title: White matter signal abnormality quality differentiates mild cognitive impairment that converts to Alzheimer's disease from nonconverters.
abstract: The objective of this study was to assess how longitudinal change in the quantity and quality of white matter signal abnormalities (WMSAs) contributes to the progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD). The Mahalanobis distance of WMSA from normal-appearing white matter using T1-, T2-, and proton density-weighted MRI was defined as a quality measure for WMSA. Cross-sectional analysis of WMSA volume in 104 cognitively healthy older adults, 116 individuals with MCI who converted to AD within 3 years (mild cognitive impairment converter [MCI-C]), 115 individuals with MCI that did not convert in that time (mild cognitive impairment nonconverter [MCI-NC]), and 124 individuals with AD from the Alzheimer's Disease Neuroimaging Initiative revealed that WMSA volume was substantially greater in AD relative to the other groups but did not differ between MCI-NC and MCI-C. Longitudinally, MCI-C exhibited faster WMSA quality progression but not volume compared with matched MCI-NC beginning 18 months before MCI-C conversion to AD. The strongest difference in rate of change was seen in the time period starting 6 months before MCI-C conversion to AD and ending 6 months after conversion (p < 0.001). The relatively strong effect in this time period relative to AD conversion in the MCI-C was similar to the relative rate of change in hippocampal volume, a traditional imaging marker of AD pathology. These data demonstrate changes in white matter tissue properties that occur within WMSA in individuals with MCI that will subsequently obtain a clinical diagnosis of AD within 18 months. Individuals with AD have substantially greater WMSA volume than all MCI suggesting that there is a progressive accumulation of WMSA with progressive disease severity, and that quality change predates changes in this total volume. Given the timing of the changes in WMSA tissue quality relative to the clinical diagnosis of AD, these findings suggest that WMSAs are a critical component for this conversion and are a critical component of this clinical syndrome.
authors.affiliation: Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA; Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. Electronic address: lindemer@mit.edu.
authors.forename: Emily R
authors.initials: ER
authors.lastname: Lindemer
authors.affiliation: Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA; Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; VA Boston Healthcare System, Boston, MA, USA.
authors.forename: David H
authors.initials: DH
authors.lastname: Salat
authors.affiliation: Department of Clinical Neurosciences and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.
authors.forename: Eric E
authors.initials: EE
authors.lastname: Smith
authors.affiliation: Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA; Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
authors.forename: Khoa
authors.initials: K
authors.lastname: Nguyen
authors.affiliation: Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA; Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology (MIT), Cambridge, MA, USA.
authors.forename: Bruce
authors.initials: B
authors.lastname: Fischl
authors.affiliation: Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA; Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
authors.forename: Douglas N
authors.initials: DN
authors.lastname: Greve
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000473:pathology*; D000704:Analysis of Variance; D060825:Cognitive Dysfunction / Q000473:pathology* / Q000503:physiopathology; D003430:Cross-Sectional Studies; D005260:Female; D006624:Hippocampus / Q000473:pathology*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008137:Longitudinal Studies; D008279:Magnetic Resonance Imaging; D008297:Male; D008609:Mental Status Schedule; D066127:White Matter / Q000473:pathology*
keywords: Alzheimer's Disease Neuroimaging initiative; Alzheimer's disease; FreeSurfer; Hippocampus; Mild cognitive impairment; White matter signal abnormality