[11C]arachidonic acid incorporation measurement in human brain: Optimization for clinical use
Diabetes Mellitus, Type 2
Arachidonic acid (AA) is involved in signal transduction, neuroinflammation, and production of eicosanoid metabolites. The AA brain incorporation coefficient (K*) is quantifiable in vivo using [11 C]AA positron emission tomography, although repeatability remains undetermined. We evaluated K* estimates obtained with population-based metabolite correction (PBMC) and image-derived input function (IDIF) in comparison to arterial blood-based estimates, and compared repeatability. Eleven healthy volunteers underwent a [11 C]AA scan; five repeated the scan 6 weeks later, simulating a pre- and post-treatment study design. For all scans, arterial blood was sampled to measure [11 C]AA plasma radioactivity. Plasma [11 C]AA parent fraction was measured in 5 scans. K* was quantified using both blood data and IDIF, corrected for [11 C]AA parent fraction using both PBMC (from published values) and individually measured values (when available). K* repeatability was calculated in the test-retest subset. K* estimates based on blood and individual metabolites were highly correlated with estimates using PBMC with arterial input function (r = 0.943) or IDIF (r = 0.918) in the subset with measured metabolites. In the total dataset, using PBMC, IDIF-based estimates were moderately correlated with arterial input function-based estimates (r = 0.712). PBMC and IDIF-based K* estimates were ∼6.4% to ∼11.9% higher, on average, than blood-based estimates. Average K* test-retest absolute percent difference values obtained using blood data or IDIF, assuming PBMC for both, were between 6.7% and 13.9%, comparable to other radiotracers. Our results support the possibility of simplified [11 C]AA data acquisition through eliminating arterial blood sampling and metabolite analysis, while retaining comparable repeatability and validity.