Evidence map›Paper›PMID 35671095›Full record

ReviewThe British journal of radiology2022

State-of-the-art imaging in oesophago-gastric cancer.

Samuel J Withey, Vicky Goh, Kieran G Foley

Open access · hybridAbstract readReview
In one paragraph

Review in The British journal of radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
1.5field-weighted citation impact, top 18% 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, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. PET/MRI is superior to PET/CT in detecting oesophago and gastric carcinomas: a meta-analysis.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025
    Pooled it
  2. Article
  3. Article
  4. Article
  5. 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

3 authors at 3 institutions in 1 country.

Samuel J WitheyDepartment of Radiology, The Royal Marsden NHS Foundation Trust, London, UK.
Vicky GohCancer Imaging, School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
Kieran G FoleyDivision of Cancer & Genetics, School of Medicine, Cardiff University, Wales, UK.ORCID 0000-0002-1299-1759
King's College London · GBRoyal Marsden NHS Foundation Trust · GBVelindre Cancer Centre · GB

Funding

Wellcome Trust
6 · The paper itself

Abstract

Radiological investigations are essential in the management of oesophageal and gastro-oesophageal junction cancers. The current multimodal combination of CT, 18F-fluorodeoxyglucose positron emission tomography combined with CT (PET/CT) and endoscopic ultrasound (EUS) has limitations, which hinders the prognostic and predictive information that can be used to guide optimum treatment decisions. Therefore, the development of improved imaging techniques is vital to improve patient management. This review describes the current evidence for state-of-the-art imaging techniques in oesophago-gastric cancer including high resolution MRI, diffusion-weighted MRI, dynamic contrast-enhanced MRI, whole-body MRI, perfusion CT, novel PET tracers, and integrated PET/MRI. These novel imaging techniques may help clinicians improve the diagnosis, staging, treatment planning, and response assessment of oesophago-gastric cancer.

Indexed as

Esophageal NeoplasmsStomach NeoplasmsFluorodeoxyglucose F18HumansMagnetic Resonance ImagingNeoplasm StagingPositron-Emission TomographyPositron Emission Tomography Computed TomographyRadiopharmaceuticalsFluorodeoxyglucose F18Radiopharmaceuticals

Identifiers

PMID35671095
PMCPMC10996959
OpenAlexW4281980007

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.