Repeatability and reproducibility of MRI-based radiomic features in cervical cancer.
Cervical cancer
MRI
Radiomics
Repeatability
Reproducibility
T2-Weighted
Journal
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
ISSN: 1879-0887
Titre abrégé: Radiother Oncol
Pays: Ireland
ID NLM: 8407192
Informations de publication
Date de publication:
06 2019
06 2019
Historique:
received:
21
11
2018
revised:
02
03
2019
accepted:
04
03
2019
pubmed:
25
4
2019
medline:
24
3
2020
entrez:
25
4
2019
Statut:
ppublish
Résumé
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. 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). 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. 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.
Identifiants
pubmed: 31015155
pii: S0167-8140(19)30105-7
doi: 10.1016/j.radonc.2019.03.001
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
107-114Informations de copyright
Copyright © 2019 Elsevier B.V. All rights reserved.