Texture Feature Comparison Between Step-and-Shoot and Continuous-Bed-Motion <sup>18</sup>F-FDG PET

Yamashita, Shizuya; Okuda, Koichi; Nakaichi, Tetsu; Yamamoto, Hideya; Yokoyama, Keitaro

doi:10.2967/jnmt.120.246157

Cited by 2 publications

(3 citation statements)

References 25 publications

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“…The similar high reproducibility of PCA‐based DDG‐PET and SAM‐based DDG‐PET suggests the potential for interchangeability of texture features between other DDG‐PET methods and NG‐PET. In contrast, some texture features associated with GLRLM and GLZLM were not reproducible because these matrix indices, which are known to be highly variable, are calculated from large scales with many voxels 39,40 . In other words, non‐reproducible features are thought to be affected by blurring reduction due to the application of DDG.…”

Section: Discussionmentioning

confidence: 97%

“…In contrast, some texture features associated with GLRLM and GLZLM were not reproducible because these matrix indices, which are known to be highly variable, are calculated from large scales with many voxels. 39,40 In other words, non-reproducible features are thought to be affected by blurring reduction due to the application of DDG. From a different perspective, reproducibility confirmed in useful texture features such as GLCM Entropy and GLCM Dissimilarity is important.…”

Section: Discussionmentioning

confidence: 99%

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Reproducibility of the principal component analysis (PCA)‐based data‐driven respiratory gating on texture features in non‑small cell lung cancer patients with ¹⁸F‑FDG PET/CT

Fukai

Daisaki

Ishiyama

et al. 2023

J Applied Clin Med Phys

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Objective: Texture analysis is one of the lung cancer countermeasures in the field of radiomics. Even though image quality affects texture features, the reproducibility of principal component analysis (PCA)-based data-driven respiratory gating (DDG) on texture features remains poorly understood. Hence, this study aimed to clarify the reproducibility of PCA-based DDG on texture features in non-small cell lung cancer (NSCLC) patients with 18 F-Fluorodeoxyglucose ( 18 F-FDG) Positron emission tomography/computed tomography (PET/CT). Methods: Twenty patients with NSCLC who underwent 18 F-FDG PET/CT in routine clinical practice were retrospectively analyzed. Each patient's PET data were reconstructed in two PET groups of no gating (NG-PET) and PCAbased DDG gating (DDG-PET). Forty-six image features were analyzed using LIFEx software. Reproducibility was evaluated using Lin's concordance correlation coefficient (𝜌 c ) and percentage difference (%Diff). Non-reproducibility was defined as having unacceptable strength (𝜌 c < 0.8) and a %Diff of >10%. NG-PET and DDG-PET were compared using the Wilcoxon signed-rank test. Results: A total of 3/46 (6.5%) image features had unacceptable strength, and 9/46 (19.6%) image features had a %Diff of >10%. Significant differences between the NG-PET and DDG-PET groups were confirmed in only 4/46 (8.7%) of the high %Diff image features. Conclusion:Although the DDG application affected several texture features, most image features had adequate reproducibility. PCA-based DDG-PET can be routinely used as interchangeable images for texture feature extraction from NSCLC patients. K E Y W O R D S18F-FDG, data-driven respiratory gating, image feature, non-small cell lung cancer, PET/CT, texture analysis, texture featureThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Discussionmentioning

confidence: 97%

Section: Discussionmentioning

confidence: 99%

Reproducibility of the principal component analysis (PCA)‐based data‐driven respiratory gating on texture features in non‑small cell lung cancer patients with ¹⁸F‑FDG PET/CT

Fukai

Daisaki

Ishiyama

et al. 2023

J Applied Clin Med Phys

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“…In contrast to our reproducibility study, only a small fraction of radiomics features was considered as stable because radiomics features had varying values between the different respiratory patterns. Yamashita et al ( 2021 ) only looked at texture features derived from step-and-shoot and continuous bed motion [ 18 F]-FDG PET/CT. To see the influence between the two acquisitions, the mean difference percentage and correlation coefficient between the two derivations of radiomics features were calculated.…”

Section: Discussionmentioning

confidence: 99%

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

Faist

Jreige²,

Oreiller³

et al. 2022

European J Hybrid Imaging

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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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Texture Feature Comparison Between Step-and-Shoot and Continuous-Bed-Motion ¹⁸F-FDG PET

Cited by 2 publications

References 25 publications

Reproducibility of the principal component analysis (PCA)‐based data‐driven respiratory gating on texture features in non‑small cell lung cancer patients with ¹⁸F‑FDG PET/CT

Reproducibility of the principal component analysis (PCA)‐based data‐driven respiratory gating on texture features in non‑small cell lung cancer patients with ¹⁸F‑FDG PET/CT

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

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Texture Feature Comparison Between Step-and-Shoot and Continuous-Bed-Motion 18F-FDG PET

Cited by 2 publications

References 25 publications

Reproducibility of the principal component analysis (PCA)‐based data‐driven respiratory gating on texture features in non‑small cell lung cancer patients with 18F‑FDG PET/CT

Reproducibility of the principal component analysis (PCA)‐based data‐driven respiratory gating on texture features in non‑small cell lung cancer patients with 18F‑FDG PET/CT

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

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Texture Feature Comparison Between Step-and-Shoot and Continuous-Bed-Motion ¹⁸F-FDG PET

Reproducibility of the principal component analysis (PCA)‐based data‐driven respiratory gating on texture features in non‑small cell lung cancer patients with ¹⁸F‑FDG PET/CT

Reproducibility of the principal component analysis (PCA)‐based data‐driven respiratory gating on texture features in non‑small cell lung cancer patients with ¹⁸F‑FDG PET/CT