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BACKGROUND: Automated magnetic resonance imaging (MRI) volumetry is a promising tool to evaluate regional brain volumes in dementia and especially Alzheimer's disease (AD). PURPOSE: To compare automated methods and the gold standard manual segmentation in measuring regional brain volumes on MRI across healthy controls, patients with mild cognitive impairment, and patients with dementia due to AD. STUDY TYPE: Systematic review and meta-analysis. DATA SOURCES: MEDLINE, Embase, and PsycINFO were searched through October 2021. FIELD STRENGTH: 1.0 T, 1.5 T, or 3.0 T. ASSESSMENT: Two review authors independently identified studies for inclusion and extracted data. Methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). STATISTICAL TESTS: Standardized mean differences (SMD; Hedges' g) were pooled using random-effects meta-analysis with robust variance estimation. Subgroup analyses were undertaken to explore potential sources of heterogeneity. Sensitivity analyses were conducted to examine the impact of the within-study correlation between effect estimates on the meta-analysis results. RESULTS: Seventeen studies provided sufficient data to evaluate the hippocampus, lateral ventricles, and parahippocampal gyrus. The pooled SMD for the hippocampus, lateral ventricles, and parahippocampal gyrus were 0.22 (95% CI -0.50 to 0.93), 0.12 (95% CI -0.13 to 0.37), and -0.48 (95% CI -1.37 to 0.41), respectively. For the hippocampal data, subgroup analyses suggested that the pooled SMD was invariant across clinical diagnosis and field strength. Subgroup analyses could not be conducted on the lateral ventricles data and the parahippocampal gyrus data due to insufficient data. The results were robust to the selected within-study correlation value. DATA CONCLUSION: While automated methods are generally comparable to manual segmentation for measuring hippocampal, lateral ventricle, and parahippocampal gyrus volumes, wide 95% CIs and larg

This article describes source data from a systematic review and meta-analysis of electroencephalography (EEG) and magnetoencephalography (MEG) studies investigating functional connectivity in idiopathic generalized epilepsy. Data selection, analysis and reporting was performed according to PRISMA guidelines. Eligible studies for review were identified from human case-control, and cohort studies. Twenty-two studies were included in the review. Extracted descriptive data included sample characteristics, acquisition of EEG or MEG recordings and network construction. Reported differences between IGE and control groups in functional connectivity or network metrics were extracted as the main outcome measure. Qualitative group differences in functional connectivity were synthesized through narrative review. Meta-analysis was performed for group-level, quantitative estimates of common network metrics clustering coefficient, path length, mean degree and nodal strength. Six studies were included in the meta-analysis. Risk of bias was assessed across all studies. Raw and synthesized data for included studies are reported, alongside effect size and heterogeneity statistics from meta-analyses. Network neurosciences is a rapidly expanding area of research, with significant potential for clinical applications in epilepsy. This data article provides novel, statistical estimates of brain network differences from patients with IGE relative to healthy controls, across the existing literature. Increasing data accessibility supports study replication and improves study comparability for future reviews, enabling a better understanding of network characteristics in IGE.