Cargando…

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

BACKGROUND: Quality and reproducibility of radiomics studies are essential requirements for the standardisation of radiomics models. As recent data-driven respiratory gating (DDG) [(18)F]-FDG has shown superior diagnostic performance in lung cancer, we evaluated the impact of DDG on the reproducibil...

Descripción completa

Detalles Bibliográficos
Autores principales: Faist, Daphné, Jreige, Mario, Oreiller, Valentin, Nicod Lalonde, Marie, Schaefer, Niklaus, Depeursinge, Adrien, Prior, John O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9617997/
https://www.ncbi.nlm.nih.gov/pubmed/36309636
http://dx.doi.org/10.1186/s41824-022-00153-2
Descripción
Sumario:BACKGROUND: Quality and reproducibility of radiomics studies are essential requirements for the standardisation of radiomics models. As recent data-driven respiratory gating (DDG) [(18)F]-FDG has shown superior diagnostic performance in lung cancer, we evaluated the impact of DDG on the reproducibility of radiomics features derived from [(18)F]-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 (C(b)) 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(b)  < 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s41824-022-00153-2.