Abnormal topological organization in white matter network in patients with amnestic mild cognitive impairment

Objective: To investigate the characteristics of the topological architecture of structural brain networks using diffusion tensor imaging (DTI) in amnestic mild cognitive impairment (aMCI) patients and evaluate the value of quantitative complex network analysis in early diagnoses of Alzheimer' s disease. Methods: In this study, 26 aMCI patients and 30 age-matched normal controls, collected in memory clinics at Xuanwu Hospital of Capital Medical University from January 2011 to August 2014, underwent DTI. Fifty-six network matrices were constructed thresholding fractional anisotropy and fiber number. Finally relevant network parameters were compared between the two groups utilizing permutation test. Results: Both groups showed small-world architecture, whereas compared to normal controls, significant decrease in normalized clustering coefficient (for example, when threshold is 0.1, aMCI group was 2.47, normol control group was 2.57, P=0.049), local efficiency (aMCI group was 12.01, normol control group was 13.57, P=0.001) and small-world (aMCI group was 2.02, normol control group was 2.11, P=0.013) were found in aMCI, hut there was no significant difference in average degree (aMCI group was 92.02, normol control group was 103.62, P=0.502), normalized characteristic path length (aMCI group was 3.32, normol control group 3.62, P=0.061) and global efficiency (aMCI group was 1.23, normol control group 1.23, P=0.199) between the two groups. Conclusion: Our findings suggest that the structural network widely alters in aMCI patients and network analysis has the potential to be an imaging biomarker for aMCI diagnosis. (ClinicalTrials.