Evidence map›Paper›PMID 23064544›Full record

ReviewEuropean journal of nuclear medicine and molecular imaging2013

Quantifying tumour heterogeneity in 18F-FDG PET/CT imaging by texture analysis.

Sugama Chicklore, Vicky Goh, Musib Siddique, Arunabha Roy, Paul K Marsden, Gary J R Cook

Registry-linked trialAbstract readReview
PubMed Publisher
In one paragraph

Review in European journal of nuclear medicine and molecular imaging, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04276025 (Relationship Between Histopathological Features, Mutation Status, 18F-FDG PET/CT Radiomic Imaging Parameters as Well as Clinical Outcome in Patients With Treatment-naïve Non-small Cell Lung Cancer), which is not on this map. Cited by 241 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
241citing papers in PubMed, 3 pooled it
–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.

NCT04276025 completednot on this mapstarted 2016, after this paper: background citation

Relationship Between Histopathological Features, Mutation Status, 18F-FDG PET/CT Radiomic Imaging Parameters as Well as Clinical Outcome in Patients With Treatment-naïve Non-small Cell Lung Cancer

TypeobservationalSponsorKlinikum Bayreuth GmbHRan2016 to 2020Enrolled2,000ConditionsNSCLCArmsClinical routine F18-FDG-PET/CT, molecular pathology and clinical outcome
3 · Its place in the literature

Who cites it

241 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Repeatability and Reproducibility of Radiomic Features: A Systematic Review.International journal of radiation oncology, biology, physics · 2018
    Pooled it
  3. Pooled it
  4. Trial
  5. A radiomics nomogram for the prediction of overall survival in patients with hepatocellular carcinoma after hepatectomy.Cancer imaging : the official publication of the International Cancer Imaging Society · 2020
    Trial
  6. Textural features of hypoxia PET predict survival in head and neck cancer during chemoradiotherapy.European journal of nuclear medicine and molecular imaging · 2020
    Trial
  7. Radiomics based onCancer medicine · 2020
    Trial
  8. Trial
  9. Trial
  10. Trial
  11. Robustness of Radiomic Features in [Molecular imaging and biology · 2016
    Trial
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Texture analysis and metabolic parameters ofEuropean journal of nuclear medicine and molecular imaging · 2025
    Article

181 more citing papers are in PubMed but not listed here.

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.

Sugama ChickloreClinical PET Centre, Division of Imaging Sciences and Biomedical Engineering, Kings College London, St Thomas' Hospital, London, UK.
Vicky Goh
Musib Siddique
Arunabha Roy
Paul K Marsden
Gary J R Cook

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

(18)F-Fluorodeoxyglucose positron emission tomography/computed tomography ((18)F-FDG PET/CT) is now routinely used in oncological imaging for diagnosis and staging and increasingly to determine early response to treatment, often employing semiquantitative measures of lesion activity such as the standardized uptake value (SUV). However, the ability to predict the behaviour of a tumour in terms of future therapy response or prognosis using SUVs from a baseline scan prior to treatment is limited. It is recognized that medical images contain more useful information than may be perceived with the naked eye, leading to the field of "radiomics" whereby additional features can be extracted by computational postprocessing techniques. In recent years, evidence has slowly accumulated showing that parameters obtained by texture analysis of radiological images, reflecting the underlying spatial variation and heterogeneity of voxel intensities within a tumour, may yield additional predictive and prognostic information. It is hoped that measurement of these textural features may allow better tissue characterization as well as better stratification of treatment in clinical trials, or individualization of future cancer treatment in the clinic, than is possible with current imaging biomarkers. In this review we focus on the literature describing the emerging methods of texture analysis in (18)FDG PET/CT, as well as other imaging modalities, and how the measurement of spatial variation of voxel grey-scale intensity within an image may provide additional predictive and prognostic information, and postulate the underlying biological mechanisms.

Indexed as

Fluorodeoxyglucose F18Mathematical ComputingMultimodal ImagingPositron-Emission TomographyRadiopharmaceuticalsTomography, X-Ray ComputedHumansNeoplasmsProbabilityPrognosisFluorodeoxyglucose F18Radiopharmaceuticals

Identifiers

PMID23064544

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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.