Automated Total-Body Perfusion Imaging with15O-Water PET Using Basis Functions and Organ-Specific Model Selection

Long-axial-field-of-view PET with 15O-water allows perfusion to be measured in the whole body simultaneously. The purpose of this work was to describe a method for automated computation of total-body parametric perfusion images using PET information only and to validate the perfusion and volume of distribution (V T) values obtained by comparing them with the gold standard (nonlinear regression analysis). Methods: Data from 10 subjects at Turku PET Centre were evaluated. Each subject underwent a 4-min 40-s dynamic PET/CT scan starting simultaneously with a controlled bolus administration of 350 MBq of 15O-water. Arterial and venous blood curves were defined using cluster analysis. Delay correction was performed by down-sampling the PET volume, using nonlinear regression for estimation of the delay for each subvolume, interpolation of delay values to the original matrix, and delay correction of all voxel time-activity curves, allowing for linearization of the model. Total-body perfusion images were calculated using several basis function implementations of the single-tissue-compartment model, considering the variations in blood supply to different organs. Model selection for each voxel was performed using cluster analysis to identify different organs. Perfusion and V T values based on the automated parametric imaging method were validated by comparison of mean organ values with nonlinear regression of the appropriate compartment models to whole-organ time-activity curves. Results: The results showed good agreement between the parameters achieved from the automated parametric images and nonlinear regression. Correlation (R 2) and agreement between linear and nonlinear analyses were high, with an R 2 of 0.99 for both perfusion and V T, with a slope of 0.98 and 1.01 for perfusion and V T, respectively. Conclusion: Perfusion and V T values based on automated total-body parametric analysis agreed well with those based on nonlinear regression of whole-organ time-activity curves.