Reproducibility of Tumor Uptake Heterogeneity Characterization Through Textural Feature Analysis

18F-FDG PET measurement of standardized uptake value (SUV) is increasingly used for monitoring therapy response and predicting outcome. Alternative parameters computed through textural analysis were recently proposed to quantify the heterogeneity of tracer uptake by tumors as a significant predictor of response. The primary objective of this study was to evaluate the reproducibility of these heterogeneity mea-surements. Methods: Double baseline 18F-FDG PET scans were acquired within 4 d of each other for 16 patients before any treatment was considered. A Bland–Altman analysis was performed on 8 parameters based on histogram measure-ments and 17 parameters based on textural heterogeneity features after discretization with values between 8 and 128. Results: The reproducibility of maximum and mean SUV was similar to that in previously reported studies, with a mean percentage difference of 4.7 % 6 19.5 % and 5.5 % 6 21.2%, respectively. By comparison, better reproducibility was measured for some textural features describing local heterogeneity of tracer uptake, such as entropy and homoge-neity, with a mean percentage difference of 22 % 6 5.4 % and 1.8 % 6 11.5%, respectively. Several regional heterogeneity parameters such as variability in the intensity and size of regions of homogeneous activity distribution had reproduc-ibility similar to that of SUV measurements, with 95 % confi-dence intervals of 222.5 % to 3.1 % and 21.1 % to 23.5%, respectively. These parameters were largely insensitive to the discretization range. Conclusion: Several parameters de-rived from textural analysis describing heterogeneity of tracer uptake by tumors on local and regional scales had repro-ducibility similar to or better than that of simple SUV mea-surements. These reproducibility results suggest that these 18F-FDG PET–derived parameters, which have already been shown to have predictive and prognostic value in certain can-cer models, may be used to monitor therapy response and predict patient outcome