Sensitivity of radiomic features to inter-observer variability and image pre-processing in Apparent Diffusion Coefficient (ADC) maps of cervix cancer patients.
Apparent Diffusion Coefficient
Cervical cancer
MRI
Radiomics
Reproducibility
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:
02 2020
02 2020
Historique:
received:
24
06
2019
revised:
30
07
2019
accepted:
07
08
2019
pubmed:
4
9
2019
medline:
15
4
2021
entrez:
4
9
2019
Statut:
ppublish
Résumé
The aims of this study are to evaluate the stability of radiomic features from Apparent Diffusion Coefficient (ADC) maps of cervical cancer with respect to: (1) reproducibility in inter-observer delineation, and (2) image pre-processing (normalization/quantization) prior to feature extraction. Two observers manually delineated the tumor on ADC maps derived from pre-treatment diffusion-weighted Magnetic Resonance imaging of 81 patients with FIGO stage IB-IVA cervical cancer. First-order, shape, and texture features were extracted from the original and filtered images considering 5 different normalizations (four taken from the available literature, and one based on urine ADC) and two different quantization techniques (fixed-bin widths from 0.05 to 25, and fixed-bin count). Stability of radiomic features was assessed using intraclass correlation coefficient (ICC): poor (ICC < 0.75); good (0.75 ≤ ICC ≤ 0.89), and excellent (ICC ≥ 0.90). Dependencies of the features with tumor volume were assessed using Spearman's correlation coefficient (ρ). The approach using urine-normalized values together with a smaller bin width (0.05) was the most reproducible (428/552, 78% features with ICC ≥ 0.75); the fixed-bin count approach was the least (215/552, 39% with ICC ≥ 0.75). Without normalization, using a fixed bin width of 25, 348/552 (63%) of features had an ICC ≥ 0.75. Overall, 26% (range 25-30%) of the features were volume-dependent (ρ ≥ 0.6). None of the volume-independent shape features were found to be reproducible. Applying normalization prior to features extraction increases the reproducibility of ADC-based radiomics features. When normalization is applied, a fixed-bin width approach with smaller widths is suggested.
Identifiants
pubmed: 31477335
pii: S0167-8140(19)33047-6
doi: 10.1016/j.radonc.2019.08.008
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
88-94Informations de copyright
Copyright © 2019 The Author(s). Published by Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.