Evidence map›Paper›PMID 41619289›Full record

ArticleJournal of applied clinical medical physics2026

Evaluating consistency of radiomic features derived from CT images: A cross-center phantom study.

Lorna Tu, Hervé H F Choi, Haley Clark, Bradford Gill, Scott Young, Samantha A M Lloyd

Abstract readMulticenter StudyEvaluation Study
In one paragraph

Article in Journal of applied clinical medical physics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Lorna TuDepartment of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.ORCID https://orcid.org/0000-0002-6902-8998
Hervé H F ChoiDepartment of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.ORCID https://orcid.org/0009-0000-4226-3210
Haley ClarkDepartment of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.ORCID https://orcid.org/0000-0003-4780-8093
Bradford GillDepartment of Medical Physics, BC Cancer, Vancouver, British Columbia, Canada.
Scott YoungDepartment of Medical Physics, BC Cancer, Vancouver, British Columbia, Canada.
Samantha A M LloydDepartment of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.ORCID https://orcid.org/0000-0002-0468-2040

Funding

BC Cancer FoundationNatural Sciences and Engineering Research Council of Canada PGS D - 579626 - 2023
6 · The paper itself

Abstract

purposeTo investigate the consistency of radiomic features extracted from computed tomography (CT) scans across CT radiotherapy simulators geographically spread across a Canadian province using a simplified lung radiomic phantom, and to determine whether it is appropriate to combine multicenter imaging data into a single dataset.

methodsAn inexpensive phantom was created using foam with a density similar to lung and a plastic vial insert filled with water. It was imaged at six provincial radiotherapy treatment centers using eight GE CT radiotherapy simulators and routine lung stereotactic ablative radiotherapy planning CT acquisition protocols. Radiomic features were extracted from regions of interest using Imaging Biomarker Explorer radiomics software and compared using Kruskal Wallis H tests, intraclass correlation coefficient (ICC), and coefficient of variation (CV).

resultsImage acquisition parameters were similar across centers. At the population level, no significant inconsistencies between radiomic features originating from different centers or from within the same center were observed (Bonferroni-corrected p > 0.05; ICC > 0.941). On average, 52.5% of features were considered consistent (CV ≤ 0.10).

conclusionsThe proposed phantom was transported across widespread centers without detectable damage and demonstrates potential for easy quality assurance checks on radiomic feature consistency within a multi-institutional setting. Our analysis suggests that some features should be omitted or standardized before combining provincial imaging data into a harmonized lung radiotherapy dataset. These preliminary findings lay the groundwork for further investigation into provincial radiomic feature consistency and potential application to multicenter clinical studies. Owing to potential differences in imaging protocols, a consistency evaluation should be performed before undertaking radiomic analysis of data combined from different institutions.

Indexed as

Lung NeoplasmsPhantoms, ImagingRadiomicsTomography, X-Ray ComputedHumansImage Processing, Computer-AssistedRadiotherapy DosageRadiotherapy, Intensity-ModulatedRadiotherapy Planning, Computer-Assistedcomputed tomographyfeature consistencymulti‐institutionalphantomradiomics

Identifiers

PMID41619289
PMCPMC12860509

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LicenceCC BY
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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.