115
OpenAlexW4388823859

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.