Alzheimer's disease and frontotemporal dementia exhibit distinct atrophy-behavior correlates: a computer-assisted imaging study.

RATIONALE AND OBJECTIVES The purpose of this study was to test the hypothesis that distinct patterns of gray matter atrophy are responsible for unique interruptions of the naming process in Alzheimer's disease (AD) and frontotemporal dementia (FTD). MATERIALS AND METHODS Voxel-based morphometry (VBM) was performed to characterize at the voxel level the neuroanatomic changes that occur in AD and FTD based on high-resolution T1-weighted three-dimensional (3D) spoiled-gradient echo images of patients (AD, n = 12; FTD, n = 29) and healthy control subjects (n = 12). The cortical atrophy measurements were correlated with performance on behavioral measures of naming and related processes to identify brain regions that may contribute to this language function. RESULTS Both AD and FTD have significant naming difficulty, and this difficulty in naming correlates with a measure of lexical retrieval in both patient groups as well. However, only FTD patients showed a correlation with semantic memory. Areas of cortical atrophy common to AD and FTD were found in the anterior temporal, posterolateral temporal, and dorsolateral prefrontal regions of the left hemisphere. Correlation with naming in both AD and FTD was seen in the left anterior temporal cortex, suggesting that this area may play a role in the lexical retrieval component of naming. We also observed several unique areas of cortical atrophy in temporal and frontal cortices of these patients. Right anterior temporal and left posterolateral temporal regions of atrophy correlated with naming difficulty in FTD, suggesting that these areas may contribute to the semantic memory component of naming. Cortical areas correlating with naming that are not atrophic may represent regions that play an optional role in naming. CONCLUSION VBM provides an important first step in analyzing brain-behavior relations in vivo in patients with neurodegenerative diseases. More refined analyses of brain morphology via high-dimensional normalization methods that are capable of modeling local as well as global variability in neuroanatomical structure promise to be even more informative.