Abstract
Background and purpose: Quantitative tissue characteristics derived from medical images, also called radiomics, contain valuable prognostic information in several tumour-sites. The large number of features available increases the risk of overfitting. Typically test-retest CT-scans are used to reduce dimensionality and select robust features. However, these scans are not always available. We propose to use different phases of respiratory-correlated 4D CT-scans (4DCT) as alternative.
Materials and methods: In test-retest CT-scans of 26 non-small cell lung cancer (NSCLC) patients and 4DCT-scans (8 breathing phases) of 20 NSCLC and 20 oesophageal cancer patients, 1045 radiomics features of the primary tumours were calculated. A concordance correlation coefficient (CCC) >0.85 was used to identify robust features. Correlation with prognostic value was tested using univariate cox regression in 120 oesophageal cancer patients.
Results: Features based on unfiltered images demonstrated greater robustness than wavelet-filtered features. In total 63/74 (85%) unfiltered features and 268/299 (90%) wavelet features stable in the 4D-lung dataset were also stable in the test-retest dataset. In oesophageal cancer 397/1045 (38%) features were robust, of which 108 features were significantly associated with overall-survival.
Conclusion: 4DCT-scans can be used as alternative to eliminate unstable radiomics features as first step in a feature selection procedure. Feature robustness is tumour-site specific and independent of prognostic value. (C) 2017 The Authors. Published by Elsevier Ireland Ltd.
Original language | English |
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Pages (from-to) | 147-153 |
Number of pages | 7 |
Journal | Radiotherapy and Oncology |
Volume | 125 |
Issue number | 1 |
DOIs | |
Publication status | Published - Oct 2017 |
Keywords
- Radiomics
- Oesophageal cancer
- Lung cancer
- Test-retest
- 4D-CT
- Feature stability
- PRIMARY ESOPHAGEAL CANCER
- DECISION-SUPPORT-SYSTEMS
- LEARNING HEALTH-CARE
- CELL LUNG-CANCER
- TUMOR HETEROGENEITY
- TEST-RETEST
- JUNCTIONAL CANCER
- TEXTURAL FEATURES
- F-18-FDG PET
- VARIABILITY