Differentiating between Patients with Alzheimer's Disease and Patients with Major Depressive Disorder Using the Voxel-based Specific Regional Aanalysis System for Alzheimer's Disease

Background: Recently, voxel-based morphometry (VBM) has become a popular tool for the early diagnosis of Alzheimer’s disease (AD). The voxel-based specific regional analysis system for Alzheimer’s disease (VSRAD) is a clinically useful VBM technique that employs magnetic resonance imaging (MRI) to automatically detect the loss of Powered by Editorial Manager® and ProduXion Manager® from Aries Systems Corporation gray matter volume in the medial temporal lobe. Objective: To investigate the utility of VSRAD for differentiating between AD and major depressive disorder (MDD), and to identify the neuropathological differences between the two groups. Methods: The subjects included 18 patients with MDD (mean ± standard deviation: 74.8 ± 7.1 years, 4 males and 14 females) and 31 patients with AD (82.4 ± 7.3 years, 7 males and 24 females). Three-dimensional T1-weighted sagittal images, were acquired using a 1.5Tesla MRI device and analyzed using the VSRAD advance software, parahippocampal atrophy was represented as a Z-score. Neuropsychological tests consisted of the Patient Health Questionnaire 9, Hamilton Rating Scale for Depression, Global Assessment of Function and Mini-Mental State Examination (MMSE). Correlations between the Z-score and the neuropsychological test scores were statistically examined. Results: Patients with AD had significantly higher Z-scores than did patients with MDD (1.99 ± 1.27 vs. 1.11 ± 0.49, p 2 were all diagnosed as AD. In the AD group, the Z-scores were significantly correlated with the MMSE scores throughout the study period (0 weeks: p=0.015, 24 weeks: p=0.024), whereas no significant correlations between the Z-scores and MMSE were observed for the MDD group. Conclusion: Our results obtained using the VSRAD suggest that VSRAD is useful for differentiating between AD and MDD, which is important, as the these two diseases are often difficult to diagnose based solely on their symptoms. Such findings imply that VSRAD may become a useful auxiliary diagnostic tool.