Evidence map›Paper›PMID 33389037›Full record

ArticleEuropean radiology2021

Retrospective analysis of current guidelines for hepatocellular carcinoma diagnosis on gadoxetic acid-enhanced MRI in at-risk patients.

So Hyun Park, Young Sup Shim, Bohyun Kim, So Yeon Kim, Yun Soo Kim, Jimi Huh, Ji Hyun Park, Kyung Won Kim, Seung Soo Lee

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In one paragraph

Article in European radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 3 pooled it
–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

17 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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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

9 authors.

So Hyun Park *Department of Radiology, Gil Medical Center, Gachon University College of Medicine, Incheon, Korea.
Young Sup Shim *Department of Radiology, Gil Medical Center, Gachon University College of Medicine, Incheon, Korea.
Bohyun KimDepartment of Radiology, Ajou University Hospital, Ajou University School of Medicine, Suwon, Korea. kbh@catholic.ac.kr.ORCID http://orcid.org/0000-0003-1157-415X
So Yeon KimDivision of Abdominal Radiology, Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
Yun Soo KimDepartment of Internal Medicine, Gil Medical Center, Gachon University College of Medicine, Incheon, Korea.
Jimi HuhDepartment of Radiology, Ajou University Hospital, Ajou University School of Medicine, Suwon, Korea.
Ji Hyun ParkOffice of Biostatistics, Ajou Research Institute for Innovative Medicine, Ajou University Hospital, Suwon, Korea.
Kyung Won KimDivision of Abdominal Radiology, Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
Seung Soo LeeDivision of Abdominal Radiology, Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.

Funding

Gachon University research fund of 2017 GCU-2017-5256National Research Foundation of Korea 2017R1A2B3011475
6 · The paper itself

Abstract

objectiveTo evaluate and compare the diagnostic performance of the updated HCC guidelines using gadoxetic acid-enhanced MRI.

methodsIn this study, patients at risk of HCC who underwent gadoxetic acid-enhanced MRI following US/CT surveillance were retrospectively recruited from 3 centers. Three radiologists independently evaluated hepatic nodule imaging features relevant to the diagnostic criteria outlined in each guideline. Per-lesion sensitivity, specificity, and accuracy were compared between guidelines using logistic regression with a generalized estimating equation. Inter-observer agreements on imaging features were determined using Fless κ statistics.

resultsAltogether, 447 nodules (310 HCCs, 20 combined hepatocellular-cholangiocarcinomas, 2 cholangiocarcinomas, and 115 benign entities) measuring 1-3 cm from 386 patients were assessed. The KLCA-NCC and APASL guidelines showed the highest sensitivity (82.3-90.6%, p < .001) and accuracy (83.9-88.6%) among the five guidelines. The OPTN/UNOS guideline showed the highest specificity (94.9-97.1%), followed by the AASLD/LI-RADS, EASL, KLCA-NCC, and APASL guidelines, with significant difference only with the APASL guideline. The diagnostic performance of the updated AASLD/LI-RADS and EASL guidelines and of the KLCA-NCC and APASL guidelines was comparable (p > .05). Inter-observer agreement was substantial to almost perfect (κ = 0.73-0.87).

conclusionsFor the diagnosis of HCC using gadoxetic acid-enhanced MRI, the KLCA-NCC and APASL guidelines showed the highest sensitivity and accuracy. The OPTN/UNOS guideline showed the highest specificity. Acknowledging their relative strengths and weaknesses could help adapt the diagnostic criteria according to the clinical context. KEY POINTS: • APASL and KLCA-NCC provided significantly the highest sensitivity and accuracy, followed by AASLD/LI-RADS and EASL in an endemic area for hepatitis B. • OPTN/UNOS showed the highest specificity, followed by AASLD/LI-RADS, EASL, KLCA-NCC, and APASL guidelines, with significant difference only with APASL. • Broadened definition of arterial hyperenhancement, washout, and the size of the lesion eligible to apply diagnostic criteria may improve the diagnostic performance for HCC in an endemic area for hepatitis B.

Indexed as

Bile Duct NeoplasmsCarcinoma, HepatocellularLiver NeoplasmsBile Ducts, IntrahepaticContrast MediaGadolinium DTPAHumansMagnetic Resonance ImagingRetrospective StudiesSensitivity and SpecificityContrast MediaGadolinium DTPAgadolinium ethoxybenzyl DTPAGuidelineHepatocellular carcinomaLiverMagnetic resonance imaging

Identifiers

PMID33389037

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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.