Advances in computerized MRI-based biomarkers in Alzheimer's disease

The use of neuroimaging examinations is crucial in Alzheimer’s disease(AD),in both research and clinical settings.Over the years,magnetic resonance imaging(MRI)–based computer-aided diagnosis has been shown to be helpful for early screening and predicting cognitive decline.Meanwhile,an increasing number of studies have adopted machine learning for the classification of AD,with promising results.In this review article,we focus on computerized MRI-based biomarkers of AD by reviewing representative studies that used computerized techniques to identify AD patients and predict cognitive progression.We categorized these studies based on the following applications:(1)identifying AD from normal control;(2)identifying AD from other dementia types,including vascular dementia,dementia with Lewy bodies,and frontotemporal dementia;and(3)predicting conversion from NC to mild cognitive impairment(MCI)and from MCI to AD.This systematic review could act as a state-of-the-art overview of this emerging field as well as a basis for designing future studies.

Visualizing the neuroanatomical changes in Han Chinese adulthood: A pseudo-longitudinal study based on age-related large-scale statistical Chinese brain atlases

Objective:Understanding how brain changes over lifetime provides the basis for new insights into neurophysiology and neuropathology.In this study,we carried out a pseudo-longitudinal study based on age-related Chinese brain atlases(i.e.,Chinese2020)constructed from large-scale volumetric brain MRI data collected in normal Han Chinese adults at varying ages.Methods:In order to quantify the deformation and displacement of brains for each voxel as age increases,optical flow algorithm was employed to compute motion vectors between every two consecutive brain templates of the age-related brain atlas,i.e.,Chinese2020.Results:Dynamic age-related neuroanatomical changes in a standardized brain space were shown.Overall,our results demonstrate that brain inward deformation(mainly due to atrophy)can appear in adulthood and this trend generally accelerates as age increases,affecting multiple regions including frontal cortex,temporal cortex,parietal cortex,and cerebellum,whereas occipital cortex is least affected by aging,and even showed some degree of outward deformation in the midlife.Conclusion:Our findings indicated more complicated age-related changes instead of a simple trend of brain volume decrease,which may be in line with the recently increasing interests in the age-related cortical complexity with other morphometry measures.