Evidence map›Paper›PMID 29245304›Full record

ReviewMedicine2017

Computed tomography imaging features of hepatic perivascular epithelioid cell tumor: A case report and literature review.

Xu Han, Mei-Yu Sun, Jing-Hong Liu, Xiao-Yan Zhang, Meng-Yao Wang, Rui Fan, Sahrish Qamar

Open access · goldAbstract readCase ReportsReview
In one paragraph

Review in Medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.6field-weighted citation impact, top 29% 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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Review
  5. Article
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 4 institutions in 1 country.

Xu HanThe First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning Cancer Hospital of Peking University, Beijing The Chinese University of Hong Kong, Shatin, Hong Kong, China.
Mei-Yu Sun
Jing-Hong Liu
Xiao-Yan Zhang
Meng-Yao Wang
Rui Fan
Sahrish Qamar
First Affiliated Hospital of Dalian Medical University · CNChinese University of Hong Kong · CNDalian Medical University · CNPeking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

rationalePerivascular epithelioid cell tumor (PEComa) is a rare tumor which is most frequently found in uterus. The tumor arising from liver is extremely uncommon. PATIENT CONCERNS: A 36-year-old female with abdominal distention, cramps, and low-grade fever for over 15 days. The patient had a history of gastric adenocarcinoma with ovarian, celiac lymph nodes, and retroperitoneal lymph nodes metastases. DIAGNOSES: Computed tomography (CT) imaging demonstrated an ill-defined heterogeneous hypo-dense mass in segment 8 (S8) of the liver. Contrast-enhanced CT imaging showed marked enhancement in arterial phase, mild-to-moderate enhancement in portal and equilibrium phases. Tumor-feeding artery was demonstrated from the right hepatic artery by the three-dimensional reconstruction images. Biopsy was performed, and a diagnosis of PEComa was rendered.

interventionsNo intervention for this tumor before liver biopsy. LESSONS: We present a rare case of hepatic PEComa. The information we provided is useful for summarizing the CT features of this kind of tumors. It should be included in differential diagnoses from common hypervascular neoplasms of liver. The final diagnosis is established on histopathological and immunohistochemical studies that are the "gold standard."

Indexed as

Contrast MediaAdultFemaleHumansLiverLiver NeoplasmsPerivascular Epithelioid Cell NeoplasmsTomography, X-Ray ComputedContrast Media

Identifiers

PMID29245304
PMCPMC5728919
OpenAlexW2772534355

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.