The Clinical Value of Structural and Functional Brain Connectivity MR Biomarkers in Alzheimer's Disease

Abstract

Background: At present, clinical use of MRI in Alzheimer’s disease (AD) is mostly focused on the assessment of brain atrophy, namely in the hippocampal region. Despite this, multiple biomarkers reflecting structural and functional brain connectivity changes have shown promising results in the assessment of AD. To help identify the most relevant ones that may stand a chance of being used in clinical practice, we compared multiple biomarker in terms of their value to discriminate AD from healthy controls and analyzed their age dependency. Methods: 20 AD patients and 20 matched controls underwent MRI-scanning (3T GE), including T1-weighted, diffusion-MRI, and resting-state-fMRI (rsfMRI). Whole-brain, white-matter, gray-matter, cortical-gray-matter and hippocampi volumes were measured using icobrain. rsfMRI between regions of the default-mode-network (DMN) was assessed using group independent-component-analysis. Median diffusivity and kurtosis were determined in gray and white-matter.Logistic-Regression and Random-Forest models were trained to classify AD-status based on different features and feature-groups. Results: Hippocampal and DMN features involving the medial-Pre-Frontal-Cortex (mPFC) showed the strongest differences between AD-patients and controls. mPFC-DMN-features, WM volume, and relative hippocampal asymmetry showed only an association with AD-status (p <0.05) but not with age. Whole-brain volume, hippocampi volumes, and DTI/DKI features showed an association both with age and AD-status. Smallest-hippocampus-volume was the most discriminative feature. The best performance (accuracy:0.77, sensitivity:0.77, specificity:0.77) was obtained with an RF-model combining the best feature from each feature-group (smallest hippocampus volume, WM volume, median GM AxD and lTPJ-mPFC connectivity) and age. Conclusions: Brain-connectivity changes are reflected in multiple MRI-biomarkers. Inclusion of structural and functional connectivity biomarkers in addition to hippocampal volumes can contribute to a higher diagnostic accuracy and may provide a more complete assessment of the clinical status of each patient.