Monte-Carlo Modelling of a WristPET Scanner for Non-Invasive Measurement of the Arterial Input Function

Kinetic analysis of PET studies requires measurement of patient-specific arterial input function (PSAIF), an invasive and risky procedure. The aim of this study is to assess the feasibility to image-derive the AIF using a miniature wrist PET device (wristPET) using Monte Carlo (MC) simulation. The scanner hosted 11 rings, each with 80 detector modules. Each module is an array of 5×5 LSO crystals (1×1×20mm3). The scanner was simulated with axial FOV's of 15mm, 25mm, and 55mm to study the effect of system sensitivity on the accuracy of image-derived input function (IDIF). The wrist was simulated using a cylindrical phantom with a 3mm diameter line source positioned at 2.52 mm off-center to mimic the radial artery. Dynamic PET data were simulated using as input the Time-Activity-Curves of AIF and normal tissue background deduced from a [11C]-DPA-713 PET brain study. The PET images were reconstructed with CASTOR using MLEM algorithm with 4 subsets and up to 100 iterations. Logan VT kinetic modeling was performed for nine brain segments (white matter, cerebellum, thalamus, caudate, putamen, pallidum, brainstem, hippocampus and amygdala), using the PSAIF and the wristPET IDIF. We compared the IDIF and PSAIF using area under curve (AUC) and distribution volume (VT). Variability in VT was assessed for selected brain regions using Bland-Altman analysis. The results show that for all FOVs, the AUC_ratio, Peak_ratio and the % difference in VT consistently improves with increasing number of iterations. The 55mm FOV performed the best, mostly due to the increased system sensitivity compared to the 15mm and 25mm axial FOV's, with less deviation from the line of unity (1 for the AUC/Peak ratio, and 0 for % difference). Thirty iterations allowed reproducing the PSAIF-based VT values, for all the three axial FOV's, to within the limits of agreements (38%) that were previously determined from a test-retest [11C]-DPA-713 brain study. Our preliminary results show the feasibility to accurately recover the arterial input function from the wrist radial artery using a dedicated miniature wristPET.