Brain Connectivity Markers Of Mild Cognitive Impairment In Advanced Parkinson’s Disease

Purpose : Mild cognitive impairment(MCI)is a well-defined non-motor manifestation and a harbinger of dementia in Parkinson’s disease.This study is to investigate brain connectivity markers of MCI using diffusion tensor imaging and resting-state functional MRI,and help MCI diagnosis in PD patients.Materials and Methods : We evaluated 131 advanced PD patients(disease duration > 5 years;59 patients with MCI)and 48 healthy control subjects who underwent a diffusion-weighted and resting-state functional MRI scanning.The patients were randomly assigned into training(n=100)and testing(n=31)groups.According to the Brainnetome atlas,ROI-based structural and functional connectivity analysis was employed to extract connectivity features.To identify features with significant discriminative power for patient classification,all features were put into an all-relevant feature selection procedure within cross-validation loops.Results:Nine features were identified to be significantly relevant to patient classification.They positively correlated with Mo CA score in patients.Five of them showed significant differences between PD patients with and without MCI,but not between general MCI subjects and healthy controls from the ADNI database,which suggested that they could uniquely play a part in the MCI diagnosis of PD.On basis of these relevant features,the random forest model constructed from the training group achieved an accuracy of 83.9% in the testing group,to discriminate patients with and without MCI.Conclusions:The results of our study provide preliminary evidence that structural and functional connectivity abnormalities may contribute to cognitive impairment and allow to predict the outcome of MCI diagnosis in PD.