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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2022
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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 |
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author | Faist, Daphné Jreige, Mario Oreiller, Valentin Nicod Lalonde, Marie Schaefer, Niklaus Depeursinge, Adrien Prior, John O. |
author_facet | Faist, Daphné Jreige, Mario Oreiller, Valentin Nicod Lalonde, Marie Schaefer, Niklaus Depeursinge, Adrien Prior, John O. |
author_sort | Faist, Daphné |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9617997 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-96179972022-10-31 Reproducibility of lung cancer radiomics features extracted from data-driven respiratory gating and free-breathing flow imaging in [(18)F]-FDG PET/CT Faist, Daphné Jreige, Mario Oreiller, Valentin Nicod Lalonde, Marie Schaefer, Niklaus Depeursinge, Adrien Prior, John O. Eur J Hybrid Imaging Short Communication 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. Springer International Publishing 2022-10-30 /pmc/articles/PMC9617997/ /pubmed/36309636 http://dx.doi.org/10.1186/s41824-022-00153-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Short Communication Faist, Daphné Jreige, Mario Oreiller, Valentin Nicod Lalonde, Marie Schaefer, Niklaus Depeursinge, Adrien Prior, John O. Reproducibility of lung cancer radiomics features extracted from data-driven respiratory gating and free-breathing flow imaging in [(18)F]-FDG PET/CT |
title | Reproducibility of lung cancer radiomics features extracted from data-driven respiratory gating and free-breathing flow imaging in [(18)F]-FDG PET/CT |
title_full | Reproducibility of lung cancer radiomics features extracted from data-driven respiratory gating and free-breathing flow imaging in [(18)F]-FDG PET/CT |
title_fullStr | Reproducibility of lung cancer radiomics features extracted from data-driven respiratory gating and free-breathing flow imaging in [(18)F]-FDG PET/CT |
title_full_unstemmed | Reproducibility of lung cancer radiomics features extracted from data-driven respiratory gating and free-breathing flow imaging in [(18)F]-FDG PET/CT |
title_short | Reproducibility of lung cancer radiomics features extracted from data-driven respiratory gating and free-breathing flow imaging in [(18)F]-FDG PET/CT |
title_sort | reproducibility of lung cancer radiomics features extracted from data-driven respiratory gating and free-breathing flow imaging in [(18)f]-fdg pet/ct |
topic | Short Communication |
url | 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 |
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