Evidence map›Paper›PMID 31783595›Full record

ReviewCancers2019

Imaging of Preclinical Endometrial Cancer Models for Monitoring Tumor Progression and Response to Targeted Therapy.

Heidi Espedal, Tina Fonnes, Kristine E Fasmer, Camilla Krakstad, Ingfrid S Haldorsen

Open access · goldAbstract readReview
In one paragraph

Review in Cancers, 2019. 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
1.6field-weighted citation impact, top 16% 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

7 citing papers in PubMed, 14 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Feasibility and utility of MRI and dynamicJournal of translational medicine · 2021
    Article
  6. Article
  7. 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

5 authors at 1 institution in 1 country.

Heidi EspedalDepartment of Clinical Medicine, University of Bergen, 5021 Bergen, Norway.ORCID 0000-0002-0190-8999
Tina FonnesCentre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, 5021 Bergen, Norway.
Kristine E FasmerDepartment of Clinical Medicine, University of Bergen, 5021 Bergen, Norway.
Camilla KrakstadCentre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, 5021 Bergen, Norway.
Ingfrid S HaldorsenDepartment of Clinical Medicine, University of Bergen, 5021 Bergen, Norway.ORCID 0000-0001-9313-7564
Haukeland University Hospital · NO

Funding

Kreftforeningen 190202Norges Forskningsråd 273280Trond Mohn Foundation BFS2018TMT06
6 · The paper itself

Abstract

Endometrial cancer is the most common gynecologic malignancy in industrialized countries. Most patients are cured by surgery; however, about 15% of the patients develop recurrence with limited treatment options. Patient-derived tumor xenograft (PDX) mouse models represent useful tools for preclinical evaluation of new therapies and biomarker identification. Preclinical imaging by magnetic resonance imaging (MRI), positron emission tomography-computed tomography (PET-CT), single-photon emission computed tomography (SPECT) and optical imaging during disease progression enables visualization and quantification of functional tumor characteristics, which may serve as imaging biomarkers guiding targeted therapies. A critical question, however, is whether the in vivo model systems mimic the disease setting in patients to such an extent that the imaging biomarkers may be translatable to the clinic. The primary objective of this review is to give an overview of current and novel preclinical imaging methods relevant for endometrial cancer animal models. Furthermore, we highlight how these advanced imaging methods depict pathogenic mechanisms important for tumor progression that represent potential targets for treatment in endometrial cancer.

Indexed as

computed tomographyendometrial cancergynecological cancerimaging biomarkersmagnetic resonance imagingmouse modelsoptical imagingPDX modelspositron emission tomographypreclinical imaging

Identifiers

PMID31783595
PMCPMC6966645
OpenAlexW2990018520

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.