ArticleEuropean radiology2023
Phantom-based radiomics feature test-retest stability analysis on photon-counting detector CT.
Article in European radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.
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Who cites it
32 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Image Quality Standardization in Radiomics: A Systematic Review of Artifacts, Variability, and Feature Stability.Sensors (Basel, Switzerland) · 2026Pooled it
- Age-associated radiomic phenotyping in mice using multi-energy photon-counting and preclinical CT: an exploratory study.Biogerontology · 2026Article
- Comparison of radiomics-based models for detection of Modic type 1 changes in photon-counting detector CT images of the lumbar spine.Skeletal radiology · 2026Article
- Impact of Different Energy Levels of Virtual Monoenergetic Reconstructions on Radiomic Features Stability in Organic Phantom Imaging Using Photon-Counting CT.Tomography (Ann Arbor, Mich.) · 2026Article
- Radiomics: Current Applications and Future Directions.MedComm · 2026Review
- Influence of image preprocessing on reproducibility and longitudinal repeatability analysis of radiomics features in magnetic resonance image-guided accelerator imaging.Quantitative imaging in medicine and surgery · 2026Article
- Analysis of epicardial adipose tissue in relation to arterial hypertension using radiomics in photon-counting CT.Frontiers in cardiovascular medicine · 2026Article
- Phantom-based evaluation of radiomics feature stability for low-dose CT lung cancer screening.Frontiers in endocrinology · 2026Article
- Photon-Counting CT in Musculoskeletal Radiology: Technical Principles, Clinical Applications, and Future Directions.Journal of the Belgian Society of Radiology · 2026Review
- Targeting tumoral heterogeneity in lung cancer: a novel, CT-texture-guided targeted biopsy approach with exome sequencing.NPJ precision oncology · 2025Article
- Thoracic applications of photon-counting CT: where are we after 3 years of clinical implementation?The British journal of radiology · 2025Review
- A Narrative Review of Photon-Counting CT and Radiomics in Cardiothoracic Imaging: A Promising Match?Diagnostics (Basel, Switzerland) · 2025Review
- Insertion of hepatic lesions into clinical photon-counting-detector CT projection data.Physics in medicine and biology · 2025Article
- Robustness of radiomics within photon-counting detector CT: impact of acquisition and reconstruction factors.European radiology · 2025Article
- Radiomics Signature of Aging Myocardium in Cardiac Photon-Counting Computed Tomography.Diagnostics (Basel, Switzerland) · 2025Article
- Assessing the stability of photon-counting CT: insights from a 2-year longitudinal study.European radiology · 2025Article
- Radiomics-driven spectral profiling of six kidney stone types with monoenergetic CT reconstructions in photon-counting CT.European radiology · 2025Article
- Recent trends in scientific research in chest radiology: What to do or not to do? That is the critical question in research.Japanese journal of radiology · 2025Review
- Future Applications of Cardiothoracic CT.Radiology · 2025Review
- Robustness of radiomics among photon-counting detector CT and dual-energy CT systems: a texture phantom study.European radiology · 2025Article
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11 authors.
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Abstract
objectivesRadiomics image data analysis offers promising approaches in research but has not been implemented in clinical practice yet, partly due to the instability of many parameters. The aim of this study is to evaluate the stability of radiomics analysis on phantom scans with photon-counting detector CT (PCCT).
methodsPhoton-counting CT scans of organic phantoms consisting of 4 apples, kiwis, limes, and onions each were performed at 10 mAs, 50 mAs, and 100 mAs with 120-kV tube current. The phantoms were segmented semi-automatically and original radiomics parameters were extracted. This was followed by statistical analysis including concordance correlation coefficients (CCC), intraclass correlation coefficients (ICC), as well as random forest (RF) analysis, and cluster analysis to determine the stable and important parameters.
resultsSeventy-three of the 104 (70%) extracted features showed excellent stability with a CCC value > 0.9 when compared in a test and retest analysis, and 68 features (65.4%) were stable compared to the original in a rescan after repositioning. Between the test scans with different mAs values, 78 (75%) features were rated with excellent stability. Eight radiomics features were identified that had an ICC value greater than 0.75 in at least 3 of 4 groups when comparing the different phantoms in a phantom group. In addition, the RF analysis identified many features that are important for distinguishing the phantom groups.
conclusionRadiomics analysis using PCCT data provides high feature stability on organic phantoms, which may facilitate the implementation of radiomics analysis likewise in clinical routine. KEY POINTS: • Radiomics analysis using photon-counting computed tomography provides high feature stability. • Photon-counting computed tomography may pave the way for implementation of radiomics analysis in clinical routine.
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