UNLABELLED: PET studies with biomarkers of regional neuronal activity (cerebral glucose metabolism or blood flow [CBF]) and amyloid-β (Aβ) depositions provide complementary information for the early diagnosis of dementia and follow-up of patients with dementia. We investigated the validity of relative regional CBF estimates (R(1)) gained from pharmacokinetic analyses of (11)C-labeled Pittsburgh compound B ((11)C-PIB) PET studies as a marker of neuronal activity and neurodegeneration. METHODS: Twenty-two patients with cognitive impairment (16 patients with early Alzheimer disease) underwent (18)F-FDG and (11)C-PIB PET studies for the assessment of regional glucose metabolism and Aβ load. Parametric images of R(1) (relative CBF) and binding potential (BP(ND); Aβ load) were generated by 2-step simplified reference tissue model (SRTM2) analyses of dynamic (11)C-PIB data. Volume-of-interest and voxel-based statistical analyses were performed to investigate the association between normalized (18)F-FDG uptake and (11)C-PIB R(1) and the correlation of these measures with symptom severity (Mini-Mental State Examination [MMSE] scores) in patients with Alzheimer disease. RESULTS: SRTM2 analyses provided high-quality (11)C-PIB R(1) images that were comparable to (18)F-FDG PET images. Regional (11)C-PIB R(1) values strongly correlated with normalized regional (18)F-FDG uptake when correlations were calculated separately for each patient (R(2) [mean ± SD], 0.73 ± 0.11) or across all regions of all patients (R(2), 0.62). A regression model including (18)F-FDG uptake, subject identification, and region grouping (into cortical, subcortical, and limbic regions to allow for possible differences in flow/metabolism coupling) accounted for 86% of total (11)C-PIB R(1) variability. Voxel-based correlation analyses of (18)F-FDG uptake and (11)C-PIB R(1) with MMSE scores revealed similar core findings of positive correlations in the posterior cingulate gyrus/precuneus and negative correlations (preserved activity) in the bilateral sensorimotor cortex. There was no correlation between Aβ load (BP(ND)) and MMSE scores. CONCLUSION: These results strongly suggest that (11)C-PIB R(1) can serve as a complementary biomarker of neuronal activity and, thus, neurodegeneration in addition to Aβ load given by (11)C-PIB BP(ND). Further studies are needed to validate the diagnostic value of dual-biomarker (11)C-PIB PET studies in comparison with combined (18)F-FDG and (11)C-PIB PET studies. Compared with the latter, dual-biomarker (11)C-PIB PET greatly reduces costs and burden for patients.
UNLABELLED: PET studies with biomarkers of regional neuronal activity (cerebral glucose metabolism or blood flow [CBF]) and amyloid-β (Aβ) depositions provide complementary information for the early diagnosis of dementia and follow-up of patients with dementia. We investigated the validity of relative regional CBF estimates (R(1)) gained from pharmacokinetic analyses of (11)C-labeled Pittsburgh compound B ((11)C-PIB) PET studies as a marker of neuronal activity and neurodegeneration. METHODS: Twenty-two patients with cognitive impairment (16 patients with early Alzheimer disease) underwent (18)F-FDG and (11)C-PIB PET studies for the assessment of regional glucose metabolism and Aβ load. Parametric images of R(1) (relative CBF) and binding potential (BP(ND); Aβ load) were generated by 2-step simplified reference tissue model (SRTM2) analyses of dynamic (11)C-PIB data. Volume-of-interest and voxel-based statistical analyses were performed to investigate the association between normalized (18)F-FDG uptake and (11)C-PIB R(1) and the correlation of these measures with symptom severity (Mini-Mental State Examination [MMSE] scores) in patients with Alzheimer disease. RESULTS: SRTM2 analyses provided high-quality (11)C-PIB R(1) images that were comparable to (18)F-FDG PET images. Regional (11)C-PIB R(1) values strongly correlated with normalized regional (18)F-FDG uptake when correlations were calculated separately for each patient (R(2) [mean ± SD], 0.73 ± 0.11) or across all regions of all patients (R(2), 0.62). A regression model including (18)F-FDG uptake, subject identification, and region grouping (into cortical, subcortical, and limbic regions to allow for possible differences in flow/metabolism coupling) accounted for 86% of total (11)C-PIB R(1) variability. Voxel-based correlation analyses of (18)F-FDG uptake and (11)C-PIB R(1) with MMSE scores revealed similar core findings of positive correlations in the posterior cingulate gyrus/precuneus and negative correlations (preserved activity) in the bilateral sensorimotor cortex. There was no correlation between Aβ load (BP(ND)) and MMSE scores. CONCLUSION: These results strongly suggest that (11)C-PIB R(1) can serve as a complementary biomarker of neuronal activity and, thus, neurodegeneration in addition to Aβ load given by (11)C-PIB BP(ND). Further studies are needed to validate the diagnostic value of dual-biomarker (11)C-PIB PET studies in comparison with combined (18)F-FDG and (11)C-PIB PET studies. Compared with the latter, dual-biomarker (11)C-PIB PET greatly reduces costs and burden for patients.
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