Total-Body PET Multiparametric Imaging of Cancer Using a Voxel-wise Strategy of Compartmental Modeling

Abstract

Quantitative dynamic PET with compartmental modeling has the potential to enable multiparametric imaging and more accurate quantification as compared to static PET imaging. Conventional methods for parametric imaging commonly use a single kinetic model for all image voxels and neglect the heterogeneity of physiological models, which can work well for single-organ parametric imaging but may significantly compromise total-body parametric imaging on long axial field-of-view scanners. In this paper, we evaluate the necessity of voxel-wise compartmental modeling strategies, including time delay correction and model selection, for total-body multiparametric imaging. Methods: Ten subjects (5 patients with metastatic cancer and 5 healthy volunteers) were scanned on the uEXPLORER total-body PET/CT system following injection of 370 MBq ¹⁸F-fluorodeoxyglucose (FDG). Dynamic data were acquired for 60 minutes. Total-body parametric imaging was performed using two approaches. One is the conventional method that uses a single irreversible two-tissue compartmental model with and without time delay correction. The second approach selects the best kinetic model from three candidate models for individual voxels. The differences between the two approaches were evaluated for parametric imaging of micro kinetic parameters and FDG net influx rate K_i. Results: Time delay correction had a non-negligible effect on kinetic quantification of various organs and lesions. The effect was larger in lesions with higher blood volume. Parametric imaging of K_i with the standard two-tissue model introduced artifacts in vascular regions, which was overcome by the voxel-wise model selection strategy. Conclusion: The time delay and appropriate kinetic model vary in different organs and lesions. Modeling of the time delay of the blood input function and model selection improved total-body multiparametric imaging.