Reproducibility of lung cancer radiomics features extracted from data-driven respiratory gating and free-breathing flow imaging in [18F]-FDG PET/CT.

Détails

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Etat: Public
Version: Final published version
Licence: CC BY 4.0
ID Serval
serval:BIB_B5DE6B69D4AD
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Reproducibility of lung cancer radiomics features extracted from data-driven respiratory gating and free-breathing flow imaging in [18F]-FDG PET/CT.
Périodique
European journal of hybrid imaging
Auteur⸱e⸱s
Faist D., Jreige M., Oreiller V., Nicod Lalonde M., Schaefer N., Depeursinge A., Prior J.O.
ISSN
2510-3636 (Electronic)
ISSN-L
2510-3636
Statut éditorial
Publié
Date de publication
30/10/2022
Peer-reviewed
Oui
Volume
6
Numéro
1
Pages
33
Langue
anglais
Notes
Publication types: Journal Article
Publication Status: epublish
Résumé
Quality and reproducibility of radiomics studies are essential requirements for the standardisation of radiomics models. As recent data-driven respiratory gating (DDG) [ <sup>18</sup> F]-FDG has shown superior diagnostic performance in lung cancer, we evaluated the impact of DDG on the reproducibility of radiomics features derived from [ <sup>18</sup> F]-FDG PET/CT in comparison to free-breathing flow (FB) imaging.
Twenty four lung nodules from 20 patients were delineated. Radiomics features were derived on FB flow PET/CT and on the corresponding DDG reconstruction using the QuantImage v2 platform. Lin's concordance factor (C <sub>b</sub> ) and the mean difference percentage (DIFF%) were calculated for each radiomics feature using the delineated nodules which were also classified by anatomical localisation and volume. Non-reproducible radiomics features were defined as having a bias correction factor C <sub>b</sub> < 0.8 and/or a mean difference percentage DIFF% > 10.
In total 141 features were computed on each concordance analysis, 10 of which were non-reproducible on all pulmonary lesions. Those were first-order features from Laplacian of Gaussian (LoG)-filtered images (sigma = 1 mm): Energy, Kurtosis, Minimum, Range, Root Mean Squared, Skewness and Variance; Texture features from Gray Level Cooccurence Matrix (GLCM): Cluster Prominence and Difference Variance; First-order Standardised Uptake Value (SUV) feature: Kurtosis. Pulmonary lesions located in the superior lobes had only stable radiomics features, the ones from the lower parts had 25 non-reproducible radiomics features. Pulmonary lesions with a greater size (defined as long axis length > median) showed a higher reproducibility (9 non-reproducible features) than smaller ones (20 non-reproducible features).
Calculated on all pulmonary lesions, 131 out of 141 radiomics features can be used interchangeably between DDG and FB PET/CT acquisitions. Radiomics features derived from pulmonary lesions located inferior to the superior lobes are subject to greater variability as well as pulmonary lesions of smaller size.
Mots-clé
Radiology, Nuclear Medicine and imaging, Molecular Medicine, Biophysics, Computer Science (miscellaneous), Data-driven gating, Data-driven respiratory gating, Lung PET/CT, PET/CT, Pulmonary nodule, Radiomics features, Reproducibility, Respiratory gating, [18F]-FDG
Pubmed
Web of science
Open Access
Oui
Création de la notice
31/10/2022 15:33
Dernière modification de la notice
23/01/2024 8:33
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