Presentation Abstract

Session: Advances in PET Amyloid Imaging
Sunday, Jul 11, 2010, 1:00 PM - 3:00 PM
Presentation: O1-02-01 - Florbetaben for β-amyloid brain PET in Alzheimer disease - Results of a multicentre phase 2 trial
Pres. Time: Sunday, Jul 11, 2010, 1:00 PM - 1:15 PM
Location: Hall 1
Category: +New imaging methods
Author(s): Osama Sabri1, Hermann-Josef Gertz1, Stefan Dresel2, Isabella Heuser3, Peter Bartenstein4, Katharina Bürger4, Florian Hiemeyer5, Cornelia Reininger5, John Seibyl6, Henryk Barthel1.
1University of Leipzig, Leipzig, Germany, 2Helios Hospital Berlin-Buch, Berlin, Germany, 3Charite-Campus Benjamin Franklin, Berlin, Germany, 4Ludwig-Maximilian University Munich, Munich, Germany, 5Bayer Healthcare, Berlin, Germany, 6MNI, New Haven, CT, USA.
Abstract: Background:
Beta-amyloid (Aβ) PET has a great potential to facilitate early and accurate Alzheimer disease (AD) diagnosis and therapy monitoring. Florbetaben is a promising 18F-labeled Aβ-targeting PET tracer currently under global clinical development. This multicenter phase 2 trial aimed at determining the diagnostic efficacy of florbetaben in differentiating AD subjects from healthy controls (HCs).
In 18 centers on 3 continents, 150 subjects were recruited and imaged with florbetaben PET: 81 patients with probable AD (according to DSM-IV-TR und NINCDS-ADRDA criteria, age≥55yrs, MMSE=18-26, CDR=0.5-2) and 69 age-matched HCs (MMSE≥28, CDR=0). The PET data were visually analyzed by 3 blinded readers. Further, semi-quantitative analysis was carried out centralized by adapting a modified AAL volume of interest (VOI) template and obtaining SUV ratios (SUVRs, reference: cerebellar cortex). To optimize this VOI method, automated grey matter segmentation on the MRIs was carried out.
The florbetaben PET images of all subjects were judged as interpretable, with >95% of high image quality. According to visual analysis, the 90-110 min p.i. PET data were 80% sensitive and 90% specific in discriminating ADs from HCs, with high inter-reader agreement. VOI analysis of the 90-110 min p.i. PET data revealed significantly (p<0.0001) higher SUVRs for the ADs as compared to the HCs, in particular in frontal, laterotemporal, parietal, and cingulate cortices. Grey matter segmentation led to 10-22% improved SUVR discrimination between AD and HCs (p<0.0001) for cortical regions compared to the non-segmented approach. In AD patients, APOE4 alleles were found more frequently for the PET-positives as compared to the PET-negatives (65 vs. 22%, p=0.027). In the HCs, a similar trend (50 vs. 16%, p=0.074) was observed.
These results demonstrate that florbetaben brain PET achieves high accuracy in differentiating clinically diagnosed ADs from HCs. The correlations observed between the PET data and the APOE4 genotypes are consistent with preclinical data showing that florbetaben binds to Aβ. Taken together, florbetaben PET has a significant potential to become a valuable visual adjunct for improving the diagnosis of AD.
This trial was supported by Bayer Healthcare
Disclosures:   O. Sabri, Bayer Healthcare, Grants/Research Support; Bayer Healthcare, Consultant; H. Gertz, Bayer Healthcare, Grants/Research Support; S. Dresel, Bayer Healthcare, Grants/Research Support; I. Heuser, Bayer Healthcare, Grants/Research Support; P. Bartenstein, Bayer Healthcare, Grants/Research Support; K. Bürger, Bayer Healthcare, Grants/Research Support; F. Hiemeyer, Bayer Healthcare, Employee; C. Reininger, Bayer Healthcare, Employee; J. Seibyl, Bayer Healthcare, Grants/Research Support; H. Barthel, Bayer Healthcare, Consultant.
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