ArticleTomography (Ann Arbor, Mich.)2022
Noise-Based Image Harmonization Significantly Increases Repeatability and Reproducibility of Radiomics Features in PET Images: A Phantom Study.
Article in Tomography (Ann Arbor, Mich.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- A Robust [Journal of imaging informatics in medicine · 2025Article
- Long-axial field-of-view PET/CT improves radiomics feature reliability.European journal of nuclear medicine and molecular imaging · 2025Article
- Leveraging artificial intelligence to validate traditional biomarkers and drug targets in liver cancer recovery: a mini review.Frontiers in pharmacology · 2025Review
- On the robustness of [18F]-FDG-PET radiomic features to variations in image acquisition and reconstruction settings: A phantom study.PloS one · 2025Article
- Stability of radiomic features from positron emission tomography images: a phantom study comparing advanced reconstruction algorithms and ordered subset expectation maximization.Physical and engineering sciences in medicine · 2024Article
- Review on radiomic analysis inCancer imaging : the official publication of the International Cancer Imaging Society · 2024Review
- Strategies for Implementing Machine Learning Algorithms in the Clinical Practice of Radiology.Radiology · 2024Review
- Multicentric study on the reproducibility and robustness of PET-based radiomics features with a realistic activity painting phantom.PloS one · 2024Article
- A Critical Analysis of the Robustness of Radiomics to Variations in Segmentation Methods inDiagnostics (Basel, Switzerland) · 2023Article
- Reproducibility and location-stability of radiomic features derived from cone-beam computed tomography: a phantom study.Dento maxillo facial radiology · 2023Article
- Artificial intelligence-driven radiomics study in cancer: the role of feature engineering and modeling.Military Medical Research · 2023Review
- Prognostic value of pre-therapeutic FDG-PET radiomic analysis in gastro-esophageal junction cancer.Scientific reports · 2023Article
- Investigating the Effects of Reconstruction Conditions on Image Quality and Radiomic Analysis in Photon-counting Computed Tomography.Journal of medical physicsArticle
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Authors and funding
17 authors.
Funding
Abstract
For multicenter clinical studies, characterizing the robustness of image-derived radiomics features is essential. Features calculated on PET images have been shown to be very sensitive to image noise. The purpose of this work was to investigate the efficacy of a relatively simple harmonization strategy on feature robustness and agreement. A purpose-built texture pattern phantom was scanned on 10 different PET scanners in 7 institutions with various different image acquisition and reconstruction protocols. An image harmonization technique based on equalizing a contrast-to-noise ratio was employed to generate a "harmonized" alongside a "standard" dataset for a reproducibility study. In addition, a repeatability study was performed with images from a single PET scanner of variable image noise, varying the binning time of the reconstruction. Feature agreement was measured using the intraclass correlation coefficient (ICC). In the repeatability study, 81/93 features had a lower ICC on the images with the highest image noise as compared to the images with the lowest image noise. Using the harmonized dataset significantly improved the feature agreement for five of the six investigated feature classes over the standard dataset. For three feature classes, high feature agreement corresponded with higher sensitivity to the different patterns, suggesting a way to select suitable features for predictive models.
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