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J Cereb Blood Flow Metab. 2005 Nov;25(11):1528-47.

Kinetic modeling of amyloid binding in humans using PET imaging and Pittsburgh Compound-B.

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  • 1Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15213, USA. pricejc@upmc.edu

Abstract

A valid quantitative imaging method for the measurement of amyloid deposition in humans could improve Alzheimer's disease (AD) diagnosis and antiamyloid therapy assessment. Our group developed Pittsburgh Compound-B (PIB), an amyloid-binding radiotracer, for positron emission tomography (PET). The current study was aimed to further validate PIB PET through quantitative imaging (arterial input) and inclusion of subjects with mild cognitive impairment (MCI). Pittsburgh Compound-B studies were performed in five AD, five MCI, and five control subjects and five subjects were retested within 20 days. Magnetic resonance images were acquired for partial volume correction and region-of-interest definition (e.g., posterior cingulate: PCG; cerebellum: CER). Data were analyzed using compartmental and graphical approaches. Regional distribution volume (DV) values were normalized to the reference region (CER) to yield DV ratios (DVRs). Good agreement was observed between compartmental and Logan DVR values (e.g., PCG: r=0.89, slope=0.91); the Logan results were less variable. Nonspecific PIB retention was similar across subjects (n=15, Logan CER DV: 3.63+/-0.48). Greater retention was observed in AD cortical areas, relative to controls (P<0.05). The PIB retention in MCI subjects appeared either 'AD-like' or 'control-like'. The mean test/retest variation was approximately 6% in primary areas-of-interest. The Logan analysis was the method-of-choice for the PIB PET data as it proved stable, valid, and promising for future larger studies and voxel-based statistical analyses. This study also showed that it is feasible to perform quantitative PIB PET imaging studies that are needed to validate simpler methods for routine use across the AD disease spectrum.

PMID:
15944649
[PubMed - indexed for MEDLINE]
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