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IC‐P2‐126: MRI‐based cortical thickness measurement improves the prediction of MCI to AD conversion
Author(s) -
Querbes Olivier,
Albert Lotterie Jean,
Pariente Jérémie,
Berry Isabelle,
Fort Jean Claude,
Aubry Florent,
Celsis Pierre
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.2008.05.2581
Subject(s) - alzheimer's disease neuroimaging initiative , neuroimaging , magnetic resonance imaging , audiology , medicine , dementia , neuropsychology , positron emission tomography , psychology , cognition , disease , nuclear medicine , radiology , neuroscience
grey matter (GM) probability in the MTL were obtained. Neuropsychological testing was performed at baseline for all subjects, and during follow-up between 1-3.5 years in MCI patients. Conversion to AD was defined based upon clinical and neuropsychological evaluation and change in Clinical Dementia Rating (CDR) scale score from 0.5 to 1.0. Subjects were reclassified to four cognitive status levels: 1 control, 2 MCI-Nonconverter, 3 MCI-Converter, and 4 AD. An ordinal regression model was created with MTL structural and PMC fMRI measures, age and MMSE as the independent variables. Results: Both imaging and follow-up data were available in 32 MCI subjects, 10 of whom converted to AD (total sample 28 controls, 22 MCI-Nonconverters, 10 MCI-Converters, and 13 AD). In our regression model, the main effects of all four factors were statistically significant (p 0.05), independent of one another. Contributions to model variance (highest to lowest) were as follows: MTL GM probability, MMSE, Age, and PMC signal change. Conclusions: PMC deactivation and MTL GM probability measures contribute independently to diagnostic classification, including prognosis in MCI patients. Combined use of structural and functional MRI information may serve as adjuncts to neuropsychological testing in early identification and monitoring of disease progression.