Washout allometric reference method (WARM) for parametric analysis of [(11)C]PIB in human brains

Rapid clearance and disappearance of a tracer from the circulation challenges the determination of the tracer's binding potentials in brain (BP(ND)) by positron emission tomography (PET). This is the case for the analysis of the binding of radiolabeled [(11)C]Pittsburgh Compound B ([(11)C]PIB) to amyloid-β (Aβ) plaques in brain of patients with Alzheimer's disease (AD). To resolve the issue of rapid clearance from the circulation, we here introduce the flow-independent Washout Allometric Reference Method (WARM) for the analysis of washout and binding of [(11)C]PIB in two groups of human subjects, healthy aged control subjects (HC), and patients suffering from AD, and we compare the results to the outcome of two conventional analysis methods. We also use the rapid initial clearance to obtain a surrogate measure of the rate of cerebral blood flow (CBF), as well as a method of identifying a suitable reference region directly from the [(11)C]PIB signal. The difference of average absolute CBF values between the AD and HC groups was highly significant (P < 0.003). The CBF measures were not significantly different between the groups when normalized to cerebellar gray matter flow. Thus, when flow differences confound conventional measures of [(11)C]PIB binding, the separate estimates of CBF and BP(ND) provide additional information about possible AD. The results demonstrate the importance of data-driven estimation of CBF and BP(ND), as well as reference region detection from the [(11)C]PIB signal. We conclude that the WARM method yields stable measures of BP(ND) with relative ease, using only integration for noise reduction and no model regression. The method accounts for relative flow differences in the brain tissue and yields a calibrated measure of absolute CBF directly from the [(11)C]PIB signal. Compared to conventional methods, WARM optimizes the Aβ plaque load discrimination between patients with AD and healthy controls (P = 0.009).