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Updated: Mar 20, 2026
Application of Granger Causality Analysis of the Directed Functional Connection in Alzheimer's Disease and Mild Cognitive Impairment
Published on: August 7, 2017
Predicting progression from mild cognitive impairment to Alzheimer's disease using longitudinal callosal atrophy
Sang Han Lee1, Alvin H Bachman1, Donghyeon Yu2
1Center for Biomedical Imaging and Neuromodulation, The Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
Introduction:
We investigate whether longitudinal callosal atrophy could predict conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD).
Methods:
Longitudinal (baseline + 1-year follow-up) MRI scans of 132 MCI subjects from the Alzheimer's Disease Neuroimaging Initiative were used. A total of 54 subjects did not convert to AD over an average (±SD) follow-up of 5.46 (±1.63) years, whereas 78 converted to AD with an average conversion time of 2.56 (±1.65) years. Annual change in the corpus callosum thickness profile was calculated from the baseline and 1-year follow-up MRI. A logistic regression model with fused lasso regularization for prediction was applied to the annual changes.
Results:
We found a sex difference. The accuracy of prediction was 84% in females and 61% in males. The discriminating regions of corpus callosum differed between sexes. In females, the genu, rostrum, and posterior body had predictive power, whereas the genu and splenium were relevant in males.
Discussion:
Annual callosal atrophy predicts MCI-to-AD conversion in females more accurately than in males.
Insights
Annual callosal atrophy, a measure of brain structure change, can predict the conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD), particularly in females.
Area of Science:
- Neuroimaging
- Neurology
- Biomedical Engineering
Background:
- Mild cognitive impairment (MCI) is a prodromal stage for Alzheimer's disease (AD).
- Identifying predictors of MCI-to-AD conversion is crucial for early intervention.
Purpose of the Study:
- To investigate if longitudinal changes in corpus callosum thickness can predict conversion from MCI to AD.
- To explore potential sex differences in the predictive accuracy and relevant brain regions.
Main Methods:
- Utilized longitudinal MRI scans from 132 MCI subjects (Alzheimer's Disease Neuroimaging Initiative).
- Calculated annual changes in corpus callosum thickness profile.
- Employed a logistic regression model with fused lasso regularization for prediction.
Main Results:
- Achieved an 84% prediction accuracy in females and 61% in males.
- Identified distinct predictive regions of the corpus callosum between sexes.
- Female prediction involved the genu, rostrum, and posterior body; male prediction involved the genu and splenium.
Conclusions:
- Longitudinal callosal atrophy is a significant predictor of MCI-to-AD conversion.
- Prediction accuracy is notably higher in females compared to males.
- Sex-specific patterns of callosal atrophy influence conversion prediction.
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