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Structural MRI biomarkers for preclinical and mild Alzheimer's disease
Open accessAbstract
Noninvasive MRI biomarkers for Alzheimer's disease (AD) may enable earlier clinical diagnosis and the monitoring of therapeutic effectiveness. To assess potential neuroimaging biomarkers, the Alzheimer's Disease Neuroimaging Initiative is following normal controls (NC) and individuals with mild cognitive impairment (MCI) or AD. We applied high‐throughput image analyses procedures to these data to demonstrate the feasibility of detecting subtle structural changes in prodromal AD. Raw DICOM scans (139 NC, 175 MCI, and 84 AD) were downloaded for analysis. Volumetric segmentation and cortical surface reconstruction produced continuous cortical surface maps and region‐of‐interest (ROI) measures. The MCI cohort was subdivided into single‐ (SMCI) and multiple‐domain MCI (MMCI) based on neuropsychological performance. Repeated measures analyses of covariance were used to examine group and hemispheric effects while controlling for age, sex, and, for volumetric measures, intracranial vault. ROI analyses showed group differences for ventricular, temporal, posterior and rostral anterior cingulate, posterior parietal, and frontal regions. SMCI and NC differed within temporal, rostral posterior cingulate, inferior parietal, precuneus, and caudal midfrontal regions. With MMCI and AD, greater differences were evident in these regions and additional frontal and retrosplenial cortices; evidence for non‐AD pathology in MMCI also was suggested. Mesial temporal right‐dominant asymmetries were evident and did not interact with diagnosis. Our findings demonstrate that high‐throughput methods provide numerous measures to detect subtle effects of prodromal AD, suggesting early and later stages of the preclinical state in this cross‐sectional sample. These methods will enable a more complete longitudinal characterization and allow us to identify changes that are predictive of conversion to AD. Hum Brain Mapp 2009. © 2009 Wiley‐Liss, Inc.
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“it has been shown that brain atrophy as revealed by structural MRI is able to discriminate preclinical stages and time evolution of AD at 1‐year follow‐up. 34 , 35 , 36”
From Early dementia diagnosis, MCI-to-dementia risk prediction, and the role of machine learning methods for feature extraction from integrated biomarkers, in particular for EEG signal analysis (2022) · cites this paper as [34]
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Self-citationMild cognitive impairment as a diagnostic entity
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The Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception
Weiner, M. W., Veitch, D. P., Aisen, P. S. S., Beckett, L. A., Cairns, N. J., Green, R. C., Harvey, D. J., Jack, C. R., Jagust, W. J., Liu, E., et al. (2013) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2013.05.1769 · Cited by 1,033
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Fjell, A. M., Walhovd, K. B., Fennema-Notestine, C., McEvoy, L. K., Hagler, D. J., Holland, D., Brewer, J. B., & Dale, A. M. (2009) · The Journal of Neuroscience · doi:10.1523/jneurosci.3252-09.2009 · Cited by 692
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Preventing Alzheimer’s disease-related gray matter atrophy by B-vitamin treatment
Douaud, G., Refsum, H., de Jager, C. A., Jacoby, R. J., Nichols, T. E., Smith, S. M., & Smith, A. D. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1301816110 · Cited by 533
Metadata
- Authors
- Fennema‐Notestine, C., Hagler, D. J., McEvoy, L. K., Fleisher, A. S., Wu, E. H., Karow, D. S., & Dale, A. M.
- Affiliations
- University of California San Diego (US)
- Corresponding author
- Fennema‐Notestine, Christine
- Venue
- Human Brain Mapping
- Publisher
- Wiley
- Published
- 2009-03-10
- Volume
- 30
- Issue
- 10
- Pages
- 3238-3253
- ISSN
- 1065-9471 (ISSN-L)
- 1097-0193
- PMC
- PMC2951116
- OpenAlex
- W2079502798
- Cited by
- 233
- References
- 75
- Citations by year
- 2026: 8 · 2025: 7 · 2024: 6 · 2023: 9 · 2022: 9 · 2021: 11 · 2020: 10 · 2019: 9 · 2018: 13 · 2017: 11 · 2016: 13 · 2015: 18 · 2014: 18 · 2013: 22 · 2012: 23
- FWCI
- 14.18
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Human Brain Mapping (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Foundation for the National Institutes of Health
- National Institutes of Health (5u01ag024904-10)
- National Institute on Aging (U01-AG-024904, U19AG010483)
- National Center for Research Resources (U24RR021382)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- Alzheimer's disease, mild cognitive impairment, preclinical Alzheimer's disease, structural MRI biomarkers, 3D image segmentation, cortical surface reconstruction, region of interest analysis, hemispheric lateralization, medial temporal lobe, conversion to Alzheimer's disease, high-throughput image analysis, Alzheimer's Disease Neuroimaging Initiative
- MeSH terms
- Aged, Aged, 80 and over, Alzheimer Disease, Cerebral Cortex, Cognition Disorders, Female, Humans, Image Processing, Computer-Assisted, Functional Laterality, Magnetic Resonance Imaging, Male, Mental Status Schedule, Middle Aged, Neuropsychological Tests, Cohort Studies, Case-Control Studies
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