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

Sandra Fiset, Mattea L. Welch, Jessica Weiss, Melania Pintilie, Jessica L. Conway, Michael Milosevic, Anthony Fyles, Alberto Traverso, David Jaffra, Ur Metser, Jason Xie, Kathy Han*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

78 Citations (Web of Science)

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. (C) 2019 Elsevier B.V. All rights reserved.

Original languageEnglish
Pages (from-to)107-114
Number of pages8
JournalRadiotherapy and Oncology
Volume135
DOIs
Publication statusPublished - Jun 2019

Keywords

  • Radiomics
  • MRI
  • T2-Weighted
  • Cervical cancer
  • Repeatability
  • Reproducibility
  • INTEROBSERVER DELINEATION VARIABILITY
  • TEST-RETEST
  • FEATURE STABILITY
  • TEXTURE ANALYSIS
  • RELIABILITY
  • PARAMETERS
  • IMAGES
  • TUMORS

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