Evidence map›Paper›PMID 32107603›Full record

ArticleEuropean radiology2020

Liver Imaging Reporting and Data System (LI-RADS) v2018: diagnostic value of ancillary features favoring malignancy in hypervascular observations ≥ 10 mm at intermediate (LR-3) and high probability (LR-4) for hepatocellular carcinoma.

Roberto Cannella, Federica Vernuccio, Hersh Sagreiya, Kingshuk Roy Choudhury, Negaur Iranpour, Daniele Marin, Alessandro Furlan

Abstract readMulticenter Study
PubMed Publisher
In one paragraph

Article in European radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 2 pooled it
2.3field-weighted citation impact, top 11% 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

25 citing papers in PubMed, 2 syntheses or guidelines pooled it, 26 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

7 authors at 3 institutions in 3 countries.

Roberto CannellaSection of Radiology - BiND, University Hospital "Paolo Giaccone", Via del Vespro 127, 90127, Palermo, Italy.
Federica VernuccioSection of Radiology - BiND, University Hospital "Paolo Giaccone", Via del Vespro 127, 90127, Palermo, Italy.
Hersh SagreiyaDepartment of Radiology, Hospital of University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, 190104, USA.
Kingshuk Roy ChoudhuryDepartment of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC, USA.
Negaur IranpourDepartment of Radiology, University of Pittsburgh School of Medicine, 200 Lothrop Street, Pittsburgh, PA, 15213, USA.
Daniele MarinDepartment of Radiology, Duke University Medical Center, Durham, NC, USA.
Alessandro FurlanDepartment of Radiology, University of Pittsburgh School of Medicine, 200 Lothrop Street, Pittsburgh, PA, 15213, USA. furlana@upmc.edu.
Duke Medical Center · USUniversity of Pittsburgh · USHospital of the University of Pennsylvania · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study was conducted in order to assess the diagnostic accuracy of LI-RADS v2018 ancillary features (AFs) favoring malignancy applied to LR-3 and LR-4 observations on gadoxetate-enhanced MRI.

methodsIn this retrospective dual-institution study, we included consecutive patients at high risk for hepatocellular carcinoma (HCC) imaged with gadoxetate disodium-enhanced MRI between 2009 and 2014 fulfilling the following criteria: (i) at least one LR-3 or LR-4 observation ≥ 10 mm; (ii) nonrim arterial phase hyperenhancement; and (iii) confirmation of benignity or malignancy by pathology or imaging follow-up. We compared the distribution of AFs between HCCs and benign observations and the diagnostic performance for the diagnosis of HCC using univariate and multivariate analyses. Significance was set at p value < 0.05.

resultsTwo hundred five observations were selected in 155 patients (108 M, 47 F) including 167 (81.5%) LR-3 and 38 (18.5%) LR-4. There were 126 (61.5%) HCCs and 79 (28.5%) benign lesions. A significantly larger number of AFs favoring malignancy were found in LR-3 and LR-4 lesions that progressed to HCC compared to benign lesions (p < 0.001 and p = 0.003, respectively). The most common AFs favoring malignancy in HCCs were hepatobiliary phase (HBP) hypointensity (p < 0.001), transitional phase hypointensity (p < 0.001), and mild-moderate T2 hyperintensity (p < 0.001). Sensitivity and specificity of AFs for the diagnosis of HCC ranged 0.8-76.2% and 86.1-100%, respectively. HBP hypointensity yielded the highest sensitivity but also the lowest specificity and was the only AF remaining independently associated with the diagnosis of HCC at multivariate logistic regression analysis (OR 14.83, 95% CI 5.81-42.76, p < 0.001).

conclusionsAmong all AFs, HBP hypointensity yields the highest sensitivity for the diagnosis of HCC. KEY POINTS: • LR-3 and LR-4 observations diagnosed as HCC have a significantly higher number of ancillary features favoring malignancy compared to observations proven to be benign. • The presence of three or more ancillary features favoring malignancy has a high specificity (96.2%) for the diagnosis of HCC. • Among all ancillary features favoring malignancy, hepatobiliary phase hypointensity yields the highest sensitivity, but also the lowest specificity for the diagnosis of HCC.

Indexed as

Carcinoma, HepatocellularContrast MediaFemaleGadolinium DTPAHumansLiver NeoplasmsMagnetic Resonance ImagingMaleMiddle AgedReproducibility of ResultsResearch DesignRetrospective StudiesContrast MediaGadolinium DTPAgadolinium ethoxybenzyl DTPACirrhosisHepatocellular carcinomaLiverMagnetic resonance imaging

Identifiers

PMID32107603
OpenAlexW3008264605

What OpenQuestion holds

Textmetadata
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.