ArticleMedical physics2019
Multicenter CT phantoms public dataset for radiomics reproducibility tests.
Article in Medical physics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 27 papers.
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
27 citing papers in PubMed, 39 citations in OpenAlex.
- CT texture phantom dataset with paired image quality assessments for quantitative imaging.Medical physics · 2026Article
- An open-source CT texture phantom for radiomic imaging studies: Design, manufacture, and initial evaluation.Medical physics · 2026Article
- Radiomic analysis of medical imaging for classification in oncology and recommendations for clinically initiated research: a literature review.Quantitative imaging in medicine and surgery · 2026Review
- RadRepro CBCT: An Open-Access CBCT Phantom Dataset for Improved Standardization and Reproducibility of Radiomics Research.Scientific data · 2026Article
- Evaluating consistency of radiomic features derived from CT images: A cross-center phantom study.Journal of applied clinical medical physics · 2026Article
- Phantom studies in medical imaging (PSMI): a guide with recommendations and checklist.European radiology experimental · 2025Article
- Data-centric artificial intelligence and cancer research: construction of a real-world head and neck treatment data repository.ESMO real world data and digital oncology · 2025Article
- Sparse-View CT Joint Reconstruction Strategy with Sparse Sampling Encoding LayerCurrent medical imaging · 2025Article
- Proton FLASH-arc therapy (PFAT): A feasibility study for meeting FLASH dose-rate requirements in the clinic.Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology · 2025Article
- Emulating the Delivery of Sawtooth Proton Arc Therapy Plans on a Cyclotron-Based Proton Beam Therapy System.Cancers · 2024Article
- A reference framework for standardization and harmonization of CT radiomics features on cadaveric sample.Scientific reports · 2024Article
- Independent validation of CT radiomics models in colorectal liver metastases: predicting local tumour progression after ablation.European radiology · 2024Article
- CT Cadaveric dataset for Radiomics features stability assessment in lumbar vertebrae.Scientific data · 2024Article
- Radiogenomics: a key component of precision cancer medicine.British journal of cancer · 2023Review
- Bridging the simulation-to-real gap for AI-based needle and target detection in robot-assisted ultrasound-guided interventions.European radiology experimental · 2023Article
- Pilot Study for the Assessment of the Best Radiomic Features for Bosniak Cyst Classification Using Phantom and Radiologist Inter-Observer Selection.Diagnostics (Basel, Switzerland) · 2023Article
- A customized anthropomorphic 3D-printed phantom to reproducibility assessment in computed tomography: an oncological case study.Frontiers in oncology · 2023Article
- A Review of Radiomics and Artificial Intelligence and Their Application in Veterinary Diagnostic Imaging.Veterinary sciences · 2022Review
- XNAT-PIC: Extending XNAT to Preclinical Imaging Centers.Journal of digital imaging · 2022Article
- Radiomics: A Primer on Processing Workflow and Analysis.Seminars in ultrasound, CT, and MR · 2022Review
Corrections and comments
- Erratum issued
Authors and funding
11 authors at 5 institutions in 1 country.
Funding
Abstract
purposeThe aim of this paper is to describe a public, open-access, computed tomography (CT) phantom image set acquired at three centers and collected especially for radiomics reproducibility research. The dataset is useful to test radiomic features reproducibility with respect to various parameters, such as acquisition settings, scanners, and reconstruction algorithms. ACQUISITION AND VALIDATION
methodsThree phantoms were scanned in three independent institutions. Images of the following phantoms were acquired: Catphan 700 and COPDGene Phantom II (Phantom Laboratory, Greenwich, NY, USA), and the Triple modality 3D Abdominal Phantom (CIRS, Norfolk, VA, USA). Data were collected at three Dutch medical centers: MAASTRO Clinic (Maastricht, NL), Radboud University Medical Center (Nijmegen, NL), and University Medical Center Groningen (Groningen, NL) with scanners from two different manufacturers Siemens Healthcare and Philips Healthcare. The following acquisition parameter were varied in the phantom scans: slice thickness, reconstruction kernels, and tube current. DATA FORMAT AND USAGE NOTES: We made the dataset publically available on the Dutch instance of "Extensible Neuroimaging Archive Toolkit-XNAT" (https://xnat.bmia.nl). The dataset is freely available and reusable with attribution (Creative Commons 3.0 license). POTENTIAL APPLICATIONS: Our goal was to provide a findable, open-access, annotated, and reusable CT phantom dataset for radiomics reproducibility studies. Reproducibility testing and harmonization are fundamental requirements for wide generalizability of radiomics-based clinical prediction models. It is highly desirable to include only reproducible features into models, to be more assured of external validity across hitherto unseen contexts. In this view, phantom data from different centers represent a valuable source of information to exclude CT radiomic features that may already be unstable with respect to simplified structures and tightly controlled scan settings. The intended extension of our shared dataset is to include other modalities and phantoms with more realistic lesion simulations.
Indexed as
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What OpenQuestion holds
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.