Automated MRI measures identify individuals with mild cognitive impairment and Alzheimer's disease.
Mild cognitive impairment can represent a transitional state between normal ageing and Alzheimer's disease. Non-invasive diagnostic methods are needed to identify mild cognitive impairment individuals for early therapeutic interventions. Our objective was to determine whether automated magnetic resonance imaging-based measures could identify mild cognitive impairment individuals with a high degree of accuracy. Baseline volumetric T1-weighted magnetic resonance imaging scans of 313 individuals from two independent cohorts were examined using automated software tools to identify the volume and mean thickness of 34 neuroanatomic regions. The first cohort included 49 older controls and 48 individuals with mild cognitive impairment, while the second cohort included 94 older controls and 57 mild cognitive impairment individuals. Sixty-five patients with probable Alzheimer's disease were also included for comparison. For the discrimination of mild cognitive impairment, entorhinal cortex thickness, hippocampal volume and supramarginal gyrus thickness demonstrated an area under the curve of 0.91 (specificity 94%, sensitivity 74%, positive likelihood ratio 12.12, negative likelihood ratio 0.29) for the first cohort and an area under the curve of 0.95 (specificity 91%, sensitivity 90%, positive likelihood ratio 10.0, negative likelihood ratio 0.11) for the second cohort. For the discrimination of Alzheimer's disease, these three measures demonstrated an area under the curve of 1.0. The three magnetic resonance imaging measures demonstrated significant correlations with clinical and neuropsychological assessments as well as with cerebrospinal fluid levels of tau, hyperphosphorylated tau and abeta 42 proteins. These results demonstrate that automated magnetic resonance imaging measures can serve as an in vivo surrogate for disease severity, underlying neuropathology and as a non-invasive diagnostic method for mild cognitive impairment and Alzheimer's disease.
Desikan
Rahul S
RS
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA 02129, USA.
Cabral
Howard J
HJ
Hess
Christopher P
CP
Dillon
William P
WP
Glastonbury
Christine M
CM
Weiner
Michael W
MW
Schmansky
Nicholas J
NJ
Greve
Douglas N
DN
Salat
David H
DH
Buckner
Randy L
RL
Fischl
Bruce
B
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000175:diagnosis* / Q000473:pathology / Q000523:psychology; D015415:Biomarkers / Q000134:cerebrospinal fluid; D001931:Brain Mapping / Q000379:methods; D002540:Cerebral Cortex / Q000473:pathology; D003072:Cognition Disorders / Q000175:diagnosis* / Q000209:etiology / Q000473:pathology; D018450:Disease Progression; D042241:Early Diagnosis; D004812:Epidemiologic Methods; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D008875:Middle Aged; D009483:Neuropsychological Tests; D011379:Prognosis; D055815:Young Adult
D015415:Biomarkers