Technical Report: Time-Activity-Curve Integration in Lu-177 Therapies in Nuclear Medicine

Abstract

Currently, there is a high interest in Lu-177 targeted radionuclide therapies, which could be attributed to favourable results obtained from Lu-177 compounds targeting neuroendocrine and prostate tumours. Generally, it has been recognized that a transition from dosimetry based on planar images towards based on fully-quantitative SPECT is beneficial in terms of increased accuracy. SPECT based dosimetry could not only be used for achieving accurate absorbed dose per-organ, but even for deriving dose values for individual voxels. However, a voxel-wise determination of TACs is problematic since several confounding factors exist, such as e.g. poor count-statistics or registration inaccuracies. A particle filter (PF) is a class of methods which applies regularization based on a model of a state's evolution over time. We applied PFs for de-noising the TACs of 26 patients, who underwent Lu-177-DOTATOC or -PSMA therapy. The TACs were obtained from four serial SPECT(/CT) data. The model used in the PF was a mono-exponential decay. The time-integrated activities (TIA) resulting from the PF were compared to the results of a monoexponential fit of the individual voxels in several volumes of interest. Optimal values for noise of observations and noise of the model were 0.25 and 0.5, respectively. The distribution of voxel-wise halflives resulting from the PFFit method were considerably closer to the organ average value and the number of implausibly long halflives was reduced. However, one has to admit that voxel-wise fitting generally lead to considerable deviations from the organ-average TIA as obtained by conventional whole-organ evaluation. Unfortunately, we did not have ground-truth TIA of our patient data and proper ground-truth could even be impossible to obtain. Nevertheless, there are strong indicators that Particle Filtering can be used for reducing voxel-wise TAC noise.