Abstract

To identify a reliable alternative to the full blood [11C]PBR28 quantification method that would be easily replicated in multiple research and clinical settings. Ten [11C]PBR28 scans were acquired from 7 healthy non-human primates (NHP). Arterial input functions (AIFs) were averaged to create a population template input function (TIF). Population-based input functions were created by scaling the TIF with injected activity per body weight (PBIF) or unmetabolized tracer activity in blood at 15-,30-, and 60-min post-injection (PBIF15, PBIF30, and PBIF60). Two additional input functions were used: the native unmetabolized total plasma activity (Totals) and the Totals curve metabolite corrected by a scaled template parent fraction from a 30-min sample (TPF30-IF). Total distribution volumes (VTs) were calculated using PBIF, PBIF30, PBIF15, PBIF60, Totals, TPF30-IF, and the individual AIF (VTAIF). Distribution volume ratios (DVR) were computed using the cerebellum and the centrum semiovale (CSO), as pseudo-reference regions (DVRCereb, DVRCSO). Results obtained with each method were compared to VTAIF. Applicability of these alternative methods was tested on an independent pharmacological challenge dataset of microglial activation and depletion. Evaluation was carried at baseline, immediately after intervention (acute), and weeks post-intervention (post-recovery). VTs computed using PBIF15 and PBIF30 showed the best correlation to VTAIF (r > 0.90), while VT derived from the blood-free-scaled PBIF showed poor correlation (r = 0.46) and DVRCSO correlated the least (r = 0.26). In the pharmacological challenge study, most population-derived VT values were comparable to VTAIF at baseline and showed varied sensitivity to challenges at acute and post-recovery evaluation. DVR values did not detect relevant changes. Population-based input functions scaled with a single blood sample might be a useful alternative to using AIF to compute [11C]PBR28 binding in healthy NHPs or animals with comparable metabolism and overall perform better than pseudo-reference regions approaches.

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