Comparison of tumor uptake heterogeneity characterization between static and parametric 18F-FDG PET images in Non-Small Cell Lung Cancer.

F. Tixier, D. Vriens, C. Cheze-Le Rest, M. Hatt, J. Disselhorst, W. Oyen, L. de Geus-Oei, E. Visser and D. Visvikis




(18)F-2-fluoro-2-deoxy-D-glucose ((18)F-FDG) positron emission tomography (PET) is well established in the field of oncology for diagnosis and staging purposes, while increasingly is being used for therapy response assessment and prognosis. Many quantitative indices can be used to characterize tumors in (18)F-FDG PET images, such as the maximum of standardized radiotracer uptake (SUVmax), metabolically active tumor volume (MATV), total lesion glycolysis (TLG) or more recently proposed intra-tumor uptake heterogeneity features. Although most PET data considered within this context concerns the analysis of activity distribution images obtained from one static acquisition, parametric images generated from dynamic acquisitions and reflecting radiotracer kinetics may provide additional information. The purpose of this study was to quantify differences between volumetric, uptake and heterogeneity features extracted from static and parametric PET images in non-small cell lung carcinoma (NSCLC) in order to provide insight on the potential added value of parametric images.Dynamic (18)F-FDG PET/CT acquisitions were performed in twenty therapy-naive NSCLC patients planned for primary surgical resection. Both static and parametric PET images were analyzed with quantitative parameters (MATV, SUVmax, SUVmean, heterogeneity) extracted from the segmented tumors. Differences were investigated using Spearman's rank correlation coefficients (rs) and Bland-Altman analysis.MATV was slightly smaller in static images (-2�7\%), but the difference was not significant (p=0.14). All derived parameters, including those characterizing tumor functional heterogeneity, were highly correlated between static and parametric images (rs=0.70-0.98, p?0.0006) exhibiting differences of <�25\%.In NSCLC primary tumors, parametric and static baseline (18)F-FDG PET images provided highly correlated quantitative features for both standard (MATV, SUVmax, SUVmean) and heterogeneity quantification. Consequently, heterogeneity quantification on parametric images does not seem to provide significant complementary information compared to static SUV images.

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