Stability of radiomics features in apparent diffusion coefficient maps from a multi-centre test-retest trial.
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Embargo End Date
ICR Authors
Authors
Peerlings, J
Woodruff, HC
Winfield, JM
Ibrahim, A
Van Beers, BE
Heerschap, A
Jackson, A
Wildberger, JE
Mottaghy, FM
DeSouza, NM
Lambin, P
Woodruff, HC
Winfield, JM
Ibrahim, A
Van Beers, BE
Heerschap, A
Jackson, A
Wildberger, JE
Mottaghy, FM
DeSouza, NM
Lambin, P
Document Type
Journal Article
Date
2019-03-18
Date Accepted
2019-03-05
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
Scientific reports, 2019, 9 (1), pp. 4800 - ?
Source Title
Publisher
NATURE PORTFOLIO
ISSN
2045-2322
eISSN
2045-2322
Collections
Research Team
Magnetic Resonance