Evidence map›Paper›PMID 28538050›Full record

ReviewTransplantation2017

Molecular Imaging of Acute Cardiac Transplant Rejection: Animal Experiments and Prospects.

Yihan Chen, Li Zhang, Jinfeng Liu, Pingyu Zhang, Xiaoyuan Chen, Mingxing Xie

Abstract readReview
In one paragraph

Review in Transplantation, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Article
  6. Review
  7. Application of animal and human PET in cardiac research.American journal of cardiovascular disease · 2018
    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

6 authors.

Yihan Chen1 Department of Ultrasound, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. 2 Laboratory of Molecular Imaging and Nanomedicine (LOMIN), National Institute of Biomedical Imaging and Bioengineering (NIBIB), National Institutes of Health (NIH), Bethesda, MD.
Li Zhang
Jinfeng Liu
Pingyu Zhang
Xiaoyuan Chen
Mingxing Xie

Funding

Laboratory of Molecular Imaging and NanomedicineZIAEB000073 · NIBIB · NATIONAL INSTITUTE OF BIOMEDICAL IMAGING AND BIOENGINEERING · PI CHEN, XIAOYUAN · 2010 to 2020
$32.8M
Intramural NIH HHS Z99 EB999999Intramural NIH HHS ZIA EB000073
6 · The paper itself

Abstract

Acute rejection (AR) remains the biggest challenge during the first year after heart transplantation despite advances in immunosuppressive therapy. The early detection and curbing of AR are crucial to the survival of transplant recipients. However, as the criterion standard for AR, endomyocardial biopsy has several limitations because of its inherent invasiveness and morbidity. Traditional imaging techniques, such as echocardiography and cardiac magnetic resonance imaging, are of certain value for AR, but their diagnostic criteria and accuracy remain in question. Molecular imaging sheds new light on AR diagnosis because it can provide information about gene expression and the location of molecules and cells. This article reviews the latest research and applications of several typical modalities of molecular imaging used in AR and discusses their advantages and disadvantages.

Indexed as

Cardiac Imaging TechniquesAcute DiseaseAnimalsContrast MediaEarly DiagnosisEchocardiographyGene Expression RegulationGenetic MarkersGraft RejectionHeart TransplantationHumansMagnetic Resonance ImagingMolecular ImagingOptical ImagingPredictive Value of TestsRadiopharmaceuticalsContrast MediaGenetic MarkersRadiopharmaceuticals

Identifiers

PMID28538050
PMCPMC5568929

What OpenQuestion holds

Textmetadata
LicenceTDM
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.