Early Microstructure Changes of White Matter Fiber Bundles in Patients with Amnestic Mild Cognitive Impairment Predicts Progression of Mild Cognitive Impairment to Alzheimer’s Disease

Article type: Research Article

Authors: He, Fangmei^{a; b; c; 1} | Zhang, Yuchen^{d; 1} | Wu, Xiaofeng^{a; b; c} | Li, Youjun^{a; b; c} | Zhao, Jie^{a; b; c} | Fang, Peng^e | Fan, Liming^{a; b; c} | Li, Chenxi^{a; b; c} | Liu, Tian^{a; b; c; *} | Wang, Jue^{a; b; c; *} | Alzheimer’s Disease Neuroimaging Initiative²

Affiliations: [a] The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi, P.R. China | [b] National Engineering Research Center for Healthcare Devices, Guangzhou, Guangdong, P.R. China | [c] The Key Laboratory of Neuro-informatics & Rehabilitation Engineering of Ministry of Civil Affairs, Xi’an, Shaanxi, P.R. China | [d] Department of Oncology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, P.R. China | [e] Department of Military Medical Psychology, Air Force Medical University, Xi’an, Shaanxi, P.R. China

Correspondence: [*] Correspondence to: Dr. Jue Wang and Dr. Tian Liu, The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi, 710049, P.R. China. Tel.: 15332479788; E-mail: [email protected] (Dr. Jue Wang). Tel.: 13119130267; E-mail: [email protected] (Dr. Tian Liu).

Note: [1] These authors contributed equally to this work.

Note: [2] Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (http://adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wpcontent/uploads/howtoapply/ADNIAcknowledgement List.pdf.

Abstract: Background:Amnestic mild cognitive impairment (aMCI) is the transitional stage between normal aging and Alzheimer’s disease (AD). Some aMCI patients will progress into AD eventually, whereas others will not. If the trajectory of aMCI can be predicted, it would enable early diagnosis and early therapy of AD. Objective:To explore the development trajectory of aMCI patients, we used diffusion tensor imaging to analyze the white matter microstructure changes of patients with different trajectories of aMCI. Methods:We included three groups of subjects:1) aMCI patients who convert to AD (MCI-P); 2) aMCI patients who remain in MCI status (MCI-S); 3) normal controls (NC). We analyzed the fractional anisotropy and mean diffusion rate of brain regions, and we adopted logistic binomial regression model to predicate the development trajectory of aMCI. Results:The fraction anisotropy value is significantly reduced, the mean diffusivity value is significantly increased in the two aMCI patient groups, and the MCI-P patients presented greater changes. Significant changes are mainly located in the cingulum, fornix, hippocampus, and uncinate fasciculus. These changed brain regions significantly correlated with the patient’s Mini-Mental State Examination scores. Conclusion:The study predicted the disease trajectory of different types of aMCI patients based on the characteristic values of the above-mentioned brain regions. The prediction accuracy rate can reach 90.2%, and the microstructure characteristics of the right cingulate band and the right hippocampus may have potential clinical application value to predict the disease trajectory.

Keywords: Alzheimer’s disease, amnestic mild cognitive impairment, diffusion tensor imaging, cognition, early microstructure changes

DOI: 10.3233/JAD-210495

Journal: Journal of Alzheimer's Disease, vol. 84, no. 1, pp. 179-192, 2021