Evidence map›Paper›PMID 31273242›Full record

ArticleScientific reports2019

Assessing radiomic feature robustness to interpolation in

Philip Whybra, Craig Parkinson, Kieran Foley, John Staffurth, Emiliano Spezi

Abstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed
–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

44 citing papers in PubMed.

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  16. Predictive value ofEuropean journal of nuclear medicine and molecular imaging · 2023
    Article
  17. CT radiomic predictors of local relapse after SBRT for lung oligometastases from colorectal cancer: a single institute pilot study.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2023
    Article
  18. External validation of anEuropean journal of nuclear medicine and molecular imaging · 2023
    Article
  19. Feasibility of radiomic feature harmonization for pooling of [Zeitschrift fur medizinische Physik · 2023
    Article
  20. 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.

Philip WhybraSchool of Engineering, Cardiff University, Cardiff, United Kingdom. whybrap@cardiff.ac.uk.ORCID http://orcid.org/0000-0003-2214-6193
Craig ParkinsonSchool of Engineering, Cardiff University, Cardiff, United Kingdom.ORCID http://orcid.org/0000-0003-3454-4957
Kieran FoleyVelindre Cancer Centre, Cardiff, United Kingdom.ORCID http://orcid.org/0000-0002-1299-1759
John StaffurthVelindre Cancer Centre, Cardiff, United Kingdom.
Emiliano SpeziSchool of Engineering, Cardiff University, Cardiff, United Kingdom.ORCID http://orcid.org/0000-0002-1452-8813

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Radiomic studies link quantitative imaging features to patient outcomes in an effort to personalise treatment in oncology. To be clinically useful, a radiomic feature must be robust to image processing steps, which has made robustness testing a necessity for many technical aspects of feature extraction. We assessed the stability of radiomic features to interpolation processing and categorised features based on stable, systematic, or unstable responses. Here,

Indexed as

AdenocarcinomaAlgorithmsEsophageal NeoplasmsEsophageal Squamous Cell CarcinomaFluorodeoxyglucose F18HumansImage Processing, Computer-AssistedPhantoms, ImagingPositron-Emission TomographyRadiopharmaceuticalsFluorodeoxyglucose F18Radiopharmaceuticals

Identifiers

PMID31273242
PMCPMC6609613

What OpenQuestion holds

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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.