Quantification of [11C]CURB PET using an irreversible reference tissue model with a cluster-derived pseudo-reference region

IntroductionQuantification of [11C]CURB, an irreversible positron emission tomography (PET) radiopharmaceutical used to image fatty acid amide hydrolase (FAAH), requires invasive arterial sampling. Developing a non-invasive approach for [11C]CURB is challenging, since traditional reference region models are not directly applicable and the ubiquitous brain expression of FAAH complicates the identification of a ligand-free reference region. This study aimed to introduce and validate the irreversible reference tissue model (IRTM) used in conjunction with a data-driven, clustering-based white matter (WM) pseudo-reference region.MethodsIRTM was implemented using a coupled-fit approach to estimate a common k2′, resulting in two independent parameters per volume-of-interest: R1 and kf. Primary quantification was performed using the macroparameters Ri=Ki/K1′=R1⁢k3/kf (relative net influx) and R⁢k3=λ⁢k3/K1′=R1⁢k3/k2 (relative trapping index). Simulations characterized the sensitivity of IRTM to differences in cerebral blood volume between target and reference tissues. The model was validated against the gold standard arterial input function (AIF)-based quantification using retrospective [11C]CURB PET data from 10 healthy participants. A partition-based clustering algorithm was used to extract the centermost WM time-activity curve as a pseudo-reference region.ResultsIn the IRTM validation study with human data, Ri emerged as a more robust metric than Rk3, with the latter exhibiting high between-subject variability. Although simulations identified systematic biases in IRTM estimates driven by blood volume asymmetries, IRTM-derived Ri estimates showed strong concordance with AIF-based Ri (R2 = 0.96), λk3 (R2 = 0.90), and Ki (R2 = 0.96). Mean errors in Ri ranged from −11.2 ± 9.9% in the frontal lobe to −3.1 ± 10.4% in the amygdala. Voxel-wise parametric maps demonstrated high image quality and signal-to-noise ratio at the individual subject level.ConclusionThis study provides a validated, fully non-invasive framework for [11C]CURB PET quantification. Combined with a partition-based clustering approach to select a data-driven WM pseudo-reference region, IRTM achieved excellent concordance with AIF-based measurements, supporting the feasibility of IRTM for non-invasive FAAH imaging.