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Reproducibility of lung cancer radiomics features extracted from data-driven respiratory gating and free-breathing flow imaging in [18F]-FDG PET/CT.
Faist, Daphné; Jreige, Mario; Oreiller, Valentin; Nicod Lalonde, Marie; Schaefer, Niklaus; Depeursinge, Adrien; Prior, John O.
Afiliação
  • Faist D; Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital, Rue du Bugnon 46, CH-1011, Lausanne, Switzerland.
  • Jreige M; Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital, Rue du Bugnon 46, CH-1011, Lausanne, Switzerland.
  • Oreiller V; Institute of Information Systems, University of Applied Sciences Western Switzerland, (HES-SO), Rue du Technopôle 3, CH-3960, Sierre, Switzerland.
  • Nicod Lalonde M; Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital, Rue du Bugnon 46, CH-1011, Lausanne, Switzerland.
  • Schaefer N; Faculty of Biology and Medicine, University of Lausanne, Rue du Bugnon 21, CH-1011, Lausanne, Switzerland.
  • Depeursinge A; Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital, Rue du Bugnon 46, CH-1011, Lausanne, Switzerland.
  • Prior JO; Faculty of Biology and Medicine, University of Lausanne, Rue du Bugnon 21, CH-1011, Lausanne, Switzerland.
Eur J Hybrid Imaging ; 6(1): 33, 2022 Oct 30.
Article em En | MEDLINE | ID: mdl-36309636
ABSTRACT

BACKGROUND:

Quality and reproducibility of radiomics studies are essential requirements for the standardisation of radiomics models. As recent data-driven respiratory gating (DDG) [18F]-FDG has shown superior diagnostic performance in lung cancer, we evaluated the impact of DDG on the reproducibility of radiomics features derived from [18F]-FDG PET/CT in comparison to free-breathing flow (FB) imaging.

METHODS:

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 (Cb) 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 Cb < 0.8 and/or a mean difference percentage DIFF% > 10.

RESULTS:

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).

CONCLUSION:

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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Eur J Hybrid Imaging Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Eur J Hybrid Imaging Ano de publicação: 2022 Tipo de documento: Article