ArticleScientific data2026
RadRepro CBCT: An Open-Access CBCT Phantom Dataset for Improved Standardization and Reproducibility of Radiomics Research.
Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Radiomics, the extraction of quantitative features from medical images, has shown great potential in improving precision diagnosis, prognosis, and treatment planning. However, the reproducibility of radiomics features remains a major challenge due to the variability introduced by differences in imaging devices, acquisition protocols, and image reconstruction methods. This study introduces the first open-access cone-beam computed tomography (CBCT) phantom dataset specifically designed to test reproducibility in on-board imaging systems used in C-arm linear accelerators for radiotherapy. Using a widely recognized Catphan phantom, CBCT images were acquired from multiple devices across different imaging parameters, including variations in mAs, slice thickness, and reconstruction filters. The dataset includes 120 CBCT volumes with corresponding region of interest (ROI) segmentations and radiomics features enabling comprehensive testing of radiomics feature stability across intra- and inter-vendor comparisons. By providing this open-access dataset, the study aims to facilitate the standardization of CBCT radiomics research, improve feature reproducibility, and support the development of robust radiomics models for clinical applications.
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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.