Reproducible Abnormalities and Diagnostic Generalizability of White Matter in Alzheimer’s Disease

Alzheimer’s disease(AD)is associated with the impairment of white matter(WM)tracts.The current study aimed to verify the utility of WM as the neuroimaging marker of AD with multisite diffusion tensor imaging datasets[321 patients with AD,265 patients with mild cognitive impairment(MCI),279 normal controls(NC)],a unified pipeline,and independent site cross-validation.Automated fiber quantification was used to extract diffusion profiles along tracts.Random-effects meta-analyses showed a reproducible degeneration pattern in which fractional anisotropy significantly decreased in the AD and MCI groups compared with NC.Machine learning models using tract-based features showed good generalizability among independent site cross-validation.The diffusion metrics of the altered regions and the AD probability predicted by the models were highly correlated with cognitive ability in the AD and MCI groups.We highlighted the reproducibility and generalizability of the degeneration pattern of WM tracts in AD.

Different Regional Patterns in Gray Matter-based Age Prediction

Dear Editor,The brain experiences ongoing changes across different ages to support brain development and functional reorganization.During the span of adulthood,although the brain has matured from a neurobiological perspective,it is still continuously shaped by external factors such as living habit.

Retraction Note to:Gray Matter-Based Age Prediction Characterizes Different Regional Patterns

The authors have retracted this article.After publication we found an error in the implementation code that resulted in data leakage in the age-prediction model training process.We have redesigned the prediction model and tested the mode with an extended dataset(around 2000 subjects,in contrast to the 600 subjects in this article).

Diffusion magnetic resonance imaging for Brainnetome:A critical review

Increasing evidence shows that the human brain is a highly self-organized system that shows attributes of smallworldness,hierarchy and modularity.The ＂connectome＂ was conceived several years ago to identify the underpinning physical connectivities of brain networks.The need for an integration of multi-spatial and-temporal approaches is becoming apparent.Therefore,the ＂Brainnetome＂（brain-net-ome） project was proposed.Diffusion magnetic resonance imaging（dMRI） is a non-invasive way to study the anatomy of brain networks.Here,we review the principles of dMRI,its methodologies,and some of its clinical applications for the Brainnetome.Future research in this field is discussed.

Gray Matter-Based Age Prediction Characterizes Different Regional Patterns

Dear Editor,The brain experiences ongoing changes across different ages to support brain development and functional reorganization.During the span of adulthood,although the brain has matured from a neurobiological perspective,it is still continuously shaped by external factors such as habits,the family setting,socioeconomic status,and the work environment [1].In contrast to chronological age (CA),brain(or biological) age (BA) is conceptualized as an important index for characterizing the aging process and neuropsychological state,as well as individual cognitiveperformance.Growing evidence indicates that BA can be assessed by neuroimaging techniques,including MRI [2].