Evidence map›Paper›PMID 40502502›Full record

ArticleWorld journal of gastrointestinal surgery2025

Diagnostic challenges and radiological insights of rare hepatic perivascular epithelioid cell tumor: A case report and review of the literature.

Jun-An Zhou, Zheng-Chao Fan, Ru-Jun Zheng, Qin-Xi Guo, Song Su

Abstract readCase Reports
In one paragraph

Article in World journal of gastrointestinal surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. Review
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

5 authors.

Jun-An ZhouDepartment of General Surgery (Hepatobiliary Surgery), The Affiliated Hospital of Southwest Medical University, Luzhou 646000, Sichuan Province, China.
Zheng-Chao FanDepartment of Ultrasound, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, Sichuan Province, China.
Ru-Jun ZhengDepartment of General Surgery (Hepatobiliary Surgery), The Affiliated Hospital of Southwest Medical University, Luzhou 646000, Sichuan Province, China.
Qin-Xi GuoDepartment of Pathology, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, Sichuan Province, China.
Song SuDepartment of General Surgery (Hepatobiliary Surgery), The Affiliated Hospital of Southwest Medical University, Luzhou 646000, Sichuan Province, China. 13882778554@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHepatic perivascular epithelioid cell tumor (PEComa) is an extremely rare neoplasm that is often difficult to diagnose due to its nonspecific clinical and radiological features. This case emphasizes the importance of imaging and histopathological examination in distinguishing PEComa from other liver tumors, and the necessity of early intervention. CASE SUMMARY: A 36-year-old woman presented with a liver mass discovered during a routine physical examination. Initially diagnosed as focal nodular hyperplasia based on contrast-enhanced computed tomography, she declined surgical intervention. Two years later, re-examination revealed an approximately 60% increase in the size of the mass and suggested the possibility of hepatocellular carcinoma. She subsequently underwent surgical resection. Postoperative histopathological and immunohistochemical analysis revealed positivity for HMB-45 and Melan-A, confirming the diagnosis of hepatic PEComa. A 13-month follow-up revealed no recurrence or metastasis.

conclusionHepatic PEComa requires a combination of radiological and immunohistochemical evaluation for accurate diagnosis. This case highlights the importance of early surgical intervention and regular follow-up to monitor for recurrence or metastasis.

Indexed as

Case reportComputed tomographyDiagnosisLiver tumorPerivascular epithelioid cell tumorUltrasound

Identifiers

PMID40502502
PMCPMC12149916

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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.