Predicting Progression to Dementia in Elderly Subjects with Mild Cognitive Impairment Using Both Cognitive and Neuroimaging Predictors

Abstract

The objective of this work was to assess the predictive accuracy of targeted neuroimaging and neuropsychological measures for the detection of incipient dementia in individuals with mild cognitive impairment (MCI), and to examine the potential benefit of combining both classes of measures. Baseline MRI measures included hippocampal volume, cortical thickness, and white matter hyperintensities. Neuropsychological assessment focused on different aspects of episodic memory (i.e., familiarity, free recall, and associative memory) and executive control functions (i.e., working memory, switching, and planning). Global and regional cortical thinning was observed in MCI patients who progressed to dementia compared to those who remained stable, whereas no differences were found between groups for baseline hippocampal volume and white matter hyperintensities. The strongest neuroimaging predictors were baseline cortical thickness in the right anterior cingulate and middle frontal gyri. For cognitive predictors, we found that deficits in both free recall and recognition episodic memory tasks were highly suggestive of progression to dementia. Cortical thinning in the right anterior cingulate gyrus, combined to controlled and familiarity-based retrieval deficits, achieved a classification accuracy of 87.5%, a specificity of 90.9%, and a sensitivity of 83.3%. This predictive model including both classes of measures provided more accurate predictions than those based on neuroimaging or cognitive measures alone. Overall, our findings suggest that detecting preclinical Alzheimer's disease is probably best accomplished by combining complementary information from targeted neuroimaging and cognitive classifiers, and highlight the importance of taking into account both structural and functional changes associated with the disease.