Image Derived Input Function for [(18)F]-FEPPA: Application to Quantify Translocator Protein (18 kDa) in the Human Brain

In [(18)F]-FEPPA positron emission topography (PET) imaging, automatic blood sampling system (ABSS) is currently the gold standard to obtain the blood time activity curve (TAC) required to extract the input function (IF). Here, we compare the performance of two image-based methods of IF extraction to the ABSS gold standard method for the quantification of translocator protein (TSPO) in the human brain. The IFs were obtained from a direct delineation of the internal carotid signal (CS) and a new concept of independent component analysis (ICA). PET scans were obtained from 18 healthy volunteers. The estimated total distribution volume (V(T)) by CS-IF and ICA-IF were compared to the reference V(T) obtained by ABSS-IF in the frontal and temporal cortex, cerebellum, striatum and thalamus regions. The V(T) values estimated using ICA-IF were more reliable than CS-IF for all brain regions. Specifically, the slope regression in the frontal cortex with ICA-IF was r(2) = 0.91 (p<0.05), and r(2) = 0.71 (p<0.05) using CS-IF.