Evidence map›Paper›PMID 36017022›Full record

ArticleContrast media & molecular imaging2022

The Clinical Diagnostic Value of F-FDG PET/CT Combined with MRI in Pancreatic Cancer.

Xinyan Liu, Yi Ren, Jianying Wang, Xiujin Yang, Li Lu

Open access · hybridAbstract read
In one paragraph

Article in Contrast media & molecular imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 33% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Review
  3. Observational
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.

Xinyan LiuChongqing Universal Hongling Medical Imaging Diagnostic Center, Yuzhong, Chongqing 400000, China.ORCID 0000-0002-6339-7688
Yi RenChongqing Universal Hongling Medical Imaging Diagnostic Center, Yuzhong, Chongqing 400000, China.
Jianying WangChongqing Universal Hongling Medical Imaging Diagnostic Center, Yuzhong, Chongqing 400000, China.
Xiujin YangChongqing Universal Hongling Medical Imaging Diagnostic Center, Yuzhong, Chongqing 400000, China.
Li LuChongqing Universal Hongling Medical Imaging Diagnostic Center, Yuzhong, Chongqing 400000, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pancreatic cancer is a common gastrointestinal tumor with increasing morbidity and mortality, and it is difficult to differentiate it from chronic mass pancreatitis. F-18-fluorodeoxyglucose positron emission tomography/computed tomography (F-FDG PET/CT) can be used for diagnosis of pancreatic cancer, staging, radiotherapy planning, evaluation of efficacy and recurrence, and differentiation from posttreatment fibrosis but the sensitivity and specificity of diagnosis of chronic pancreatitis are poor. Magnetic resonance imaging (MRI) not only shows the morphology, location, and size of organs and lesions but also has the advantages of low radiation, high soft tissue contrast, and multiparameter imaging, which can help determine the nature of occupying pancreatic lesions. In this study, the watershed algorithm (WA) was used to segment the abdominal images to extract images of pancreatic cancer cells and to compare the value of F-FDG PET/CT combined with MRI in the diagnosis of pancreatic occupying lesions.

Indexed as

Fluorodeoxyglucose F18Pancreatic NeoplasmsDiagnosis, DifferentialHumansMagnetic Resonance ImagingPositron-Emission TomographyPositron Emission Tomography Computed TomographyRadiopharmaceuticalsSensitivity and SpecificityTomography, X-Ray ComputedFluorodeoxyglucose F18Radiopharmaceuticals

Identifiers

PMID36017022
PMCPMC9371826
OpenAlexW4289782754

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.