Stability of radiomics features in apparent diffusion coefficient maps from a multi-centre test-retest trial
Van Beers, B
AffiliationThe D-Lab, Department of Precision Medicine, Royal Marsden Hospital, Sutton, UK
MetadataShow full item record
AbstractQuantitative 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.
CitationPeerlings 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.
- Radiomics assessment of bladder cancer grade using texture features from diffusion-weighted imaging.
- Authors: Zhang X, Xu X, Tian Q, Li B, Wu Y, Yang Z, Liang Z, Liu Y, Cui G, Lu H
- Issue date: 2017 Nov
- 4DCT imaging to assess radiomics feature stability: An investigation for thoracic cancers.
- Authors: Larue RTHM, Van De Voorde L, van Timmeren JE, Leijenaar RTH, Berbée M, Sosef MN, Schreurs WMJ, van Elmpt W, Lambin P
- Issue date: 2017 Oct
- Can radiomics features be reproducibly measured from CBCT images for patients with non-small cell lung cancer?
- Authors: Fave X, Mackin D, Yang J, Zhang J, Fried D, Balter P, Followill D, Gomez D, Jones AK, Stingo F, Fontenot J, Court L
- Issue date: 2015 Dec
- A multi-sequence and habitat-based MRI radiomics signature for preoperative prediction of MGMT promoter methylation in astrocytomas with prognostic implication.
- Authors: Wei J, Yang G, Hao X, Gu D, Tan Y, Wang X, Dong D, Zhang S, Wang L, Zhang H, Tian J
- Issue date: 2019 Feb
- Test-Retest Data for Radiomics Feature Stability Analysis: Generalizable or Study-Specific?
- Authors: van Timmeren JE, Leijenaar RTH, van Elmpt W, Wang J, Zhang Z, Dekker A, Lambin P
- Issue date: 2016 Dec