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Variability and Repeatability of Quantitative Uptake Metrics in 18F-FDG PET/CT of Non–Small Cell Lung Cancer: Impact of Segmentation Method, Uptake Interval, and Reconstruction Protocol

There is increased interest in various new quantitative uptake metrics beyond SUV in oncologic PET/CT studies. The purpose of this study was to investigate the variability and test–retest ratio (TRT) of metabolically active tumor volume (MATV) measurements and several other new quantitative metrics in non–small cell lung cancer using 18F-FDG PET/CT with different segmentation methods, user interactions, uptake intervals, and reconstruction protocols. Methods: Ten patients with advanced non–small cell lung cancer received 2 series of 2 whole-body 18F-FDG PET/CT scans at 60 min after injection and at 90 min after injection. PET data were reconstructed with 4 different protocols. Eight segmentation methods were applied to delineate lesions with and without a tumor mask. MATV, SUVmax, SUVmean, total lesion glycolysis, and intralesional heterogeneity features were derived. Variability and repeatability were evaluated using a generalized-estimating-equation statistical model with Bonferroni adjustment for multiple comparisons. The statistical model, including interaction between uptake interval and reconstruction protocol, was applied individually to the data obtained from each segmentation method. Results: Without masking, none of the segmentation methods could delineate all lesions correctly. MATV was affected by both uptake interval and reconstruction settings for most segmentation methods. Similar observations were obtained for the uptake metrics SUVmax, SUVmean, total lesion glycolysis, homogeneity, entropy, and zone percentage. No effect of uptake interval was observed on TRT metrics, whereas the reconstruction protocol affected the TRT of SUVmax. Overall, segmentation methods showing poor quantitative performance in one condition showed better performance in other (combined) conditions. For some metrics, a clear statistical interaction was found between the segmentation method and both uptake interval and reconstruction protocol. Conclusion: All segmentation results need to be reviewed critically. MATV and other quantitative uptake metrics, as well as their TRT, depend on segmentation method, uptake interval, and reconstruction protocol. To obtain quantitative reliable metrics, with good TRT performance, the optimal segmentation method depends on local imaging procedure, the PET/CT system, or reconstruction protocol. Rigid harmonization of imaging procedure and PET/CT performance will be helpful in mitigating this variability.