Aberrant White Matter Microstructure as a Potential Diagnostic Marker in Alzheimer's Disease by Automated Fiber Quantification

Frontiers in Neuroscience

Renyuan Liu²  Bing Zhang²  Ruomeng Qin⁴  Caimei Luo⁴  Mengchun Li⁴  Feng Bai⁴  Yun Xu⁴  Hui Zhao⁴  Haifeng Chen⁴  Xiaoning Sheng⁴ 

[1] Department of Neurology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China;Department of Radiology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China;Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China;Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China;The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China;

关键词: Alzheimer's disease;    white matter microstructure;    uncinate fasciculus;    anterior thalamic radiation;    cingulum cingulate;   

DOI  :  10.3389/fnins.2020.570123

来源: DOAJ

【 摘 要 】

Neuroimaging evidence has suggested white matter microstructure are heavily affected in Alzheimer's disease (AD). However, whether white matter dysfunction is localized at the specific regions of fiber tracts and whether they would be a potential biomarker for AD remain unclear. By automated fiber quantification (AFQ), we applied diffusion tensor images from 25 healthy controls (HC), 24 amnestic mild cognitive impairment (aMCI) patients and 18 AD patients to create tract profiles along 16 major white matter fibers. We compared diffusion metrics [Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (DA), and radial diffusivity (DR)] between groups. To assess the diagnostic value, we applied a random forest (RF) classifier, a type of machine learning method. In the global tract level, we found that aMCI and AD patients showed higher MD, DA, and DR values in some fiber tracts mostly in the left hemisphere compared to HC. In the point-wise level, widespread disruption were distributed on specific locations of different tracts. The point-wise MD measurements presented the best classification performance with respect to differentiating AD from HC. The two most important variables were localized in the prefrontal potion of left uncinate fasciculus and anterior thalamic radiation. In addition, the point-wise DA in the posterior component of the left cingulum cingulate displayed the most robust discriminative ability to identify AD from aMCI. Our findings provide evidence that white matter abnormalities based on the AFQ method could be as a diagnostic biomarker in AD.

【 授权许可】

Unknown