Non–Small Cell Lung Cancer Treated with Erlotinib: Heterogeneity of<sup>18</sup>F-FDG Uptake at PET—Association with Treatment Response and Prognosis

Cook, Gary; O’Brien, Mary; Siddique, Muhammad; Chicklore, Sugama; Loi, Hoi Yin; Sharma, Bhupinder; Punwani, R.; Bassett, Paul; Goh, Vicky; Chua, Sue

doi:10.1148/radiol.2015141309

Cited by 145 publications

(130 citation statements)

References 33 publications

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“…Complexity, derived by the neighborhood gray-tone difference matrices, mainly represents a high degree of information content (i.e. an increased number of patches and primitives obtainable in the analyzed texture) [19]. Not surprisingly, Complexity derived by baseline PET portended inferior outcome with significantly reduced OS and trended towards significance for PFS in a ROC analysis (P = 0.07).…”

Section: Discussionmentioning

confidence: 98%

“…However, primarily SUV parameters (SUV peak , SUV max ) have been investigated for outcome prediction, e.g., in NSCLC treated with the TKI erlotinib [29][30][31]. Cook et al reported on heterogeneity assessment in NSCLC treated with the same TKI and the change of first-order parameters were correlated with survival [19]. However, due to a higher extent of voxel intensities, parameters of first-order intrinsically have a higher risk of association with SUV, particularly in patients with increased SUV max [19,26].…”

Section: Discussionmentioning

confidence: 99%

“…The following TF, which had been investigated in a previous study for outcome prediction in non-small cell lung cancer (NSCLC) patients under TKI treatment [19], were investigated: the first-order parameters Standard Deviation and Kurtosis, the second order parameters Entropy and Homogeneity as well as the higher-order parameters Busyness, Coarseness, Complexity, and Contrast. A detailed description can be found in [19].…”

Section: Image Interpretationmentioning

confidence: 99%

“…A detailed description can be found in [19]. In brief, first-order parameters inherit global textural features that relate to the gray level frequency distribution and are based on histogram analysis.…”

Section: Image Interpretationmentioning

confidence: 99%

“…Of note, intratumoral heterogeneity derived from in-vivo PET reflects the heterogeneity of tracer uptake assessed by exvivo autoradiography [13]. Clinically, intratumoral heterogeneity (tumor texture) analysis is currently gaining ground to serve as a potential risk stratification tool in a variety of different cancer entities [14][15][16][17][18][19]. Hence, not surprisingly, combined 18 F-FDG PET-based approaches (i.e., volumetric plus tumor texture assessment) for outcome prediction have also been investigated, e.g.…”

Section: Introductionmentioning

confidence: 99%

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Volumetric and texture analysis of pretherapeutic 18F-FDG PET can predict overall survival in medullary thyroid cancer patients treated with Vandetanib

Werner

Bundschuh²,

Higuchi

et al. 2018

Endocrine

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Purpose The metabolically most active lesion in 2-deoxy-2-( 18 F)fluoro-D-glucose ( 18 F-FDG) PET/CT can predict progression-free survival (PFS) in patients with medullary thyroid carcinoma (MTC) starting treatment with the tyrosine kinase inhibitor (TKI) vandetanib. However, this metric failed in overall survival (OS) prediction. In the present proof of concept study, we aimed to explore the prognostic value of intratumoral textural features (TF) as well as volumetric parameters (total lesion glycolysis, TLG) derived by pre-therapeutic 18 F-FDG PET. Methods Eighteen patients with progressive MTC underwent baseline 18 F-FDG PET/CT prior to and 3 months after vandetanib initiation. By manual segmentation of the tumor burden at baseline and follow-up PET, intratumoral TF and TLG were computed. The ability of TLG, imaging-based TF, and clinical parameters (including age, tumor marker doubling times, prior therapies and RET (rearranged during transfection) mutational status) for prediction of both PFS and OS were evaluated. Results The TF Complexity and the volumetric parameter TLG obtained at baseline prior to TKI initiation successfully differentiated between low-and high-risk patients. Complexity allocated 10/18 patients to the high-risk group with an OS of 3.3 y (vs. low-risk group, OS = 5.3 y, 8/18, AUC = 0.78, P = 0.03). Baseline TLG designated 11/18 patients to the high-risk group (OS = 3.5 y vs. low-risk group, OS = 5 y, 7/18, AUC = 0.83, P = 0.005). The Hazard Ratio for cancer-related death was 6.1 for Complexity (TLG, 9.5). Among investigated clinical parameters, the age at initiation of TKI treatment reached significance for PFS prediction (P = 0.02, OS, n.s.). Conclusions The TF Complexity and the volumetric parameter TLG are both independent parameters for OS prediction.

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Section: Discussionmentioning

confidence: 98%

Section: Discussionmentioning

confidence: 99%

Section: Image Interpretationmentioning

confidence: 99%

Section: Image Interpretationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Volumetric and texture analysis of pretherapeutic 18F-FDG PET can predict overall survival in medullary thyroid cancer patients treated with Vandetanib

Werner

Bundschuh²,

Higuchi

et al. 2018

Endocrine

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Making Molecular Imaging a Clinical Tool for Precision Oncology

et al. 2017

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Molecular imaging holds great promise for precision oncology, complementing tissue-based markers to guide more effective, less toxic, and more cost-effective cancer treatments. Beyond logistical and technical challenges, moving new imaging tests from the laboratory to the clinic requires a compelling use case that will benefit patients and/or improve cost-effectiveness, and it requires the collaboration of imagers, oncologists, and industry to reach its true clinical potential.

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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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Non–Small Cell Lung Cancer Treated with Erlotinib: Heterogeneity of¹⁸F-FDG Uptake at PET—Association with Treatment Response and Prognosis

Abstract: Response to erlotinib is associated with reduced heterogeneity at (18)F-FDG PET. Changes in first-order entropy are independently associated with OS and treatment response.

Cited by 145 publications

References 33 publications

Volumetric and texture analysis of pretherapeutic 18F-FDG PET can predict overall survival in medullary thyroid cancer patients treated with Vandetanib

Volumetric and texture analysis of pretherapeutic 18F-FDG PET can predict overall survival in medullary thyroid cancer patients treated with Vandetanib

Making Molecular Imaging a Clinical Tool for Precision Oncology

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

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Non–Small Cell Lung Cancer Treated with Erlotinib: Heterogeneity of18F-FDG Uptake at PET—Association with Treatment Response and Prognosis

Abstract: Response to erlotinib is associated with reduced heterogeneity at (18)F-FDG PET. Changes in first-order entropy are independently associated with OS and treatment response.

Cited by 145 publications

References 33 publications

Volumetric and texture analysis of pretherapeutic 18F-FDG PET can predict overall survival in medullary thyroid cancer patients treated with Vandetanib

Volumetric and texture analysis of pretherapeutic 18F-FDG PET can predict overall survival in medullary thyroid cancer patients treated with Vandetanib

Making Molecular Imaging a Clinical Tool for Precision Oncology

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

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Product

Resources

About

Non–Small Cell Lung Cancer Treated with Erlotinib: Heterogeneity of¹⁸F-FDG Uptake at PET—Association with Treatment Response and Prognosis

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