RT Journal Article
SR Electronic
T1 Progressive Disintegration of Brain Networking from Normal Aging to Alzheimer Disease: Analysis of Independent Components of <sup>18</sup>F-FDG PET Data
JF Journal of Nuclear Medicine
JO J Nucl Med
FD Society of Nuclear Medicine
SP 1132
OP 1139
DO 10.2967/jnumed.116.184309
VO 58
IS 7
A1 Marco Pagani
A1 Alessandro Giuliani
A1 Johanna Öberg
A1 Fabrizio De Carli
A1 Silvia Morbelli
A1 Nicola Girtler
A1 Dario Arnaldi
A1 Jennifer Accardo
A1 Matteo Bauckneht
A1 Francesca Bongioanni
A1 Andrea Chincarini
A1 Gianmario Sambuceti
A1 Cathrine Jonsson
A1 Flavio Nobili
YR 2017
UL http://jnm.snmjournals.org/content/58/7/1132.abstract
AB Brain connectivity has been assessed in several neurodegenerative disorders investigating the mutual correlations between predetermined regions or nodes. Selective breakdown of brain networks during progression from normal aging to Alzheimer disease dementia (AD) has also been observed. Methods: We implemented independent-component analysis of 18F-FDG PET data in 5 groups of subjects with cognitive states ranging from normal aging to AD—including mild cognitive impairment (MCI) not converting or converting to AD—to disclose the spatial distribution of the independent components in each cognitive state and their accuracy in discriminating the groups. Results: We could identify spatially distinct independent components in each group, with generation of local circuits increasing proportionally to the severity of the disease. AD-specific independent components first appeared in the late-MCI stage and could discriminate converting MCI and AD from nonconverting MCI with an accuracy of 83.5%. Progressive disintegration of the intrinsic networks from normal aging to MCI to AD was inversely proportional to the conversion time. Conclusion: Independent-component analysis of 18F-FDG PET data showed a gradual disruption of functional brain connectivity with progression of cognitive decline in AD. This information might be useful as a prognostic aid for individual patients and as a surrogate biomarker in intervention trials.