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    Optimising use of 4D-CT phase information for radiomics analysis in lung cancer patients treated with stereotactic body radiotherapy

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    Authors
    Davey, Angela
    van Herk, Marcel
    Faivre-Finn, Corinne
    Brown, Sean
    McWilliam, Alan
    Affiliation
    Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Mancheste
    Issue Date
    2021
    
    Metadata
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    Abstract
    Purpose: 4D-CT is routine imaging for lung cancer patients treated with stereotactic body radiotherapy. No studies have investigated optimal 4D phase selection for radiomics. We aim to determine how phase data should be used to identify prognostic biomarkers for distant failure, and test whether stability assessment is required. A phase selection approach will be developed to aid studies with different 4D protocols, and account for patient differences. Methods: 186 features were extracted from the tumour and peritumour on all phases for 258 patients. Feature values were selected from phase features using four methods: A) mean across phases, B) median across phases, C) 50% phase, and D) the most stable phase (closest in value to two neighbours), coined personalised selection. Four levels of stability assessment were also analysed, with inclusion of: 1) all features, 2) stable features across all phases, 3) stable features across phase and neighbour phases, and 4) features averaged over neighbour phases. Clinical-radiomics models were built for twelve combinations of feature type and assessment method. Model performance was assessed by concordance index and fraction of new information from radiomic features. Results: The most stable phase spanned the whole range but was most often near exhale. All radiomic signatures provided new information for distant failure prediction. The personalised model had the highest concordance index (0.77), and 58% of new information was provided by radiomic features when no stability assessment was performed. Conclusion: The most stable phase varies per-patient and selecting this improves model performance compared to standard methods. We advise the single most stable phase should be determined by minimising feature differences to neighbour phases. Stability assessment over all phases decreases performance by excessively removing features. Instead, averaging of neighbour phases should be used when stability is of concern. The models suggest that higher peritumoural intensity predicts distant failure.
    Citation
    Davey A, van Herk M, Faivre-Finn C, Brown S, McWilliam A. Optimising use of 4D-CT phase information for radiomics analysis in lung cancer patients treated with stereotactic body radiotherapy. Phys Med Biol. 2021 Apr 21
    Journal
    Physics in Medicine and Biology
    URI
    http://hdl.handle.net/10541/623977
    DOI
    10.1088/1361-6560/abfa34
    PubMed ID
    33882470
    Additional Links
    https://dx.doi.org/10.1088/1361-6560/abfa34
    Type
    Article
    Language
    en
    ae974a485f413a2113503eed53cd6c53
    10.1088/1361-6560/abfa34
    Scopus Count
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