Objectives: Metabolically active tumor volume (MATV) and tumor activity distribution heterogeneity parameters derived from 18F-FDG PET images were recently shown to have an impact in patient management. In all of these studies, static FDG-PET images were exclusively considered. However, images of the glucose metabolic rate (MRGlu) obtained from dynamic PET acquisitions may contain more accurate information. The objective of this study was to compare MATV and tumor heterogeneity parameters extracted from these two different types of images. Methods: 20 patients with diagnosed non-small cell lung cancer (NSCLC) were enrolled in this retrospective study. All of these patients underwent a dynamic 18F-FDG PET scan which was acquired prior to therapy. Primary tumor delineation was performed using adaptive thresholding and a fuzzy locally adaptive Bayesian algorithm (FLAB). Image derived parameters considered in this study included MATV, heterogeneity (based on textural features and cumulative histogram), coefficient of covariance and tumor lesion glycolysis. Pearson's correlation coefficient and Wilcoxon test were used in the comparison. P-values <0.05 were considered as statistically significant. Results: No statistically significant differences were measured on MATV between the MRGlu and static FDG images for the two segmentation methods considered. Although not statistically significant, differences between the two images concerning the heterogeneity parameters at a local scale were larger than differences observed on regional and global heterogeneity parameters. Conclusions: MRGlu and static images result in NSCLC tumor volume and activity distribution heterogeneity parameters which are not different. Therefore, a dynamic 18F-FDG PET acquisition and subsequent MRGlu maps may not provide any additional information concerning the extraction of these specific image derived parameters and their subsequent impact in patient management.