No abstract

A major pathological hallmark of Alzheimer's disease is accumulation of amyloid-β in senile plaques in the brain. Evidence is accumulating that decreased clearance of amyloid-β from the brain may lead to these elevated amyloid-β levels. One of the clearance pathways of amyloid-β is transport across the blood-brain barrier via efflux transporters. P-glycoprotein, an efflux pump highly expressed at the endothelial cells of the blood-brain barrier, has been shown to transport amyloid-β. P-glycoprotein function can be assessed in vivo using (R)-[(11)C]verapamil and positron emission tomography. The aim of this study was to assess blood-brain barrier P-glycoprotein function in patients with Alzheimer's disease compared with age-matched healthy controls using (R)-[(11)C]verapamil and positron emission tomography. In 13 patients with Alzheimer's disease (age 65 ± 7 years, Mini-Mental State Examination 23 ± 3), global (R)-[(11)C]verapamil binding potential values were increased significantly (P = 0.001) compared with 14 healthy controls (aged 62 ± 4 years, Mini-Mental State Examination 30 ± 1). Global (R)-[(11)C]verapamil binding potential values were 2.18 ± 0.25 for patients with Alzheimer's disease and 1.77 ± 0.41 for healthy controls. In patients with Alzheimer's disease, higher (R)-[(11)C]verapamil binding potential values were found for frontal, parietal, temporal and occipital cortices, and posterior and anterior cingulate. No significant differences between groups were found for medial temporal lobe and cerebellum. These data show altered kinetics of (R)-[(11)C]verapamil in Alzheimer's disease, similar to alterations seen in studies where P-glycoprotein is blocked by a pharmacological agent. As such, these data indicate that P-glycoprotein function is decreased in patients with Alzheimer's disease. This is the first direct evidence that the P-glycoprotein transporter at the blood-brain barrier is compromised in sporadic Alzheimer's disease and suggests that decreased P-glycoprotein function may be involved in the pathogenesis of Alzheimer's disease.

Several methods are in use for analyzing 11 C-Pittsburgh compound-B ( 11 C-PiB) data. The objective of this study was to identify the method of choice for measuring longitudinal changes in specific 11 C-PiB binding. Methods: Dynamic 90-min 11 C-PiB baseline and follow-up scans (interval, 30 6 5 mo) were obtained for 7 Alzheimer disease (AD) patients, 11 patients with mild cognitive impairment (MCI), and 11 healthy controls. Parametric images were generated using reference parametric mapping (RPM2), reference Logan values, and standardized uptake value volume ratios (SUVr), the latter for intervals between 60 and 90 (SUVr 60-90 ) and 40 and 60 (SUVr 40-60 ) minutes after injection. In all analyses, cerebellar gray matter was used as a reference region. A global cortical volume of interest was defined using a probability map-based template. Percentage change between baseline and follow-up was derived for all analytic methods. Results: SUVr 60-90 and SUVr 40-60 overestimated binding with 13% and 10%, respectively, compared with RPM2. Reference Logan values were on average 6% lower than RPM2. Both SUVr measures showed high intersubject variability. Over time, R 1 , the delivery of tracer to the cortex relative to that to the cerebellum, decreased in AD patients (P , 0.05) but not in MCI patients and controls. Simulations showed that SUVr, but not RPM2 and reference Logan values, was highly dependent on uptake period and that changes in SUVr over time were sensitive to changes in flow. Conclusion: To reliably assess amyloid binding over time-for example, in drug intervention studies-it is essential to use fully quantitative methods for data acquisition and analysis.

The purpose of this study was to investigate the potential relationships between cerebrospinal fluid (CSF) measurements of b-amyloid-1-42 (Ab ) and total tau to 11 C-Pittsburgh compound B ( 11 C-PiB) and 2-(1-f6-[(2-18 F-fluoroethyl)(methyl)amino]-2-naphthylgethylidene) malononitrile ( 18 F-FDDNP) binding as measured using PET. Methods: A total of 37 subjects were included, consisting of 15 patients with Alzheimer disease (AD), 12 patients with mild cognitive impairment, and 10 healthy controls. All subjects underwent a lumbar puncture and PET using both 11 C-PiB and 18 F-FDDNP. For both PET tracers, parametric images of binding potential were generated. Potential associations of CSF levels of Ab 1-42 and tau with 11 C-PiB and 18 F-FDDNP binding were assessed using Pearson correlation coefficients and linear regression analyses. Results: For both global 11 C-PiB and 18 F-FDDNP binding, significant correlations with CSF levels of Ab 1-42 (r 5 20.72 and 20.37, respectively) and tau (r 5 0.58 and 0.56, respectively) were found across groups (all P , 0.001, except P , 0.05 for correlation between 18 F-FDDNP and Ab 1-42 ). Linear regression analyses showed that, adjusted for regional volume, age, sex, and diagnosis, global 11 C-PiB uptake had an inverse association with Ab 1-42 CSF levels (standardized b 5 20.50, P , 0.001), whereas there was a positive association between global 18 F-FDDNP binding and tau CSF levels (standardized b 5 0.62, P , 0.01). Conclusion: The good agreement between these 2 different types of biomarkers (i.e., CSF and PET) provides converging evidence for their validity. The inverse association between 11 C-PiB and CSF tau Ab 1-42 confirms that 11 C-PiB measures amyloid load in the brain. The positive association between 18 F-FDDNP and CSF tau suggests that at least part of the specific signal of 18 F-FDDNP in AD patients is due to tangle formation.

11 C-Pittsburgh Compound-B ( 11 C-PIB) and 18 F-(2-(1-f6-[(2-[ 18 F]fluoroethyl)(methyl)amino]-2-naphthylgethylidene) ( 18 F-FDDNP) have been developed as PET tracers for in vivo imaging of pathology in Alzheimer's disease (AD). The purpose of this study was to directly compare these tracers in patients with AD, patients with mild cognitive impairment (MCI), and healthy controls. Methods: Paired 11 C-PIB and 18 F-FDDNP scans were acquired in 14 patients with AD, 11 patients with amnestic MCI, and 13 controls. For both tracers, parametric images of binding potential (BP ND ) were generated. Global cortical BP ND was assessed using ANOVA. In addition, regional patterns of BP ND were compared between diagnostic groups using ANOVA for repeated measures. Results: Global cortical BP ND of 11 C-PIB showed higher binding in patients with AD than in controls and patients with MCI. 18 F-FDDNP uptake was higher in patients with AD than in controls, but MCI could not be distinguished from AD or from controls. Global BP ND values of both tracers were moderately correlated (r 5 0.45; P 5 0.005). In MCI, BP ND of 11 C-PIB showed a bimodal distribution, whereas values for 18 F-FDDNP were more widespread, with more MCI patients demonstrating increased uptake. Regional 11 C-PIB binding showed different patterns across diagnostic groups, as AD patients showed an overall increase in binding, with the lowest binding in the medial temporal lobe. With 18 F-FDDNP, patterns were similar across diagnostic groups. For all groups, highest values were observed in the medial temporal lobe. Conclusion: Differences in BP ND between patients with AD, patients with MCI, and controls were more pronounced for 11 C-PIB. The difference in regional binding, the moderate correlation, and the discrepant findings in MCI suggest that they measure related, but different, characteristics of the disease.