Direct parametric reconstruction for dynamic [18F]-FDG PET/CT imaging in the body

Abdominal and thoracic [¹⁸F]FDG PET/CT imaging is routinely used in clinical practice and drug development but parametric imaging based on full kinetic analysis is rarely used due to noise induced bias and variance in kinetic parameters and analysis is usually restricted to semi-quantitative indices. Direct parametric estimation using 4D image reconstruction can potentially provide parametric maps of reduced bias and variance but little or no evaluation has been done in the body. Previous studies have demonstrated that body [¹⁸F]FDG PET/CT imaging can benefit from these methods but analysis was restricted to macroparameters of interest. In work, we implement and apply a recently proposed direct 4-D algorithm using a 2 tissue compartment model on simulated and real oncology [¹⁸F]FDG PET/CT data to directly estimate microparameters of interest and assess potential improvements over the traditional post-reconstruction kinetic analysis. Results on the simulated data suggest clear reduction in bias for K₁, k₂ and blood volume and less for k₃. Similarly, variance reduction was observed for K₁, k₂, k₃ and K_i and less for blood volume. Evaluation on patient data demonstrated similar improvements using the direct 4-D method in agreement with simulations.