Evidence map›Paper›PMID 39971299›Full record

ArticleInternal medicine (Tokyo, Japan)2025

Hepatic Sarcoidosis Mimicking a Metastatic Tumor.

Naohiro Nakamura, Yoshiki Matsuno, Kazunori Aoi, Hisashi Kosaka, Sanshiro Kobayashi, Yu Takahashi, Tomomitsu Tahara, Yuri Noda, Koji Tsuta, Makoto Naganuma

Abstract readCase Reports
In one paragraph

Article in Internal medicine (Tokyo, Japan), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Naohiro NakamuraThird Department of Internal Medicine, Kansai Medical University, Japan.
Yoshiki MatsunoThird Department of Internal Medicine, Kansai Medical University, Japan.
Kazunori AoiThird Department of Internal Medicine, Kansai Medical University, Japan.
Hisashi KosakaDepartment of Surgery, Kansai Medical University, Japan.
Sanshiro KobayashiThird Department of Internal Medicine, Kansai Medical University, Japan.
Yu TakahashiThird Department of Internal Medicine, Kansai Medical University, Japan.
Tomomitsu TaharaThird Department of Internal Medicine, Kansai Medical University, Japan.
Yuri NodaDepartment of Pathology, Kansai Medical University, Japan.
Koji TsutaDepartment of Pathology, Kansai Medical University, Japan.
Makoto NaganumaThird Department of Internal Medicine, Kansai Medical University, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although the liver is often involved in sarcoidosis, the majority of patients are asymptomatic and have a normal liver function; therefore, hepatic sarcoidosis may sometimes not be recognized in clinical practice. Radiologically, most hepatic nodules show hypoenhancement on contrast-enhanced computed tomography or magnetic resonance imaging (MRI) and they are hypointense across all sequences of MRI. In this case, hepatic nodules were slightly hyperintense on T2-weighted images and contrasted from the early phases on gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid. We faced difficulties in distinguishing hepatic sarcoidosis from metastatic liver tumors with concurrent duodenal adenocarcinomas. Consequently, this case was diagnosed based on the pathological findings from a laparoscopic lateral segment hepatectomy.

Indexed as

Liver DiseasesLiver NeoplasmsSarcoidosisAdenocarcinomaDiagnosis, DifferentialDuodenal NeoplasmsHepatectomyHumansMagnetic Resonance ImagingTomography, X-Ray Computedduodenal adenocarcinomahepatic sarcoidosismetastatic liver tumors

Identifiers

PMID39971299
PMCPMC12425587

What OpenQuestion holds

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Registered trials

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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.