Silvia Morbelli1, Matteo Bauckneht2, Dario Arnaldi3, Agnese Picco3, Matteo Pardini3, Andrea Brugnolo3, Ambra Buschiazzo2, Marco Pagani4,5, Nicola Girtler3, Alberto Nieri2, Andrea Chincarini6, Fabrizio De Carli7, Gianmario Sambuceti2, Flavio Nobili3. 1. Nuclear Medicine Unit, IRCCS AOU San Martino, IST and Department of Health Sciences, University of Genoa, Largo R. Benzi 10, 16132, Genoa, Italy. silviadaniela.morbelli@hsanmartino.it. 2. Nuclear Medicine Unit, IRCCS AOU San Martino, IST and Department of Health Sciences, University of Genoa, Largo R. Benzi 10, 16132, Genoa, Italy. 3. Clinical Neurology, Department of Neuroscience (DINOGMI), University of Genoa and IRCCS AOU San Martino-IST, Genoa, Italy. 4. Institute of Cognitive Sciences and Technologies, CNR, Rome, Italy. 5. Department of Nuclear Medicine, Karolinska Hospital, Stockholm, Sweden. 6. Istituto Nazionale di Fisica Nucleare, Sezione di Genova, Genoa, Italy. 7. Institute of Bioimaging and Molecular Physiology, National Research Council, Genoa, Italy.
Abstract
PURPOSE: We aimed to identify the cortical regions where hypometabolism can predict the speed of conversion to dementia in mild cognitive impairment due to Alzheimer's disease (MCI-AD). METHODS: We selected from the clinical database of our tertiary center memory clinic, eighty-two consecutive MCI-AD that underwent 18F-fluorodeoxyglucose (FDG) PET at baseline during the first diagnostic work-up and were followed up at least until their clinical conversion to AD dementia. The whole group of MCI-AD was compared in SPM8 with a group of age-matched healthy controls (CTR) to verify the presence of AD diagnostic-pattern; then the correlation between conversion time and brain metabolism was assessed to identify the prognostic-pattern. Significance threshold was set at p < 0.05 False-Discovery-Rate (FDR) corrected at peak and at cluster level. Each MCI-AD was then compared with CTR by means of a SPM single-subject analysis and grouped according to presence of AD diagnostic-pattern and prognostic-pattern. Kaplan-Meier-analysis was used to evaluate if diagnostic- and/or prognostic-patterns can predict speed of conversion to dementia. RESULTS: Diagnostic-pattern corresponded to typical posterior hypometabolism (BA 7, 18, 19, 30, 31 and 40) and did not correlate with time to conversion, which was instead correlated with metabolic levels in right middle and inferior temporal gyri as well as in the fusiform gyrus (prognostic-pattern, BA 20, 21 and 38). At Kaplan-Meier analysis, patients with hypometabolism in the prognostic pattern converted to AD-dementia significantly earlier than patients not showing significant hypometabolism in the right middle and inferior temporal cortex (9 versus 19 months; Log rank p < 0.02, Breslow test: p < 0.003, Tarone-Ware test: p < 0.007). CONCLUSION: The present findings support the role of FDG PET as a robust progression biomarker even in a naturalist population of MCI-AD. However, not the AD-typical diagnostic-pattern in posterior regions but the middle and inferior temporal metabolism captures speed of conversion to dementia in MCI-AD since baseline. The highlighted prognostic pattern is a further, independent source of heterogeneity in MCI-AD and affects a primary-endpoint on interventional clinical trials (time of conversion to dementia).
PURPOSE: We aimed to identify the cortical regions where hypometabolism can predict the speed of conversion to dementia in mild cognitive impairment due to Alzheimer's disease (MCI-AD). METHODS: We selected from the clinical database of our tertiary center memory clinic, eighty-two consecutive MCI-AD that underwent 18F-fluorodeoxyglucose (FDG) PET at baseline during the first diagnostic work-up and were followed up at least until their clinical conversion to AD dementia. The whole group of MCI-AD was compared in SPM8 with a group of age-matched healthy controls (CTR) to verify the presence of AD diagnostic-pattern; then the correlation between conversion time and brain metabolism was assessed to identify the prognostic-pattern. Significance threshold was set at p < 0.05 False-Discovery-Rate (FDR) corrected at peak and at cluster level. Each MCI-AD was then compared with CTR by means of a SPM single-subject analysis and grouped according to presence of AD diagnostic-pattern and prognostic-pattern. Kaplan-Meier-analysis was used to evaluate if diagnostic- and/or prognostic-patterns can predict speed of conversion to dementia. RESULTS: Diagnostic-pattern corresponded to typical posterior hypometabolism (BA 7, 18, 19, 30, 31 and 40) and did not correlate with time to conversion, which was instead correlated with metabolic levels in right middle and inferior temporal gyri as well as in the fusiform gyrus (prognostic-pattern, BA 20, 21 and 38). At Kaplan-Meier analysis, patients with hypometabolism in the prognostic pattern converted to AD-dementia significantly earlier than patients not showing significant hypometabolism in the right middle and inferior temporal cortex (9 versus 19 months; Log rank p < 0.02, Breslow test: p < 0.003, Tarone-Ware test: p < 0.007). CONCLUSION: The present findings support the role of FDG PET as a robust progression biomarker even in a naturalist population of MCI-AD. However, not the AD-typical diagnostic-pattern in posterior regions but the middle and inferior temporal metabolism captures speed of conversion to dementia in MCI-AD since baseline. The highlighted prognostic pattern is a further, independent source of heterogeneity in MCI-AD and affects a primary-endpoint on interventional clinical trials (time of conversion to dementia).
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