BACKGROUND: Cross-sectional imaging studies suggest that patterns of hypometabolism (measured by [(18)F] fluorodeoxyglucose positron emission tomography [FDG-PET]) and amyloid deposition (measured by [(11)C] Pittsburgh Compound B [PiB]- PET) in Alzheimer's disease (AD) show some overlap with each other. This indicates that neuronal dysfunction might spread within the anatomical pattern of amyloid deposition. The aim of this study was to examine longitudinal regional patterns of amyloid deposition and hypometabolism in the same population of mild AD subjects and to establish their regional relationship to each other. METHODS: Twenty patients with mild AD underwent baseline (BL) and follow-up (FU) examination with [(18)F] FDG-PET and [(11)C] PiB-PET. Voxel-by-voxel statistical group comparison (SPM5) was performed between patient BL- and FU-PET data as well as between patients and 15 PiB-negative elderly control subjects, who had undergone identical imaging procedures. To obtain objective measures of regional overlap, Dice similarity coefficients (DSC) between the imaging findings were calculated. RESULTS: Compared with elderly control subjects, AD patients showed typical patterns of BL hypometabolism and BL amyloid deposition, with a similarity of 40% (DSC). Amyloid deposition was more extended than hypometabolism at BL and showed only minor changes over time, whereas significant expansion of hypometabolism was observed, almost exclusively within areas already affected by BL amyloid deposition. Thus, increased similarity of FU hypometabolism with BL amyloid deposition was found (DSC: 47%). CONCLUSIONS: Longitudinal regional expansion of cerebral hypometabolism, as a measure of neuronal dysfunction in AD, seems to follow the anatomical pattern of amyloid deposition with temporal delay. This indicates that amyloid-based disruption of neuronal integrity might contribute to the regional expansion of neuronal dysfunction.
BACKGROUND: Cross-sectional imaging studies suggest that patterns of hypometabolism (measured by [(18)F] fluorodeoxyglucose positron emission tomography [FDG-PET]) and amyloid deposition (measured by [(11)C] Pittsburgh Compound B [PiB]- PET) in Alzheimer's disease (AD) show some overlap with each other. This indicates that neuronal dysfunction might spread within the anatomical pattern of amyloid deposition. The aim of this study was to examine longitudinal regional patterns of amyloid deposition and hypometabolism in the same population of mild AD subjects and to establish their regional relationship to each other. METHODS: Twenty patients with mild AD underwent baseline (BL) and follow-up (FU) examination with [(18)F] FDG-PET and [(11)C] PiB-PET. Voxel-by-voxel statistical group comparison (SPM5) was performed between patient BL- and FU-PET data as well as between patients and 15 PiB-negative elderly control subjects, who had undergone identical imaging procedures. To obtain objective measures of regional overlap, Dice similarity coefficients (DSC) between the imaging findings were calculated. RESULTS: Compared with elderly control subjects, ADpatients showed typical patterns of BL hypometabolism and BL amyloid deposition, with a similarity of 40% (DSC). Amyloid deposition was more extended than hypometabolism at BL and showed only minor changes over time, whereas significant expansion of hypometabolism was observed, almost exclusively within areas already affected by BL amyloid deposition. Thus, increased similarity of FU hypometabolism with BL amyloid deposition was found (DSC: 47%). CONCLUSIONS: Longitudinal regional expansion of cerebral hypometabolism, as a measure of neuronal dysfunction in AD, seems to follow the anatomical pattern of amyloid deposition with temporal delay. This indicates that amyloid-based disruption of neuronal integrity might contribute to the regional expansion of neuronal dysfunction.
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Authors: Clifford R Jack; David S Knopman; William J Jagust; Ronald C Petersen; Michael W Weiner; Paul S Aisen; Leslie M Shaw; Prashanthi Vemuri; Heather J Wiste; Stephen D Weigand; Timothy G Lesnick; Vernon S Pankratz; Michael C Donohue; John Q Trojanowski Journal: Lancet Neurol Date: 2013-02 Impact factor: 44.182
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Authors: L Glodzik; A Kuceyeski; H Rusinek; W Tsui; L Mosconi; Y Li; R S Osorio; S Williams; C Randall; N Spector; P McHugh; J Murray; E Pirraglia; S Vallabhajosula; A Raj; M J de Leon Journal: Neuroimage Date: 2014-07-04 Impact factor: 6.556