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IC‐P2‐091: Integration of MRI measures of atrophy and protein aggregation with CSF biomarkers of AD pathology in individuals with mild cognitive impairment
Author(s) -
Davatzikos Christos,
Borthakur Arijitt,
Xu Feng,
Wu Xiaoying,
Parmpi Evi,
Sochor Matthew,
Clark Christopher M.
Publication year - 2008
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1016/j.jalz.2008.05.084
Subject(s) - atrophy , biomarker , cohort , medicine , imaging biomarker , pathology , psychology , temporal lobe , neuroimaging , magnetic resonance imaging , oncology , neuroscience , radiology , biology , biochemistry , epilepsy
sis and prognosis. This study was based on two large neuroimaging studies of normal aging and AD: the Baltimore Longitudinal Study of Aging (BLSA) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). We investigated longitudinal progression of AD-like patterns of atrophy, determined from ADNI, in the BLSA cohort of cognitively normal (CN) elderly and of MCI. Methods: A high-dimensional pattern classifier was trained on 66 CN and 56 AD ADNI patients, and was subsequently applied to 109 CN and 15 MCI individuals from the BLSA study over a period of 9 years. The longitudinal progression of AD-like patterns of atrophy was determined for different age brackets. Results: 98.7% of all BLSA participants that remained CN were correctly classified as CN, thereby crossvalidating the accuracy of ADNI-derived classification on datasets from a different study. CN subjects of ages above 80 progressively displayed AD-like patterns of brain atrophy. The rates of change of classificationderived abnormality scores of CN’s were fairly well clustered around 0, except a small subgroup of them (especially older subjects), generally indicating lack of progression of CN towards AD-like phenotypes. In contrast, rates of change of individuals that developed MCI were more variable and positive, indicating gradual progression of many, but not all, to AD-like structure. Moreover, cognitive scores of CN and MCI that were determined to have AD-like classification scores were significantly lower than their counterparts classified as normal-like. Conclusions: A biomarker of structural abnormality distinguishing CN from AD was derived using sophisticated high-dimensional pattern classification, and was tested on longitudinal MRI scans from cognitively normal elderly and of MCI individuals. Although most CN’s that remain cognitively stable display normal and stable patterns of atrophy, individuals that develop MCI show steady increases in AD-like atrophy patterns. Structural abnormality scores and their rates of change define subgroups of CN and MCI individuals whose cognitive scores differ significantly, further indicating the clinical relevance of this structural biomarker.