Evidence map›Paper›PMID 34773467›Full record

ArticleAbdominal radiology (New York)2022

Can modified LI-RADS increase the sensitivity of LI-RADS v2018 for the diagnosis of 10-19 mm hepatocellular carcinoma on gadoxetic acid-enhanced MRI?

Sidong Xie, Yao Zhang, Jingbiao Chen, Ting Jiang, Weimin Liu, Dailin Rong, Lin Sun, Linqi Zhang, Bingjun He, Jin Wang

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In one paragraph

Article in Abdominal radiology (New York), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 3 pooled it
3.0field-weighted citation impact, top 7% 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

12 citing papers in PubMed, 3 syntheses or guidelines pooled it, 29 citations in OpenAlex.

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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

10 authors at 1 institution in 1 country.

Sidong Xie *Department of Radiology, The Third Affiliated Hospital, Sun Yat-sen University (SYSU), No 600, Tianhe Road, Guangzhou, 510630, Guangdong, People's Republic of China.
Yao Zhang *Department of Radiology, The Third Affiliated Hospital, Sun Yat-sen University (SYSU), No 600, Tianhe Road, Guangzhou, 510630, Guangdong, People's Republic of China.
Jingbiao ChenDepartment of Radiology, The Third Affiliated Hospital, Sun Yat-sen University (SYSU), No 600, Tianhe Road, Guangzhou, 510630, Guangdong, People's Republic of China.
Ting JiangDepartment of Radiology, The Third Affiliated Hospital, Sun Yat-sen University (SYSU), No 600, Tianhe Road, Guangzhou, 510630, Guangdong, People's Republic of China.
Weimin LiuDepartment of Radiology, The Third Affiliated Hospital, Sun Yat-sen University (SYSU), No 600, Tianhe Road, Guangzhou, 510630, Guangdong, People's Republic of China.
Dailin RongDepartment of Radiology, The Third Affiliated Hospital, Sun Yat-sen University (SYSU), No 600, Tianhe Road, Guangzhou, 510630, Guangdong, People's Republic of China.
Lin SunDepartment of Radiology, The Third Affiliated Hospital, Sun Yat-sen University (SYSU), No 600, Tianhe Road, Guangzhou, 510630, Guangdong, People's Republic of China.
Linqi ZhangDepartment of Radiology, The Third Affiliated Hospital, Sun Yat-sen University (SYSU), No 600, Tianhe Road, Guangzhou, 510630, Guangdong, People's Republic of China.
Bingjun HeDepartment of Radiology, The Third Affiliated Hospital, Sun Yat-sen University (SYSU), No 600, Tianhe Road, Guangzhou, 510630, Guangdong, People's Republic of China.
Jin WangDepartment of Radiology, The Third Affiliated Hospital, Sun Yat-sen University (SYSU), No 600, Tianhe Road, Guangzhou, 510630, Guangdong, People's Republic of China. wangjin3@mail.sysu.edu.cn.ORCID http://orcid.org/0000-0002-7956-9579
Sun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo evaluate whether the Liver Imaging Reporting and Data System (LI-RADS) v2018 LR-5 criteria can be modified to increase sensitivity without reducing specificity for diagnosing 10-19 mm hepatocellular carcinoma (HCC) on gadoxetic acid-enhanced magnetic resonance imaging (MRI).

methodsA total of 133 high-risk consecutive patients with 174 small observations (10-19 mm) detected on gadoxetic acid-enhanced MRI were retrospectively studied. LI-RADS MRI major features (MFs) and ancillary features (AFs) were reviewed by two independent radiologists in consensus. Observations were categorized using LI-RADS v2018 MFs. Independently significant AFs were identified through logistic regression analysis. Upgraded LR-5 criteria were developed by combining independently significant AFs with MFs of LR-3 or LR-4 v2018. The sensitivity and specificity of the new diagnostic criteria were compared with those of LR-5 v2018 using McNemar's test.

resultsThree of the AFs favoring malignancy [mild-moderate T2 hyperintensity, transitional phase (TP) hypointensity and fat in mass] were independently significant features for diagnosing 10-19 mm HCC. The upgraded LR-5 criteria (mLI-RADS VII: LR-4 + mild-moderate T2 hyperintensity/TP hypointensity or LR-3 + fat in mass) yielded a significantly greater sensitivity than that of the LR-5 v2018 criteria (70.4% vs 55.1%; p < 0.001), whereas the specificity was not significantly different (94.7% vs 98.7%, p = 0.250).

conclusionsIndependently significant AFs may be used to upgrade an observation from LR-3/LR-4 to LR-5, which can improve the sensitivity without impairing the specificity for diagnosing 10-19 mm HCC on gadoxetic acid-enhanced MRI.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsContrast MediaGadolinium DTPAHumansMagnetic Resonance ImagingRetrospective StudiesSensitivity and SpecificityContrast MediaGadolinium DTPAgadolinium ethoxybenzyl DTPADiagnosisGadoxetic acidLiver neoplasmsMagnetic resonance imagingSensitivity and specificity

Identifiers

PMID34773467
OpenAlexW3214535025

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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.