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Distinguishing Between Treatment-Resistant and Non-Treatment-Resistant Schizophrenia Using Regional Homogeneity.

ABSTRACT: Background: Patients with treatment-resistant schizophrenia (TRS) and non-treatment-resistant schizophrenia (NTRS) respond to antipsychotic drugs differently. Previous studies demonstrated that patients with TRS or NTRS exhibited abnormal neural activity in different brain regions. Accordingly, in the present study, we tested the hypothesis that a regional homogeneity (ReHo) approach could be used to distinguish between patients with TRS and NTRS. Methods: A total of 17 patients with TRS, 17 patients with NTRS, and 29 healthy controls (HCs) matched in sex, age, and education levels were recruited to undergo resting-state functional magnetic resonance imaging (RS-fMRI). ReHo was used to process the data. ANCOVA followed by post-hoc t-tests, receiver operating characteristic curves (ROC), and correlation analyses were applied for the data analysis. Results: ANCOVA analysis revealed widespread differences in ReHo among the three groups in the occipital, frontal, temporal, and parietal lobes. ROC results indicated that the optimal sensitivity and specificity of the ReHo values in the left postcentral gyrus, left inferior frontal gyrus/triangular part, and right fusiform could differentiate TRS from NTRS, TRS from HCs, and NTRS from HCs were 94.12 and 82.35%, 100 and 86.21%, and 82.35 and 93.10%, respectively. No correlation was found between abnormal ReHo and clinical symptoms in patients with TRS or NTRS. Conclusions: TRS and NTRS shared most brain regions with abnormal neural activity. Abnormal ReHo values in certain brain regions might be applied to differentiate TRS from NTRS, TRS from HC, and NTRS from HC with high sensitivity and specificity.

SUBMITTER: Gao S

PROVIDER: S-EPMC6088138 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Distinguishing Between Treatment-Resistant and Non-Treatment-Resistant Schizophrenia Using Regional Homogeneity.

Gao Shuzhan S Lu Shuiping S Shi Xiaomeng X Ming Yidan Y Xiao Chaoyong C Sun Jing J Yao Hui H Xu Xijia X

Frontiers in psychiatry 20180806

<b>Background:</b> Patients with treatment-resistant schizophrenia (TRS) and non-treatment-resistant schizophrenia (NTRS) respond to antipsychotic drugs differently. Previous studies demonstrated that patients with TRS or NTRS exhibited abnormal neural activity in different brain regions. Accordingly, in the present study, we tested the hypothesis that a regional homogeneity (ReHo) approach could be used to distinguish between patients with TRS and NTRS. <b>Methods:</b> A total of 17 patients wi ...[more]

PMID: 30127752

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Project description:ImportanceSchizophrenia is associated with alterations in mean regional brain volumes. However, it is not known whether the clinical heterogeneity seen in the disorder is reflected at the neurobiological level, for example, in differences in the interindividual variability of these brain volumes relative to control individuals.ObjectiveTo investigate whether patients with first-episode schizophrenia exhibit greater variability of regional brain volumes in addition to mean volume differences.Data sourcesStudies that reported regional brain volumetric measures in patients and controls by using magnetic resonance imaging in the MEDLINE, EMBASE, and PsycINFO databases from inception to October 1, 2016, were examined.Study selectionCase-control studies that reported regional brain volumes in patients with first-episode schizophrenia and healthy controls by using magnetic resonance imaging were selected.Data extraction and synthesisMeans and variances (SDs) were extracted for each measure to calculate effect sizes, which were combined using multivariate meta-analysis.Main outcomes and measuresRelative variability of regional brain volumetric measurements in patients compared with control groups as indexed by the variability ratio (VR) and coefficient of variation ratio (CVR). Hedges g was used to quantify mean differences.ResultsA total of 108 studies that reported measurements from 3901 patients (1272 [32.6%] female) with first-episode schizophrenia and 4040 controls (1613 [39.9%] female) were included in the analyses. Variability of putamen (VR, 1.13; 95% CI, 1.03-1.24; P = .01), temporal lobe (VR, 1.12; 95% CI, 1.04-1.21; P = .004), thalamus (VR, 1.16; 95% CI, 1.07-1.26; P < .001), and third ventricle (VR, 1.43; 95% CI, 1.20-1.71; P < 1 × 10-5) volume was significantly greater in patients, whereas variability of anterior cingulate cortex volume was lower (VR, 0.89; 95% CI, 0.81-0.98; P = .02). These findings were robust to choice of outcome measure. There was no evidence of altered variability of caudate nucleus or frontal lobe volumes. Mean volumes of the lateral (g = 0.40; 95% CI, 0.29-0.51; P < .001) and third ventricles (g = 0.43; 95% CI, 0.26-0.59; P < .001) were greater, whereas mean volumes of the amygdala (g = -0.46; -0.65 to -0.26; P < .001), anterior cingulate cortex (g = -0.26; 95% CI, -0.43 to -0.10; P = .005), frontal lobe (g = -0.31; 95% CI, -0.44 to -0.19; P = .001), hippocampus (g = -0.66; 95% CI, -0.84 to -0.47; P < .001), temporal lobe (g = -0.22; 95% CI, -0.36 to -0.09; P = .001), and thalamus (g = -0.36; 95% CI, -0.57 to -0.15; P = .001) were lower in patients. There was no evidence of altered mean volume of caudate nucleus or putamen.Conclusions and relevanceIn addition to altered mean volume of many brain structures, schizophrenia is associated with significantly greater variability of temporal cortex, thalamus, putamen, and third ventricle volumes, consistent with biological heterogeneity in these regions, but lower variability of anterior cingulate cortex volume. This finding indicates greater homogeneity of anterior cingulate volume and, considered with the significantly lower mean volume of this region, suggests that this is a core region affected by the disorder.

Project description:Background: Melancholic depression has been viewed as one severe subtype of major depressive disorder (MDD). However, it is unclear whether melancholic depression has distinct changes in brain imaging. We aimed to explore specific or distinctive alterations in melancholic MDD and whether the alterations could be used to separate melancholic MDD from non-melancholic MDD or healthy controls. Materials and Methods: Thirty-one outpatients with melancholic MDD and thirty-three outpatients with non-melancholic MDD and thirty-two age- and gender-matched healthy controls were recruited. All participants were scanned by resting-state functional magnetic resonance imaging (fMRI). Imaging data were analyzed with the regional homogeneity (ReHo) and support vector machine (SVM) methods. Results: Melancholic MDD patients exhibited lower ReHo in the right superior occipital gyrus/middle occipital gyrus than non-melancholic MDD patients and healthy controls. Merely for non-melancholic MDD patients, decreased ReHo in the right middle frontal gyrus was negatively correlated with the total HRSD-17 scores. SVM analysis results showed that a combination of abnormal ReHo in the right fusiform gyrus/cerebellum Crus I and the right superior occipital gyrus/middle occipital gyrus exhibited the highest accuracy of 83.05% (49/59), with a sensitivity of 90.32% (28/31), and a specificity of 75.00% (21/28) for discriminating patients with melancholic MDD from patients with non-melancholic MDD. And a combination of abnormal ReHo in the right fusiform gyrus/cerebellum VI and left postcentral gyrus/precentral gyrus exhibited the highest accuracy of 98.41% (62/63), with a sensitivity of 96.77% (30/31), and a specificity of 100.00%(32/32) for separating patients with melancholic MDD from healthy controls. Conclusion: Our findings showed the distinctive ReHo pattern in patients with melancholic MDD and found brain area that may be associated with the pathophysiology of non-melancholic MDD. Potential imaging markers for discriminating melancholic MDD from non-melancholic MDD or healthy controls were reported.

Project description:The aim of this study is to determine whether regional homogeneity (ReHo) of resting-state blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (rsfMRI) data based on Kendall's coefficient of concordance (KCC-ReHo) and coherence (Cohe-ReHo) metrics may allow detection of brain tumor-induced neurovascular uncoupling (NVU) in the sensorimotor network similar to findings in standard motor task-based BOLD fMRI (tbfMRI) activation. Twelve de novo brain tumor patients undergoing clinical fMRI exams (tbfMRI and rsfMRI) were included in this Institutional Review Board (IRB)-approved study. Each patient displayed decreased/absent tbfMRI activation in the primary ipsilesional sensorimotor cortex in the absence of corresponding motor deficit or suboptimal task performance, consistent with NVU. Z-score maps for motor tasks were obtained from the general linear model (GLM) analysis (reflecting motor activation vs. rest). KCC-ReHo and Cohe-ReHo maps were calculated from rsfMRI data. Precentral and postcentral gyri in contralesional (CL) and ipsilesional (IL) hemispheres were parcellated using an automated anatomical labeling (AAL) template for each patient. Similar region of interest (ROI) analysis was performed on tbfMRI, KCC-ReHo, and Cohe-ReHo maps to allow direct comparison of results. Voxel values in CL and IL ROIs of each map were divided by the corresponding global mean of KCC-ReHo and Cohe-ReHo in bihemispheric cortical brain tissue. Group analysis revealed significantly decreased IL mean KCC-ReHo (p?=?0.02) and Cohe-ReHo (p?=?0.04) metrics compared with respective values in the CL ROIs, consistent with similar findings of significantly decreased ipsilesional BOLD signal for tbfMRI (p?=?0.0005). Ipsilesional abnormalities in ReHo derived from rsfMRI may serve as potential indicators of NVU in patients with brain tumors and other resectable brain lesions; as such, ReHo findings may complement findings on tbfMRI used for presurgical planning.

Dataset Information

Distinguishing Between Treatment-Resistant and Non-Treatment-Resistant Schizophrenia Using Regional Homogeneity.

Publications

Distinguishing Between Treatment-Resistant and Non-Treatment-Resistant Schizophrenia Using Regional Homogeneity.

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