ArticleFrontiers in oncology2021
Reproducibility and Repeatability of CBCT-Derived Radiomics Features.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 3 of them syntheses that pooled it.
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Who cites it
20 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Patient outcome prognosis for external beam radiation therapy using CBCT-based radiomics: a systematic review.Biomedical physics & engineering express · 2026Pooled it
- Mastering CT-based radiomic research in lung cancer: a practical guide from study design to critical appraisal.The British journal of radiology · 2025Guideline
- Artificial intelligence applied to image-guided radiation therapy (IGRT): a systematic review by the Young Group of the Italian Association of Radiotherapy and Clinical Oncology (yAIRO).La Radiologia medica · 2024Pooled it
- Radiomics features as imaging biomarkers in alveolar and craniofacial bone healing: a scoping review.Odontology · 2026Review
- RadRepro CBCT: An Open-Access CBCT Phantom Dataset for Improved Standardization and Reproducibility of Radiomics Research.Scientific data · 2026Article
- Influence of scan mode, tilt, and radiation dose on CT radiomic metrics.Journal of applied clinical medical physics · 2026Article
- Cross species reproducibility of MRI radiomics features enables intervertebral disc degeneration assessment in experimental monkeys.Scientific reports · 2025Article
- Radiomics in Action: Multimodal Synergies for Imaging Biomarkers.Bioengineering (Basel, Switzerland) · 2025Review
- Establishment of a CT-based radiomic feature robustness databank for OPC patients via image perturbation in a multi-institutional study: a practical method to safeguard model generalizability.Frontiers in oncology · 2025Article
- Cone beam computed tomography (CBCT) and megavoltage computed tomography (MVCT)-based radiomics in head and neck cancers: a systematic review and radiomics quality score assessment.Quantitative imaging in medicine and surgery · 2024Review
- Stability of Radiomic Features against Variations in Lesion Segmentations Computed on Apparent Diffusion Coefficient Maps of Breast Lesions.Diagnostics (Basel, Switzerland) · 2024Article
- Reproducibility Analysis of Radiomic Features on T2-weighted MR Images after Processing and Segmentation Alterations in Neuroblastoma Tumors.Radiology. Artificial intelligence · 2024Article
- A comparative analysis of preclinical computed tomography radiomics using cone-beam and micro-computed tomography scanners.Physics and imaging in radiation oncology · 2024Article
- Accuracy of cone-beam breast computed tomography for assessing breast cancer tumor size-comparison with breast magnetic resonance imaging.Gland surgery · 2024Article
- Reproducibility and location-stability of radiomic features derived from cone-beam computed tomography: a phantom study.Dento maxillo facial radiology · 2023Article
- Assessment of Variabilities in Lung-Contouring Methods on CBCT Preclinical Radiomics Outputs.Cancers · 2023Article
- Development and optimisation of a preclinical cone beam computed tomography-based radiomics workflow for radiation oncology research.Physics and imaging in radiation oncology · 2023Article
- Current Applications of Deep Learning and Radiomics on CT and CBCT for Maxillofacial Diseases.Diagnostics (Basel, Switzerland) · 2022Review
- Enhancing the stability of CT radiomics across different volume of interest sizes using parametric feature maps: a phantom study.European radiology experimental · 2022Article
- Comparison of Deep Learning-Based Auto-Segmentation Results on Daily Kilovoltage, Megavoltage, and Cone Beam CT Images in Image-Guided Radiotherapy.Technology in cancer research & treatmentArticle
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThis study was conducted in order to determine the reproducibility and repeatability of cone-beam computed tomography (CBCT) radiomics features.
methodsThe first-, second-, and fifth-day CBCT images from 10 head and neck (H&N) cancer patients and 10 pelvic cancer patients were retrospectively collected for this study. Eighteen common radiomics features were extracted from the longitudinal CBCT images using two radiomics packages. The reproducibility of CBCT-derived radiomics features was assessed using the first-day image as input and compared across the two software packages. The site-specific intraclass correlation coefficient (ICC) was used to quantitatively assess the agreement between packages. The repeatability of CBCT-based radiomics features was evaluated by comparing the following days of CBCT to the first-day image and quantified using site-specific concordance correlation coefficient (CCC). Furthermore, the correlation with volume for all the features was assessed with linear regression and
resultsThe first-order histogram-based features such as skewness and entropy showed good agreement computed in either software package (ICCs ≥ 0.80), while the kurtosis measurements were consistent in H&N patients between the two software tools but not in pelvic cases. The ICCs for GLCM-based features showed good agreement (ICCs ≥ 0.80) between packages in both H&N and pelvic groups except for the GLCM-correction. The GLRLM-based texture features were overall less consistent as calculated by the two different software packages compared with the GLCM-based features. The CCC values of all first-order and second-order GLCM features (except GLCM-energy) were all above 0.80 from the 2-day part test-retest set, while the CCC values all dropped below the cutoff after 5-day treatment scans. All first-order histogram-based and GLCM-texture-based features were not highly correlated with volume, while two GLRLM features, in both H&N and pelvic cohorts, showed
conclusionThe reproducibility and repeatability of CBCT-based radiomics features were assessed and compared for the first time on both H&N and pelvic sites. There were overlaps of stable features in both disease sites, yet the overall stability of radiomics features may be disease-/protocol-specific and a function of time between scans.
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