Structural and functional connectional fingerprints in mild cognitive impairment and Alzheimer's disease patients

• Published in: PloS one Vol. 12; no. 3; p. e0173426
• Main Authors: Son, Seong-Jin, Kim, Jonghoon, Park, Hyunjin
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 23.03.2017; Public Library of Science (PLoS)
• Subjects: Age; Aged; Alzheimer Disease - pathology; Alzheimer's disease; Analysis; Atrophy; Atrophy - pathology; Biology and Life Sciences; Brain - pathology; Brain research; Care and treatment; Classifiers; Cognitive ability; Cognitive Dysfunction - pathology; Computer and Information Sciences; Computer engineering; Degeneration; Dementia; Diagnosis; Diagnostic imaging; Female; Fingerprints; Functional magnetic resonance imaging; Humans; Impairment; Magnetic resonance; Magnetic resonance imaging; Magnetic Resonance Imaging - methods; Male; Medical imaging; Medicine and Health Sciences; Memory; Neural networks; Neurodegenerative diseases; Neuroimaging; Neuroimaging - methods; Neurology; Neurosciences; NMR; Nuclear magnetic resonance; Patients; Permutations; Physical Sciences; Publishing industry; Retrospective Studies; Structure-function relationships; Studies; Trends; United States
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0173426

Regional volume atrophy and functional degeneration are key imaging hallmarks of Alzheimer's disease (AD) in structural and functional magnetic resonance imaging (MRI), respectively. We jointly explored regional volume atrophy and functional connectivity to better characterize neuroimaging data of AD and mild cognitive impairment (MCI). All data were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We compared regional volume atrophy and functional connectivity in 10 subcortical regions using structural MRI and resting-state functional MRI (rs-fMRI). Neuroimaging data of normal controls (NC) (n = 35), MCI (n = 40), and AD (n = 30) were compared. Significant differences of regional volumes and functional connectivity measures between groups were assessed using permutation tests in 10 regions. The regional volume atrophy and functional connectivity of identified regions were used as features for the random forest classifier to distinguish among three groups. The features of the identified regions were also regarded as connectional fingerprints that could distinctively separate a given group from the others. We identified a few regions with distinctive regional atrophy and functional connectivity patterns for NC, MCI, and AD groups. A three label classifier using the information of regional volume atrophy and functional connectivity of identified regions achieved classification accuracy of 53.33% to distinguish among NC, MCI, and AD. We identified distinctive regional atrophy and functional connectivity patterns that could be regarded as a connectional fingerprint.