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PurposeThe input function (IF) is a core element in the quantification of Translocator protein 18 kDa with positron emission tomography (PET), as no suitable reference region with negligible binding has been identified. Arterial blood sampling is indeed needed to create the IF (ASIF). In the present manuscript we study individualization of a population based input function (PBIF) with a single arterial manual sample to estimate total distribution volume (VT) for [18F]FEPPA and to replicate previously published clinical studies in which the ASIF was used.MethodsThe data of 3 previous [18F]FEPPA studies (39 of healthy controls (HC), 16 patients with Parkinson’s disease (PD) and 18 with Alzheimer’s disease (AD)) was reanalyzed with the new approach. PBIF was used with the Logan graphical analysis (GA) neglecting the vascular contribution to estimate VT. Time of linearization of the GA was determined with the maximum error criteria. The optimal calibration of the PBIF was determined based on the area under the curve (AUC) of the IF and the agreement range of VT between methods. The shape of the IF between groups was studied while taking into account genotyping of the polymorphism (rs6971).ResultsPBIF scaled with a single value of activity due to unmetabolized radioligand in arterial plasma, calculated as the average of a sample taken at 60 min and a sample taken at 90 min post-injection, yielded a good interval of agreement between methods and optimized the area under the curve of IF. In HC, gray matter VTs estimated by PBIF highly correlated with those using the standard method (r2 = 0.82, p = 0.0001). Bland-Altman plots revealed PBIF slightly underestimates (~1 mL/cm3) VT calculated by ASIF (including a vascular contribution). It was verified that the AUC of the ASIF were independent of genotype and disease (HC, PD, and AD). Previous clinical results were replicated using PBIF but with lower statistical power.ConclusionA single arterial blood sample taken 75 minute post-injection contains enough information to individualize the IF in the groups of subjects studied; however, the higher variability produced requires an increase in sample size to reach the same effect size.

Amnestic mild cognitive impairment (aMCI) is defined as a transitional state between normal aging and Alzheimer's disease (AD). Given the replicated finding of increased microglial activation in AD, we sought to investigate whether microglial activation is also elevated in aMCI and whether it is related to amyloid beta (Aβ) burden in-vivo . Eleven aMCI participants and 14 healthy volunteers completed positron emission tomography (PET) scans with [F]-FEPPA and [C]-PIB. Given the known sensitivity in affinity of second-generation TSPO radioligands, participants were genotyped for the TSPO polymorphism and only high-affinity binders were included. Dynamic [F]-FEPPA PET images were analyzed using the 2-tissue compartment model with arterial plasma input function. Additionally, a supplementary method, the standardized uptake value ratio (SUVR), was explored. [C]-PIB PET images were analyzed using the Logan graphical method. aMCI participants had significantly higher [C]-PIB binding in the cortical regions. No significant differences in [F]-FEPPA binding were observed between aMCI participants and healthy volunteers. In the aMCI group, [F]-FEPPA and [C]-PIB bindings were correlated in the hippocampus. There were no correlations between our PET measures and cognition. Our findings demonstrate that while Aβ burden is evident in the aMCI stage, microglial activation may not be present.