Repeatability and reproducibility of MRI-based radiomic features in cervical cancer

Purpose: The aims of this study are to evaluate the stability of radiomic features from T2-weighted MRI of cervical cancer in three ways: (1) repeatability via test-retest; (2) reproducibility between diagnostic MRI and simulation MRI; (3) reproducibility in inter-observer setting.

Materials and methods: This retrospective cohort study included FIGO stage IB-IVA cervical cancer patients treated with chemoradiation between 2005 and 2014. There were three cohorts of women corresponding to each aim of the study: (1) 8 women who underwent test-retest MRI; (2) 20 women who underwent MRI on different scanners (diagnostic and simulation MRI); (3) 34 women whose diagnostic MRIs were contoured by three observers. Radiomic features based on first-order statistics, shape features and texture features were extracted from the original, Laplacian of Gaussian (LoG)-filtered and wavelet-filtered images, for a total of 1761 features. Stability of radiomic features was assessed using intraclass correlation coefficient (ICC).

Results: The inter-observer cohort had the most reproducible features (95.2% with ICC >= 0.75) whereas the diagnostic-simulation cohort had the fewest (14.1% with ICC >= 0.75). Overall, 229 features had ICC >= 0.75 in all three tests. Shape features emerged as the most stable features in all cohorts.

Conclusion: The diagnostic-simulation test resulted in the fewest reproducible features. Further research in MRI-based radiomics is required to validate the use of reproducible features in prognostic models. (C) 2019 Elsevier B.V. All rights reserved.