Abstract

Purpose: The tau tracer [18F]AV1451, also known as flortaucipir, is a promising ligand for imaging tau accumulation in Alzheimer’s disease (AD). Most of the previous studies have quantified tau load using standardized uptake value ratios (SUVr) derived from a static [18F]AV1451 scan. SUVr may, however, be flow dependent and, especially for longitudinal studies, should be validated against a fully quantitative approach. The objective of this study was to identify the optimal tracer kinetic model for measuring tau load using [18F]AV1451. Procedures: Following intravenous injection of 225 ± 16 MBq [18F]AV1451, 130 min dynamic PET scans were performed in five biomarker confirmed AD patients and five controls. Arterial blood sampling was performed to obtain a metabolite-corrected plasma input function. Next, regional time–activity curves were generated using PVElab software. These curves were analysed using several pharmacokinetic models. Results: The reversible single tissue compartment model (1T2k_VB) was the preferred model for all but one control. For AD patients, however, model preference shifted towards a reversible two tissue compartmental model (2T4k_VB). The simplified reference tissue model (SRTM) derived binding potential (BPND) showed good correlation (AD: r2 = 0.87, slope = 1.06; controls: r2 = 0.87, slope = 0.86) with indirect plasma input binding (distribution volume ratio-1). Standardized uptake value ratios (80–100 min) correlated well with DVR (r2 = 0.93, slope = 1.07) and SRTM-derived BPND (r2 = 0.84, slope = 0.95). In addition, regional differences in tracer binding between subject groups in different tau-specific regions were observed. Conclusions: Model preference of [18F]AV1451 appears to depend on subject status and, in particular, VT. The relationship between model preference and VT suggests that (higher) tau load may be reflected by a second tissue compartment. Nevertheless, consistent results can be obtained using a 2T4k_VB model. In addition, SRTM can be used to derive BPND.

Original languageEnglish
Pages (from-to)963-971
Number of pages9
JournalMolecular Imaging and Biology
Volume19
Issue number6
DOIs
Publication statusPublished - 1 Dec 2017

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