Reduced gray matter volume of left superior temporal gyrus in schizophrenia with auditory verbal hallucinations: a voxel-based morphometry study

AbstractThis study proposes the use of the voxel-based morphometry (VBM) technique to investigate structural alterations of the cerebral cortex in patients with strabismus and amblyopia (SA). Sixteen patients with SA and sixteen healthy controls (HCs) underwent magnetic resonance imaging. Original whole brain images were analyzed using the VBM method. Pearson correlation analysis was performed to evaluate the relationship between mean gray matter volume (GMV) and clinical manifestations. Receiver operating characteristic (ROC) curve analysis was applied to classify the mean GMV values of the SA group and HCs. Compared with the HCs, GMV values in the SA group showed a significant difference in the right superior temporal gyrus, posterior and anterior lobes of the cerebellum, bilateral parahippocampal gyrus, and left anterior cingulate cortex. The mean GMV value in the right superior temporal gyrus, posterior and anterior lobes of the cerebellum, and bilateral parahippocampal gyrus were negatively correlated with the angle of strabismus. The ROC curve analysis of each cerebral region confirmed the accuracy of the area under the curve. Patients with SA have reduced GMV values in some brain regions. These findings might help to reveal the potential pathogenesis of SA and its relationship with the atrophy of specific regions of the brain.

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Age- and Sex-Related Cortical Gray Matter Volume Differences in Adolescent Cannabis Users: A Systematic Review and Meta-Analysis of Voxel-Based Morphometry Studies

Frontiers in Psychiatry ◽

10.3389/fpsyt.2021.745193 ◽

2021 ◽

Vol 12 ◽

Author(s):

Aliyah Allick ◽

Grace Park ◽

Kwon Kim ◽

Michelle Vintimilla ◽

Krutika Rathod ◽

...

Keyword(s):

Systematic Review ◽

Gray Matter ◽

Meta Analysis ◽

Gray Matter Volume ◽

Superior Temporal Gyrus ◽

Voxel Based Morphometry ◽

Whole Brain ◽

Male Youth ◽

Matter Volume ◽

Age And Sex

Introduction: Adolescent-onset cannabis use is rising in the era of marijuana legalization. Recent imaging studies have identified neuroanatomical differences between adult cannabis users and controls that are more prominent in early-onset users. Other studies point to sex-dependent effects of cannabis.Methods: A systematic review following PRISMA guidelines and subsequent effect-size seed-based d mapping (SDM) meta-analyses were conducted to investigate relationships between age (across the 12-to-21-year-old developmental window), sex, and gray matter volume (GMV) differences between cannabis using (CU) and typically developing (TD) youth.Results: Our search identified 1,326 citations, 24 of which were included in a qualitative analysis. A total of 6 whole-brain voxel-based morphometry (VBM) studies comparing regional GMV between 357 CU [mean (SD) age = 16.68 (1.28); 71% male] and 404 TD [mean (SD) age = 16.77 (1.36); 63% male] youth were included in the SDM-meta-analysis. Meta-analysis of whole-brain VBM studies identified no regions showing significant GMV difference between CU and TD youth. Meta-regressions showed divergent effects of age and sex on cortical GMV differences in CU vs. TD youth. Age effects were seen in the superior temporal gyrus (STG), with older-aged CU youth showing decreased and younger-aged CU youth showing increased STG GMV compared to age-matched TD youth. Parallel findings in the STG were also observed in relation to duration of CU (years) in supplemental meta-regressions. Regarding sex effects, a higher proportion of females in studies was associated with increased GMV in the middle occipital gyrus in CU vs. TD youth.Conclusions: These findings suggest that GMV differences between CU and TD youth, if present, are subtle, and may vary as a function of age, cumulative cannabis exposure, and sex in young people. Whether age- and sex-related GMV differences are attributable to common predispositional factors, cannabis-induced neuroadaptive changes, or both warrant further investigation.

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Reproducibility of Brain Volume Changes in Longitudinal Voxel-Based Morphometry Between Non-Accelerated and Accelerated Magnetic Resonance Imaging

Journal of Alzheimer s Disease ◽

10.3233/jad-210596 ◽

2021 ◽

pp. 1-10

Author(s):

Hidemasa Takao ◽

Shiori Amemiya ◽

Osamu Abe ◽

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Magnetic Resonance ◽

Gray Matter ◽

Gray Matter Volume ◽

Elderly Subjects ◽

Voxel Based Morphometry ◽

Volume Changes ◽

Matter Volume ◽

Healthy Elderly

Background: Scan acceleration techniques, such as parallel imaging, can reduce scan times, but reliability is essential to implement these techniques in neuroimaging. Objective: To evaluate the reproducibility of the longitudinal changes in brain morphology determined by longitudinal voxel-based morphometry (VBM) between non-accelerated and accelerated magnetic resonance images (MRI) in normal aging, mild cognitive impairment (MCI), and Alzheimer’s disease (AD). Methods: Using data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) 2 database, comprising subjects who underwent non-accelerated and accelerated structural T1-weighted MRI at screening and at a 2-year follow-up on 3.0 T Philips scanners, we examined the reproducibility of longitudinal gray matter volume changes determined by longitudinal VBM processing between non-accelerated and accelerated imaging in 50 healthy elderly subjects, 54 MCI patients, and eight AD patients. Results: The intraclass correlation coefficient (ICC) maps differed among the three groups. The mean ICC was 0.72 overall (healthy elderly, 0.63; MCI, 0.75; AD, 0.63), and the ICC was good to excellent (0.6–1.0) for 81.4%of voxels (healthy elderly, 64.8%; MCI, 85.0%; AD, 65.0%). The differences in image quality (head motion) were not significant (Kruskal–Wallis test, p = 0.18) and the within-subject standard deviations of longitudinal gray matter volume changes were similar among the groups. Conclusion: The results indicate that the reproducibility of longitudinal gray matter volume changes determined by VBM between non-accelerated and accelerated MRI is good to excellent for many regions but may vary between diseases and regions.

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Is Gray Matter Volume an Intermediate Phenotype for Schizophrenia? A Voxel-Based Morphometry Study of Patients with Schizophrenia and Their Healthy Siblings

Biological Psychiatry ◽

10.1016/j.biopsych.2007.05.027 ◽

2008 ◽

Vol 63 (5) ◽

pp. 465-474 ◽

Cited By ~ 139

Author(s):

Robyn A. Honea ◽

Andreas Meyer-Lindenberg ◽

Katherine B. Hobbs ◽

Lukas Pezawas ◽

Venkata S. Mattay ◽

...

Keyword(s):

Gray Matter ◽

Gray Matter Volume ◽

Intermediate Phenotype ◽

Voxel Based Morphometry ◽

Matter Volume ◽

Healthy Siblings

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Putaminal gray matter volume decrease in panic disorder: an optimized voxel-based morphometry study

European Journal of Neuroscience ◽

10.1111/j.1460-9568.2005.04394.x ◽

2005 ◽

Vol 22 (8) ◽

pp. 2089-2094 ◽

Cited By ~ 68

Author(s):

Hanik K. Yoo ◽

Minue J. Kim ◽

Seog Ju Kim ◽

Young Hoon Sung ◽

Minyoung E. Sim ◽

...

Keyword(s):

Panic Disorder ◽

Gray Matter ◽

Gray Matter Volume ◽

Voxel Based Morphometry ◽

Matter Volume ◽

Volume Decrease

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Voxel-Based Morphometry Reveals a Correlation Between Bone Mineral Density Loss and Reduced Cortical Gray Matter Volume in Alzheimer’s Disease

Frontiers in Aging Neuroscience ◽

10.3389/fnagi.2020.00178 ◽

2020 ◽

Vol 12 ◽

Author(s):

Yumi Takano ◽

Yasuko Tatewaki ◽

Tatsushi Mutoh ◽

Naoya Morota ◽

Izumi Matsudaira ◽

...

Keyword(s):

Bone Mineral Density ◽

Alzheimer’S Disease ◽

Bone Mineral ◽

Gray Matter ◽

Gray Matter Volume ◽

Voxel Based Morphometry ◽

Mineral Density ◽

Bone Mineral Density Loss ◽

Matter Volume ◽

Cortical Gray Matter

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The Gray Matter Volume of the Amygdala Is Correlated with the Perception of Melodic Intervals: A Voxel-Based Morphometry Study

PLoS ONE ◽

10.1371/journal.pone.0099889 ◽

2014 ◽

Vol 9 (6) ◽

pp. e99889 ◽

Cited By ~ 4

Author(s):

Xueting Li ◽

Alain De Beuckelaer ◽

Jiahui Guo ◽

Feilong Ma ◽

Miao Xu ◽

...

Keyword(s):

Gray Matter ◽

Gray Matter Volume ◽

Voxel Based Morphometry ◽

Matter Volume

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Effects of cumulative illness severity on hippocampal gray matter volume in major depression: a voxel-based morphometry study

Psychological Medicine ◽

10.1017/s0033291718000016 ◽

2018 ◽

Vol 48 (14) ◽

pp. 2391-2398 ◽

Cited By ~ 13

Author(s):

Dario Zaremba ◽

Verena Enneking ◽

Susanne Meinert ◽

Katharina Förster ◽

Christian Bürger ◽

...

Keyword(s):

Major Depression ◽

Gray Matter ◽

Gray Matter Volume ◽

Principal Component ◽

Hippocampal Volume ◽

Illness Severity ◽

Voxel Based Morphometry ◽

Matter Volume ◽

Duration Of Illness ◽

Component Scores

AbstractBackgroundPatients with major depression show reduced hippocampal volume compared to healthy controls. However, the contribution of patients’ cumulative illness severity to hippocampal volume has rarely been investigated. It was the aim of our study to find a composite score of cumulative illness severity that is associated with hippocampal volume in depression.MethodsWe estimated hippocampal gray matter volume using 3-tesla brain magnetic resonance imaging in 213 inpatients with acute major depression according to DSM-IV criteria (employing the SCID interview) and 213 healthy controls. Patients’ cumulative illness severity was ascertained by six clinical variables via structured clinical interviews. A principal component analysis was conducted to identify components reflecting cumulative illness severity. Regression analyses and a voxel-based morphometry approach were used to investigate the influence of patients’ individual component scores on hippocampal volume.ResultsPrincipal component analysis yielded two main components of cumulative illness severity: Hospitalization and Duration of Illness. While the component Hospitalization incorporated information from the intensity of inpatient treatment, the component Duration of Illness was based on the duration and frequency of illness episodes. We could demonstrate a significant inverse association of patients’ Hospitalization component scores with bilateral hippocampal gray matter volume. This relationship was not found for Duration of Illness component scores.ConclusionsVariables associated with patients’ history of psychiatric hospitalization seem to be accurate predictors of hippocampal volume in major depression and reliable estimators of patients’ cumulative illness severity. Future studies should pay attention to these measures when investigating hippocampal volume changes in major depression.

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