Evidence map›Paper›PMID 32846986›Full record

ReviewBiomedicines2020

Characterization of FDG PET Images Using Texture Analysis in Tumors of the Gastro-Intestinal Tract: A Review.

Anne-Leen Deleu, Machaba Junior Sathekge, Alex Maes, Bart De Spiegeleer, Mike Sathekge, Christophe Van de Wiele

Open access · goldAbstract readReview
In one paragraph

Review in Biomedicines, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.7field-weighted citation impact, top 27% 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

6 citing papers in PubMed, 9 citations in OpenAlex.

  1. An interpretable machine learning model integrating [European journal of nuclear medicine and molecular imaging · 2026
    Article
  2. Article
  3. The prognostic value of [Clinical physiology and functional imaging · 2025
    Article
  4. Article
  5. Review
  6. 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

6 authors at 3 institutions in 2 countries.

Anne-Leen DeleuDepartment of Nuclear Medicine, AZ Groeninge, 8500 Kortrijk, Belgium.
Machaba Junior SathekgeDepartment of Nuclear Medicine, University of Pretoria, 0002 Pretoria, South Africa.
Alex MaesDepartment of Nuclear Medicine, AZ Groeninge, 8500 Kortrijk, Belgium.
Bart De SpiegeleerDepartment of Analytical Chemistry, DruQuaR, University of Ghent, 9000 Ghent, Belgium.ORCID 0000-0001-6794-3108
Mike SathekgeDepartment of Nuclear Medicine, University of Pretoria, 0002 Pretoria, South Africa.ORCID 0000-0002-2806-0625
Christophe Van de WieleDepartment of Nuclear Medicine, AZ Groeninge, 8500 Kortrijk, Belgium.
AZ Groeninge · BEUniversity of Pretoria · ZAGhent University · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Radiomics or textural feature extraction obtained from positron emission tomography (PET) images through complex mathematical models of the spatial relationship between multiple image voxels is currently emerging as a new tool for assessing intra-tumoral heterogeneity in medical imaging. In this paper, available literature on texture analysis using FDG PET imaging in patients suffering from tumors of the gastro-intestinal tract is reviewed. While texture analysis of FDG PET images appears clinically promising, due to the lack of technical specifications, a large variability in the implemented methodology used for texture analysis and lack of statistical robustness, at present, no firm conclusions can be drawn regarding the predictive or prognostic value of FDG PET texture analysis derived indices in patients suffering from gastro-enterologic tumors. In order to move forward in this field, a harmonized image acquisition and processing protocol as well as a harmonized protocol for texture analysis of tumor volumes, allowing multi-center studies excluding statistical biases should be considered. Furthermore, the complementary and additional value of CT-imaging, as part of the PET/CT imaging technique, warrants exploration.

Indexed as

gastro-intestinal cancerradiomics

Identifiers

PMID32846986
PMCPMC7556033
OpenAlexW3081500948

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.