Evidence map›Paper›PMID 33285682›Full record

Observational studyMedicine2020

Diagnosis value preoperative localization of insulinoma by diffusion-weighted imaging: A pilot study.

Li-Jun Chen, Yue-Dong Han, Ming Zhang

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in Medicine, 2020. 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
0.3field-weighted citation impact, top 38% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. 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

3 authors at 1 institution in 1 country.

Li-Jun ChenThe Department for Radiology, Gao Xin Hospital Xi'an.
Yue-Dong HanThe Department for Radiology, Gao Xin Hospital Xi'an.
Ming ZhangThe First Affiliated Hospital of Xi'an Jiao Tong University, Xi'an, ShannXi, China.
First Hospital of Xi'an · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Insulinoma is the most common functional neuroendocrine tumor that originates from the islet of beta cells. Insulinoma is usually an isolated benign tumor and small in size (<2 cm). Due to the small size of the lesion, it often leads to difficulty in clinical preoperative localization diagnosis. However, we have unexpectedly discovered that the diffusion-weighted-imaging (DWI) adds great value in the preoperative localization diagnosis of insulinoma in non-invasive examination technique.We verified using operative pathology data and retrospectively analyzed the clinical and imageology findings of 5 cases who reported to have an insulinoma. All the 5 cases underwent DWI examination, among non-contrast enhanced magnetic resonance imaging (MRI) in 1 case, contrast-enhanced MRI in 4 cases.Five cases of DWI showed a nodular high signal <1.3 cm with pancreatic tail in 3 cases, pancreatic neck, and pancreatic head in 1 case each, respectively. Non-contrast enhanced MRI showed suspicious abnormal signals in the tail of the pancreas were detected in 1 case. MRI enhanced scans presented 2 cases with abnormal enhancement in the arterial phase and 2 cases without abnormal enhancement in arterial phase. Also, 3 cases showed mild persistence enhanced in the portal venous phase and delayed phase. However, 1 case remained normal in the portal venous phase and the delay period.DWI examination has high clinical value in the localization diagnosis of insulinoma and thus it can be used as a routine examination for preoperative localization diagnosis.

Indexed as

AdultDiffusion Magnetic Resonance ImagingFemaleHumansInsulinomaMaleMiddle AgedPancreatic NeoplasmsPreoperative PeriodRetrospective Studies

Identifiers

PMID33285682
PMCPMC7717785
OpenAlexW3112595993

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.