Evidence map›Paper›PMID 35340828›Full record

ArticleEuropean journal of radiology open2022

Using texture analysis in the development of a potential radiomic signature for early identification of hepatic metastasis in colorectal cancer.

Laurence Devoto, Balaji Ganeshan, Deborah Keller, Ashley Groves, Raymond Endozo, Tan Arulampalam, Manish Chand

Abstract read
In one paragraph

Article in European journal of radiology open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 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.

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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Colorectal cancer liver metastases: A radiologic point of view.World journal of gastrointestinal oncology · 2025
    Article
  5. Review
  6. Review
  7. Radiomics in colorectal cancer patients.World journal of gastroenterology · 2023
    Review
  8. Review
  9. Review
  10. Whole-liver enhanced CT radiomics analysis to predict metachronous liver metastases after rectal cancer surgery.Cancer imaging : the official publication of the International Cancer Imaging Society · 2022
    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

7 authors.

Laurence DevotoWellcome / EPSRC Centre, for Interventional and Surgical Sciences, University College London, 1st Floor, Charles Bell House, 43-45 Foley Street, London W1W 7TS, United Kingdom.
Balaji GaneshanInstitute of Nuclear Medicine, 5th floor, Tower, University College London Hospital, 235 Euston Road, London NW1 2BU, United Kingdom.
Deborah KellerWellcome / EPSRC Centre, for Interventional and Surgical Sciences, University College London, 1st Floor, Charles Bell House, 43-45 Foley Street, London W1W 7TS, United Kingdom.
Ashley GrovesInstitute of Nuclear Medicine, 5th floor, Tower, University College London Hospital, 235 Euston Road, London NW1 2BU, United Kingdom.
Raymond EndozoInstitute of Nuclear Medicine, 5th floor, Tower, University College London Hospital, 235 Euston Road, London NW1 2BU, United Kingdom.
Tan ArulampalamICENI Centre, Colchester Hospital, Turner Rd, Mile End, Colchester CO4 5JL, United Kingdom.
Manish ChandWellcome / EPSRC Centre, for Interventional and Surgical Sciences, University College London, 1st Floor, Charles Bell House, 43-45 Foley Street, London W1W 7TS, United Kingdom.

Funding

Wellcome Trust
6 · The paper itself

Abstract

Background: Radiomics allows information not readily available to the naked eye to be extracted from high resolution imaging modalities such as CT. Identifying that a cancer has already metastasised at the time of presentation through a radiomic signature will affect the treatment pathway. The ability to recognise the existence of metastases earlier will have a significant impact on the survival outcomes. Aim: To create a novel radiomic signature using textural analysis in the evaluation of synchronous liver metastases in colorectal cancer. Methods: CT images at baseline and subsequent surveillance over a 5-year period of patients with colorectal cancer were processed using textural analysis software. Comparison was made between those patients who developed liver metastases and those that remained disease free to detect differences in the 'texture' of the liver. Results: A total of 24 patients were divided into two matched groups for comparison. Significant differences between the two groups scores when using the textural analysis programme were found on coarse filtration (p = 0.044). Patients that went on to develop metastases an average of 18 months after presentation had higher levels of hepatic heterogeneity on CT. Conclusion: This initial study demonstrates the potential of using a textural analysis programme to build a radiomic signature to predict the development of hepatic metastases in rectal cancer patients otherwise thought to have clear staging CT scans at time of presentation.

Indexed as

CancerImagingMetastasesRadiologySurgical management

Identifiers

PMID35340828
PMCPMC8942820

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.