RT Journal Article SR Electronic T1 Influence of tau accumulation on structural connectivity in early Alzheimer disease JF Journal of Nuclear Medicine JO J Nucl Med FD Society of Nuclear Medicine SP 1465 OP 1465 VO 60 IS supplement 1 A1 Hiroshi Matsuda A1 Yoko Shigemoto A1 Kyoji Okita A1 Masayo Ogawa A1 Harumasa Takano YR 2019 UL http://jnm.snmjournals.org/content/60/supplement_1/1465.abstract AB 1465Introduction: Alzheimer’s disease (AD) is characterized by accumulation of extracellular amyloid-β and intracellular tau neurofibrillary tangles. The recent advent of tau-specific positron emission tomography (PET) has enabled in vivo assessment of tau pathology. Because amyloid-β and intracellular tau neurofibrillary tangles are associated with local synaptic disruption, AD is suggested to be a dysconnectivity syndrome characterized by abnormalities in the brain network. Recent advances in neuroimaging have enabled investigation of brain networks using functional and structural magnetic resonance imaging (MRI) including diffusion tensor imaging or conventional T1 weighted imaging. The aim of this study was to explore whether tau deposition influences the structural connectivity in amyloid-negative and amyloid-positive groups, and further explore the difference between the groups. We investigated 18 patients with mild cognitive impairment/mild AD (70.4+7.9 years old, MMSE=22.0+4.5, AD-spectrum group) and 35 cognitively normal older adults (66.0+8.6 years old, MMSE=29.2+0.9,CN group) using structural MRI (3D T1 weighted imaging), amyloid PET (11C-PiB) and tau PET (18F-THK5351) imaging. Connectometry analysis based on graph theory was introduced to similarity-based extraction of individual networks from gray matter MRI. Nodes represented small regions of interest in brain areas (defined as 3 × 3 × 3 voxel cubes), and connectivity was based on similarities in gray matter density values as quantified with Pearson’s correlations. Then, each node was rotated by a θ angle with multiples of 45° and reflected over all axes to identify the maximal similarity value with the target node. The gray matter similarity matrices were constructed by connecting brain areas when the significance of their correlation values exceeded a subject-specific threshold of p < 0.05 corrected for multiple testing based on the random permutation method. The obtained networks were binarized and the following four local network measures were calculated: degree (number of edges of a node), clustering coefficient (level of interconnectedness of neighboring nodes), characteristic path length (shortest distance between two nodes), and betweenness centrality (the proportion of shortest paths that run through a node). We investigated relationship between parametric images for these four local networks and tau deposition in the whole cerebrum as compared to cerebellar cortex (total tau). In the AD-spectrum group with amyloid deposition statistical parametric mapping analysis with age as a nuisance variable showed a positive correlation in precuneus (degree) and angular gyrus (betweenness centrality) between total tau and network parameters (p=0.005). In contrast the CN group without amyloid depostion did not show a positive correlation in these areas. On the other hand the CN group showed a negative correlation in hippocampus and insula (clustering coefficient, path length). These results suggest that total tau accumulation induces network degradation mainly in the hippocampus in the CN group and overload to network hubs at precuneus and parietal cortex in the AD-spectrum group where metabolic or perfusion reduction is specifically observed in AD.