Objectives
To use statistical modeling of neuropsychological data to determine subgroups of dementia patients clinically diagnosed with Alzheimer’s disease (AD) or vascular dementia (VaD) and then, using brain imaging, investigate between group differences in gray and white matter regions of interest.
Methods
An analysis of neuropsychological functioning was obtained from dementia patients clinically diagnosed with AD/VaD characterized with significant leukoaraiosis (LA) and/or lacunes where a k-means cluster analysis requested a 3-group solution. MRI measures of hippocampal, caudate, ventricular, subcortical lacunar infarction, whole brain volume and LA were analyzed. Three regions of LA volumes were quantified and these included the periventricular (5mm around the ventricles), infracortical (5mm beneath the gray matter), and deep (between periventricular and infracortical) regions.
Results
Cluster analysis sorted AD/VaD patients into single domain amnestic (n=41), single-domain dysexecutive (n=26), and multi-domain (n=26) phenotypes. The multi-domain patients exhibited worst performance on language tests; however, multi-domain patients were equally impaired on memory tests when compared to amnestic patients. Statistically-determined groups were relatively dissociated using neuroradiological parameters such that amnestic and multi-domain groups presented with smaller hippocampal volume while the dysexecutive group presented with greater deep, periventricular, and whole brain LA. Neither caudate nor lacunar infarction volume differed between cluster-determined groups. Caudate nucleus volume negatively correlated with total LA in the dysexecutive and multi-domain groups.
Conclusions
Results suggest that embedded within patients diagnosed clinically with AD/VaD spectrum dementia there are at least three distinct subtypes which can be operationally-defined. Further research is needed to assess the neuroradiological substrates underlying statistically-determined AD/VaD spectrum dementia and how statistical modeling can be integrated into existing diagnostic criteria.