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    Stability of radiomics features in apparent diffusion coefficient maps from a multi-centre test-retest trial

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    Authors
    Peerlings, J
    Woodruff, H
    Winfield, J
    Ibrahim, A
    Van Beers, B
    Heerschap, A
    Jackson, Andrew
    Wildberger, J
    Mottaghy, F
    DeSouza, N
    Lambin, P
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    Affiliation
    The D-Lab, Department of Precision Medicine, Royal Marsden Hospital, Sutton, UK
    Issue Date
    2019
    
    Metadata
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    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.
    Citation
    Peerlings J, Woodruff HC, Winfield JM, Ibrahim A, Van Beers BE, Heerschap A, et al. Stability of radiomics features in apparent diffusion coefficient maps from a multi-centre test-retest trial. Sci Rep. 2019 Mar 18;9(1):4800.
    Journal
    Scientific Reports
    URI
    http://hdl.handle.net/10541/621774
    DOI
    10.1038/s41598-019-41344-5
    PubMed ID
    30886309
    Additional Links
    https://dx.doi.org/10.1038/s41598-019-41344-5
    Type
    Article
    Language
    en
    ae974a485f413a2113503eed53cd6c53
    10.1038/s41598-019-41344-5
    Scopus Count
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