Repeatability and reproducibility of MRI-based radiomic features in cervical cancer. (June 2019)

• Record Type: Journal Article
• Authors: Fiset, Sandra; Welch, Mattea L.; Weiss, Jessica; Pintilie, Melania; Conway, Jessica L.; Milosevic, Michael; Fyles, Anthony; Traverso, Alberto; Jaffray, David; Metser, Ur; Xie, Jason; Han, Kathy
• Is Part Of: Radiotherapy and oncology. Volume 135(2019)
• Page Start: 107
• Page End: 114
• Publication Date: 2019-06
• Subjects: ICC intraclass correlation coefficient -- LoG Laplacian of Gaussian -- GLCM gray-level co-occurrence matrix -- GLSZM gray-level size zone matrix -- GLDM gray-level dependence matrix -- GLRLM gray-level run length matrix -- NGTDM neighboring gray tone difference matrix -- NSCLC non-small cell lung cancer; Radiomics -- MRI -- T2-Weighted -- Cervical cancer -- Repeatability -- Reproducibility; Oncology -- Periodicals; Radiotherapy -- Periodicals; Tumors -- Periodicals; Medical Oncology -- Periodicals; Neoplasms -- radiotherapy -- Periodicals; Radiotherapy -- Periodicals; Radiothérapie -- Périodiques; Cancérologie -- Périodiques; Tumeurs -- Périodiques; Electronic journals; 616.9940642
• DOI: 10.1016/j.radonc.2019.03.001
• Languages: English
• ISSNs: 0167-8140

Abstract

Highlights: This study examined the stability of radiomic features from T2-weighted MRI of cervical cancer. Three tests were applied: 1. test–retest; 2. diagnostic vs simulation MRI; and 3. inter-observer delineation. The inter-observer cohort had the greatest number of reproducible features. The diagnostic–simulation cohort had the fewest reproducible features. Shape features were the most stable features in all three cohorts. Abstract: 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.