Evidence map›Paper›PMID 37869332›Full record

ArticleQuantitative imaging in medicine and surgery2023

Differentiating mass-forming intrahepatic cholangiocarcinoma from atypical hepatocellular carcinoma using Gd-EOB-DTPA-enhanced magnetic resonance imaging combined with serum markers in at-risk patients with hepatitis B virus.

Dingsheng Han, Yalin Li, Xu He, Jiacheng Zhang, Yanru Zhou, Jiajia Zhang, Lan Zhang

Open access · diamondAbstract read
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Article in Quantitative imaging in medicine and surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.2field-weighted citation impact, top 12% 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

6 citing papers in PubMed, 7 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 2 countries.

Dingsheng HanImaging and Nuclear Medicine Department, Henan University of Chinese Medicine, Zhengzhou, China.
Yalin LiImaging and Nuclear Medicine Department, Henan University of Chinese Medicine, Zhengzhou, China.
Xu HeImaging and Nuclear Medicine Department, Henan University of Chinese Medicine, Zhengzhou, China.
Jiacheng ZhangImaging and Nuclear Medicine Department, Henan University of Chinese Medicine, Zhengzhou, China.
Yanru ZhouDepartment of MRI, the First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, China.
Jiajia ZhangDepartment of Radiology, Gold Coast University Hospital, School of Medicine, Bond University, Gold Coast, Queensland, Australia.
Lan ZhangDepartment of MRI, the First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, China.
First Affiliated Hospital of Henan University · CNBond University · AUHenan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The precise differentiation of intrahepatic cholangiocarcinoma (ICC) from atypical hepatocellular carcinoma (HCC) is vital for treatment strategy and prognostic prediction. In clinical practice, nearly 40% of HCCs demonstrate atypical manifestations, particularly HCCs with rim arterial phase hyperenhancement (APHE), which is challenging to differentiate from mass-forming ICC. Thus, we aimed to develop a diagnostic regimen of gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) contrast-enhanced magnetic resonance imaging (MRI) combined with serum tumor markers in differentiating mass-forming ICC from atypical HCC in at-risk patients with the hepatitis B virus (HBV). Methods: This study enrolled 129 patients with pathologically proven mass-forming ICCs (n=53) and atypical HCCs (n=76) who had undergone preoperative Gd-EOB-DTPA contrast-enhanced MRI. The clinical data and imaging findings were analyzed. Univariate and multivariate logistic analyses were performed to identify the independent predictors for differentiating mass-forming ICCs from atypical HCCs. The diagnostic performance was evaluated using receiver operating characteristic (ROC) curves, and DeLong test was used to compare the areas under curves of all independent predictors. Results: Univariate logistic regression analysis revealed normal alpha fetoprotein (AFP), elevated carbohydrate antigen 19-9 (CA19-9) level, elevated carcinoma embryonic antigen (CEA) level, central hyperintensity on T2-weighted imaging (T2WI), central hypointensity on T2WI, and targetoid sign on hepatobiliary phase (HBP) and targetoid restriction on diffusion-weighted imaging (DWI) were more likely to be significant predictors favoring mass-forming ICCs (all P values <0.05). In contrast, multifocal hyperintensity on T2WI and capsule sign were more frequently seen in patients with atypical HCC (all P values <0.05). Multivariate analysis revealed normal AFP, elevated CA19-9 level, targetoid sign on HBP, and targetoid restriction on DWI (all P=0.001) were independent predictors for differentiating mass-forming ICCs from atypical HCCs; DeLong test showed that the area under curve (AUC) increased to 0.949 when the above predictors were combined (all P values <0.05), and the sensitivity, specificity, and accuracy of the combined independent predictors were 88.7%, 93.4%, and 91.5%, respectively. Conclusions: A diagnostic regimen integrating tumor markers (AFP, CA19-9) and imaging biomarkers (targetoid restriction on DWI and/or targetoid sign on HBP) using Gd-EOB-DTPA-enhanced MRI could help to differentiate mass-forming ICCs from atypical HCCs and achieve high diagnostic performance of mass-forming ICCs in at-risk patients with the HBV. Keywords: Mass-forming intrahepatic cholangiocarcinoma (mass-forming ICC); atypical hepatocellular carcinoma (atypical HCC); magnetic resonance imaging (MRI); gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA); hepatobiliary phase (HBP).

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PMID37869332
PMCPMC10585505
OpenAlexW4387023384

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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.