ArticleContrast media & molecular imaging2018
Parameters Influencing PET Imaging Features: A Phantom Study with Irregular and Heterogeneous Synthetic Lesions.
Article in Contrast media & molecular imaging, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Multiparametric PET/CT Tensor Radiomics for Stability-Aware Machine Learning in Lung Cancer Survival Prediction.Journal of imaging informatics in medicine · 2026Article
- Enhancing PET/CT target assessment with porous 3D printed grids: a pilot study.Physical and engineering sciences in medicine · 2026Article
- Enhancing radiomics robustness using bayesian penalized likelihood PET reconstruction: application to Phantom and non-small cell lung cancer patient studies.BMC medical imaging · 2025Article
- Robustness of textural analysis features in quantitativeEJNMMI physics · 2025Article
- On the robustness of [18F]-FDG-PET radiomic features to variations in image acquisition and reconstruction settings: A phantom study.PloS one · 2025Article
- Artificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 2: recommendations for standardisation, validation, and good clinical practice.The Lancet. Oncology · 2024Review
- PET radiomics in lung cancer: advances and translational challenges.EJNMMI physics · 2024Review
- Multicentric study on the reproducibility and robustness of PET-based radiomics features with a realistic activity painting phantom.PloS one · 2024Article
- The Applications of Artificial Intelligence in Digestive System Neoplasms: A Review.Health data science · 2023Review
- A heterogeneous phantom study for investigating the stability of PET images radiomic features with varying reconstruction settings.Frontiers in nuclear medicine · 2023Article
- A methodological framework for AI-assisted diagnosis of active aortitis using radiomic analysis of FDG PET-CT images: Initial analysis.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2022Article
- A multi-modality physical phantom for mimicking tumor heterogeneity patterns in PET/CT and PET/MRI.Medical physics · 2022Article
- Synergistic impact of motion and acquisition/reconstruction parameters onMedical physics · 2022Article
- Design and evaluation of a modular multimodality imaging phantom to simulate heterogeneous uptake and enhancement patterns for radiomic quantification in hybrid imaging: A feasibility study.Medical physics · 2022Article
- Noise-Based Image Harmonization Significantly Increases Repeatability and Reproducibility of Radiomics Features in PET Images: A Phantom Study.Tomography (Ann Arbor, Mich.) · 2022Article
- Radiomics feature reliability assessed by intraclass correlation coefficient: a systematic review.Quantitative imaging in medicine and surgery · 2021Review
- Preselection of robust radiomic features does not improve outcome modelling in non-small cell lung cancer based on clinical routine FDG-PET imaging.EJNMMI research · 2021Article
- Repeatability ofJournal of nuclear medicine : official publication, Society of Nuclear Medicine · 2021Article
- Deep Learning-Based Methods for Prostate Segmentation in Magnetic Resonance Imaging.Applied sciences (Basel, Switzerland) · 2021Article
- Radiomics in medical imaging-"how-to" guide and critical reflection.Insights into imaging · 2020Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aim: To evaluate reproducibility and stability of radiomic features as effects of the use of different volume segmentation methods and reconstruction settings. The potential of radiomics in really capturing the presence of heterogeneous tumor uptake and irregular shape was also investigated. Materials and Methods: An anthropomorphic phantom miming real clinical situations including synthetic lesions with irregular shape and nonuniform radiotracer uptake was used. Results: The choice of the segmentation method has a strong impact on the stability of radiomic features (less than 20% can be considered stable features). Reconstruction affects the estimate of radiomic features (only 26% are stable). Thirty-one radiomic features (53%) resulted to be reproducible, 11 of them are able to discriminate heterogeneity. Among these, we found a subset of 3 radiomic features strongly correlated with GS heterogeneity index that can be suggested as good features for retrospective evaluations.
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