Characterization of [18F]flutemetamol binding properties : A β-amyloid PET imaging ligand

The criteria for diagnosing Alzheimer’s disease (AD) have recently been revised to include the use of biomarkers for the in vivo presence of β-amyloid, one of the neuropathological hallmarks of AD. Examples of such biomarkers are positron emission tomography (PET) β-amyloid specific ligands, including [18F]flutemetamol. The aim of this thesis was to characterize the binding properties of [18F]flutemetamol from a tracer kinetic perspective as well as by validating binding measures through comparison with tissue pathology assessments. The applicability of previously developed kinetic models of tracer binding for voxel-based analysis was examined and compared to arterial input compartment modelling, the “gold standard” for PET quantification. Several voxel-based methods were found to exhibit high correlations with compartment modelling, including the semi-quantitative standardized uptake value ratio (SUVR). The kinetic components of [18F]flutemetamol uptake were also investigated without model assumptions using the data driven method spectral analysis, with binding to β-amyloid shown to relate to a slow kinetic component. The same component was also found to predominate in the uptake of white matter, known to be free of β-amyloid accumulation. White matter uptake was however possible to separate from β-amyloid binding based on the relative contribution of the slow component to the total volume of distribution. Uptake of [18F]flutemetamol as quantified using SUVR or assessed visually was found to correlate well with tissue pathology assessments. Classifying the brains of 68 deceased subjects who had undergone [18F]flutemetamol PET scanning ante mortem, based on the spatial distribution of β-amyloid according to pre-defined phases, revealed that abnormal uptake patterns of [18F]flutemetamol were only certain to be found in the last phase of β-amyloid accumulation. In the same cohort however, [18F]flutemetamol was also shown to accurately distinguish between subjects with AD and non-AD dementia. While this supports the use of [18F]flutemetamol in clinical settings for ruling out AD, the association of abnormal [18F]flutemetamol uptake to late phases of β-amyloid accumulation may limit the detection of early accumulation and pre-clinical stages of AD. It remains to be investigated whether application of voxel-based methods and slow component filtering may increase sensitivity, particularly in the context of clinical trials