Year: 2014
Type: article
Abstract: OBJECTIVE: F-AV45-PET uptake, in individuals with early mild cognitive impairment(MCI). Furthermore, to assess the relative importance of imaging modalities in classification of Aβ+/Aβ- early mild cognitive impairment. METHODS: Sixty-seven ADNI-GO/2 participants with early-MCI were included. Voxel-wise anatomical shape variation measures were computed by estimating the initial diffeomorphic mapping momenta from an unbiased control template. CBF measures normalized to average motor cortex CBF were mapped onto the template space. Using partial least squares regression, we identified the structural and CBF signatures of Aβ after accounting for normal cofounding effects of age, sex, and education. RESULTS: F-AV45-positive early-MCIs could be identified with 83% classification accuracy, 87% positive predictive value, and 84% negative predictive value by multidisciplinary classifiers combining demographics data, ApoE ε4-genotype, and a multimodal MRI-based Aβ score. INTERPRETATION: Multimodal-MRI can be used to predict the amyloid status of early-MCI individuals. MRI is a very attractive candidate for the identification of inexpensive and non-invasive surrogate biomarkers of Aβ deposition. Our approach is expected to have value for the identification of individuals likely to be Aβ+ in circumstances where cost or logistical problems prevent Aβ detection using cerebrospinal fluid analysis or Aβ-PET. This can also be used in clinical settings and clinical trials, aiding subject recruitment and evaluation of treatment efficacy. Imputation of the Aβ-positivity status could also complement Aβ-PET by identifying individuals who would benefit the most from this assessment.
DOI: 10.1002/acn3.40
Language: English
Subfield: Psychiatry and Mental health
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $4,100
Funders: Foundation for the National Institutes of Health, Alzheimer's Association, Bristol-Myers Squibb, Eli Lilly and Company, Pfizer, Biogen, F. Hoffmann-La Roche, Medpace, Meso Scale Diagnostics, Synarc, Alzheimer's Disease Neuroimaging Initiative, BioClinica, Novartis Pharmaceuticals Corporation, Northern California Institute for Research and Education, Eisai, Servier, IXICO, National Institutes of Health, Genentech, University of California, Los Angeles, University of California, San Diego, Canadian Institutes of Health Research, National Institute on Aging, National Institute of Mental Health, National Institute of Biomedical Imaging and Bioengineering, National Center for Research Resources
Awards: G104586243, G1103752518, UC Davis Alzheimer's Disease Core Center, G1593117279, Alzheimer's Disease Neuroimaging Initiative, G2152643862, G2340207221, G2409989180, G2612545735, G2662806094, G2751204023, G2835601961, G2844381683, G29951154, G3131374986, G3146424788, G3218891203, G3553156159, G3638842286, G3705772492, G3710456697, G3752451908, G3870774570, G3908963977, G3966393351, "MR Morphometrics and Cognitive Decline Rate in Large-Scale Aging Studies", G43180419, G4401988282, G4411643199, G4501223628, G4660785924, G4684857399, G4894255983, G5207404921, G5209990037, G5389965057, G5654639750, G5740349702, G5780694236, G598830915, G6069485058, G613619302, G6210868510, G6371410416, G6412110892, G6899163935, G6948409098, G7298697282, G7315666996, G7414321945, G7799614282, G781725486, G793122433, G8130182348, G839208290, G8488061998, G8636843673, G8659614056, G8852128998, G9000039018, G9000074849, G9000084418, G9000086741, G9000087106, G9000108235, G9000122335, G9000234615, G920654007, G991187644
OpenAlex ID: W2066901586