Tumor delineation using noninvasive medical imaging modalities is important to determine the target volume in radiation treatment planning and to evaluate treatment response. It is expected that combined use of CT and functional information from 18 F-FDG PET will improve tumor delineation. However, until now, tumor delineation using PET has been based on static images of 18 F-FDG standardized uptake values (SUVs). 18 F-FDG uptake depends not only on tumor physiology but also on blood supply, distribution volume, and competitive uptake processes in other tissues. Moreover, 18 F-FDG uptake in tumor tissue and in surrounding healthy tissue depends on the time after injection. Therefore, it is expected that the glucose metabolic rate (MR glu ) derived from dynamic PET scans gives a better representation of the tumor activity than does SUV. The aim of this study was to determine tumor volumes in MR glu maps and to compare them with the values from SUV maps. Methods: Twenty-nine lesions in 16 dynamic 18 F-FDG PET scans in 13 patients with non-small cell lung carcinoma were analyzed. MR glu values were calculated on a voxel-by-voxel basis using the standard 2-compartment 18 F-FDG model with trapping in the linear approximation (Patlak analysis). The blood input function was obtained by arterial sampling. Tumor volumes were determined in SUV maps of the last time frame and in MR glu maps using 3-dimensional isocontours at 50% of the maximum SUV and the maximum MR glu , respectively. Results: Tumor volumes based on SUV contouring ranged from 1.31 to 52.16 cm 3 , with a median of 8.57 cm 3 . Volumes based on MR glu ranged from 0.95 to 37.29 cm 3 , with a median of 3.14 cm 3 . For all lesions, the MR glu volumes were significantly smaller than the SUV volumes. The percentage differences (defined as 100% · (V MR glu 2 V SUV )/V SUV , where V is volume) ranged from 212.8% to 284.8%, with a median of 232.8%. Conclusion: Tumor volumes from MR glu maps were significantly smaller than SUV-based volumes. These findings can be of importance for PET-based radiotherapy planning and therapy response monitoring.