A meta-analysis of voxel-based morphometry studies on gray matter volume alteration in juvenile myoclonic epilepsy

2013 ◽  
Vol 106 (3) ◽  
pp. 370-377 ◽  
Author(s):  
Bei Cao ◽  
YingYing Tang ◽  
JianPeng Li ◽  
Xiang Zhang ◽  
Hui-Fang Shang ◽  
...  
Keyword(s):  
Gray Matter ◽  
Meta Analysis ◽  
Gray Matter Volume ◽  
Juvenile Myoclonic Epilepsy ◽  
Myoclonic Epilepsy ◽  
Voxel Based Morphometry ◽  
Matter Volume

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

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.

scholarly journals Gray matter abnormalities in Tourette Syndrome: a meta-analysis of voxel-based morphometry studies

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xinyue Wan ◽  
Simin Zhang ◽  
Weina Wang ◽  
Xiaorui Su ◽  
Jun Li ◽  
...  
Keyword(s):  
Tourette Syndrome ◽  
Gray Matter ◽  
Clinical Characteristics ◽  
Meta Analysis ◽  
Gray Matter Volume ◽  
Brain Regions ◽  
Voxel Based Morphometry ◽  
Matter Volume ◽  
Meta Regression ◽  
Meta Regression Analysis

AbstractTourette syndrome (TS) is a neurobehavioral disorder for which the neurological mechanism has not been elucidated. Voxel-based morphometry (VBM) studies have revealed abnormalities in gray matter volume (GMV) in patients with TS; however, consistent results have not been obtained. The current study attempted to provide a voxel wise meta-analysis of gray matter changes using seed-based d mapping (SDM). We identified ten relevant studies that investigated gray matter alterations in TS patients and performed a meta-analysis using the SDM method to quantitatively estimate regional gray matter abnormalities. Next, we examined the relationships between GMV abnormalities and demographic and clinical characteristics. Our results demonstrated that TS patients had smaller GMV in the bilateral inferior frontal gyri and greater GMV in the cerebellum, right striatum (putamen), and bilateral thalami (pulvinar nucleus) than healthy controls. A meta-regression analysis did not identify correlations between GMV changes and demographic or clinical variables. This meta-analysis confirmed significant and consistent GMV changes in several brain regions of TS patients, primarily in the cortico-striato-thalamo-cortical network.

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

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.

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

2008 ◽  
Vol 63 (5) ◽  
pp. 465-474 ◽  
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

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

2005 ◽  
Vol 22 (8) ◽  
pp. 2089-2094 ◽  
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

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

PLoS ONE ◽  
2014 ◽  
Vol 9 (6) ◽  
pp. e99889 ◽  
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

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

2018 ◽  
Vol 48 (14) ◽  
pp. 2391-2398 ◽  
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.

Sign in / Sign up

Export Citation Format

Share Document