Estimation of the Healthy Subjects BrainAGE:Scaled Subprofile Modeling With Connectome Analysis

In order to recognize the brain network topology deviated from the normal pattern of aging,a model of healthy brain aging is needed.In this paper,a framework for automatically and efficiently estimating the age of healthy subjects from their DTI MRI scans was introduced,by using connectome analysis.The age estimation procedures included automatic preprocessing of the DTI,anatomical network construction,connectome analysis and finally estimation of the age of the subjects based on Scaled Subprofile Model(SSM).The prediction model was proved to be accurate and reliable in healthy subjects,yielding brain age gap estimate(BrainAGE) +0.09 years for the healthy aging group.Applying the framework to subjects with hypertension resulted in a mean score BrainAGE of + 5.55 years.This model may serve as a clinically relevant biomarker for the detection of abnormal brain aging associated with disease.