Diagnosis of depression by MRI scans with the use of VSRAD – a promising auxiliary means of diagnosis: a report of 10 years research

Abstract

Objectives:This study was designed to evaluate the usefulness of assessing subgenual anterior cingulate cortex (sACC) volume reduction by magnetic resonance imaging (MRI) as an objective auxiliary means of diagnosis of depression. The study was additionally designed to analyze the association of sACC volume reduction with the effectiveness of treatments for depression and other diseases presenting with similar symptoms, and to examine the possibility of using sACC volume reduction in the distinction between depression and bipolar disorder and determining optimum medication for these conditions.Methods:Three-dimensional T1-weighted sagittal images, taken with Achieva 1.5T NOVA (Philips), were analyzed with VSRAD plus® to evaluate a reduction in sACC volume. The finding from this analysis was compared with the clinical data, including the longitudinal course follow-up data based on the treatment algorithm.Subjects:The study involved 88 patients aged over 54 who received MRI during 2010, ie, 71 patients with major depressive disorder (MDD), 11 patients bipolar disorder, and 6 patients in whom the initial diagnosis (MDD) was later modified. Thirty-three normal individuals served as controls.Results:sACC volume reduction was noted in 66 of the 71 patients receiving treatment of MDD, with sensitivity of 93%, specificity of 85%, and accuracy of 90%. In the 66 patients diagnosed as having MDD and exhibiting sACC volume reduction, the disease showed remission in response to treatment with antidepressants, but medication needed to be continued after achievement of remission. In cases initially diagnosed as having MDD but not exhibiting sACC volume reduction, the necessity of modifying the diagnosis was considered. Typical cases of bipolar disorder did not exhibit sACC volume reduction.Conclusion:That patients receiving treatment of MDD often showed reduction in sACC volume suggests the usefulness of this parameter as an objective auxiliary means of diagnosis for MDD.

Identification of atrophy of the subgenual anterior cingulate cortex, in particular the subcallosal area, as an effective auxiliary means of diagnosis for major depressive disorder

“…Atrophy of the sACC was noted in 65 of 71 MDD patients, and the prevalence was higher than that observed in the hippocampus, amygdala, and prefrontal area (in 35, 21, and 20 patients, respectively). The sensitivity, specificity, and accuracy of the diagnosis of MDD based on the presence or absence of atrophy in the sACC was 93%, 85%, and 90%, respectively 4. Accordingly, we suggested that identification of atrophy in the sACC (including a part of the orbitofrontal area) would be useful for accurate auxiliary diagnosis of MDD.…”

“…In previous research, we have focused on the VSRAD plus, an early diagnostic support system for Alzheimer’s disease, which allowed us to identify regional atrophy in the brain easily, based on images obtained from MRI scans 4. We showed that identification of atrophy of the sACC (through a visual method) served as an effective auxiliary means of diagnosis for MDD.…”

Computer-aided detection of depression from magnetic resonance images

“…VSRAD was initially developed for Alzheimer's detection by Niiida et al [26]. It is an automated VBM analysis approach that uses a statistical z-score map.…”

“…It is an automated VBM analysis approach that uses a statistical z-score map. Niida et al [26] applied VSRAD for checking subgenual ACC volume reduction. Images were processed with SPM2 to isolate ROIs, followed by automated statistical analysis of ROIs' density in units of voxel for the entire brain based on anatomical standardization.…”

“…This study demonstrated that user needs to consider proper selection of tools properties in order to utilize it in depression analysis for accurate results. VSRAD was employed by Niida et al [26] who reported a sensitivity of 93%, specificity of 85%, and accuracy of 90% to detect sACC volume reduction of patients receiving treatment of Major Depression Disorder. Bergouignan et al [12] investigated the performance of VBM with SPM5, manual segmentation and an automated segmentation algorithm for comparing Hc structure in depressed patients.…”