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• W2922347875 abstract "Abstract Quantitative radiomics features, extracted from medical images, characterize tumour-phenotypes and have been shown to provide prognostic value in predicting clinical outcomes. Stability of radiomics features extracted from apparent diffusion coefficient (ADC)-maps is essential for reliable correlation with the underlying pathology and its clinical applications. Within a multicentre, multi-vendor trial we established a method to analyse radiomics features from ADC-maps of ovarian (n = 12), lung (n = 19), and colorectal liver metastasis (n = 30) cancer patients who underwent repeated (<7 days) diffusion-weighted imaging at 1.5 T and 3 T. From these ADC-maps, 1322 features describing tumour shape, texture and intensity were retrospectively extracted and stable features were selected using the concordance correlation coefficient (CCC > 0.85). Although some features were tissue- and/or respiratory motion-specific, 122 features were stable for all tumour-entities. A large proportion of features were stable across different vendors and field strengths. By extracting stable phenotypic features, fitting-dimensionality is reduced and reliable prognostic models can be created, paving the way for clinical implementation of ADC-based radiomics." @default.
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• W2922347875 date "2019-03-18" @default.
• W2922347875 modified "2023-10-10" @default.
• W2922347875 title "Stability of radiomics features in apparent diffusion coefficient maps from a multi-centre test-retest trial" @default.
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• W2922347875 doi "https://doi.org/10.1038/s41598-019-41344-5" @default.
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• W2922347875 hasPublicationYear "2019" @default.
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