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Predicting Mental Decline Rates in Mild Cognitive Impairment From Baseline MRI Volumetric Data.
- Source :
- Alzheimer Disease & Associated Disorders; Jan-Mar2021, Vol. 35 Issue 1, p1-7, 7p
- Publication Year :
- 2021
-
Abstract
- <bold>Purpose: </bold>In mild cognitive impairment (MCI), identifying individuals at high risk for progressive cognitive deterioration can be useful for prognostication and intervention. This study quantitatively characterizes cognitive decline rates in MCI and tests whether volumetric data from baseline magnetic resonance imaging (MRI) can predict accelerated cognitive decline.<bold>Methods: </bold>The authors retrospectively examined Alzheimer Disease Neuroimaging Initiative data to obtain serial Mini-Mental Status Exam (MMSE) scores, diagnoses, and the following baseline MRI volumes: total intracranial volume, whole-brain and ventricular volumes, and volumes of the hippocampus, entorhinal cortex, fusiform gyrus, and medial temporal lobe. Subjects with <24 months or <4 measurements of MMSE data were excluded. Predictive modeling of fast cognitive decline (defined as >0.6/year) from baseline volumetric data was performed on subjects with MCI using a single hidden layer neural network.<bold>Results: </bold>Among 698 baseline MCI subjects, the median annual decline in the MMSE score was 1.3 for converters to dementia versus 0.11 for stable MCI (P<0.001). A 0.6/year threshold captured dementia conversion with 82% accuracy (sensitivity 79%, specificity 85%, area under the receiver operating characteristic curve 0.88). Regional volumes on baseline MRI predicted fast cognitive decline with a test accuracy of 71%.<bold>Discussion: </bold>An MMSE score decrease of >0.6/year is associated with MCI-to-dementia conversion and can be predicted from baseline MRI. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 08930341
- Volume :
- 35
- Issue :
- 1
- Database :
- Supplemental Index
- Journal :
- Alzheimer Disease & Associated Disorders
- Publication Type :
- Academic Journal
- Accession number :
- 148969272
- Full Text :
- https://doi.org/10.1097/WAD.0000000000000406