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Bipolar Disorder Neuroimaging Database

Database of 141 studies which have investigated brain structure (using MRI and CT scans) in patients with bipolar disorder compared to a control group. Ninety-eight studies and 47 brain structures are included in the meta-analysis. The database and meta-analysis are contained in an Excel spreadsheet file which may be freely downloaded from this website.

URL: https://sites.google.com/site/bipolardatabase/

Resource ID: nlx_149352     Resource Type: Resource     Version: Latest Version

Keywords

magnetic resonance imaging assay, cat imaging assay, mri, brain, neuroimaging, normal control, image

Additional Resource Types

database

Species

human

Publication Link

http://archpsyc.jamanetwork.com/article.aspx?articleid=210132

Abbreviation

BiND

Synonyms

Bipolar Disorder Neuroimaging Database (BiND)

Parent Organization

Funding Information

King's College London; England; United Kingdom, National Institute for Health Research NIHR Biomedical Research Centre for Mental Health, South London and Maudsley NHS Foundation, MRC,

Related Disease

Bipolar Disorder

Supercategory

Resource

Original Submitter

Anonymous

Version Status

Curated

Submitted On

12:00am July 22, 2012

Originated From

SciCrunch

Changes from Previous Version

First Version

Version 1

Created 3 years ago by Anonymous

Meta-analysis, database, and meta-regression of 98 structural imaging studies in bipolar disorder.

  • Kempton MJ
  • Arch. Gen. Psychiatry
  • 2008 2

CONTEXT: Despite 25 years of structural imaging in bipolar disorder, brain regions affected in the disorder are ill defined. OBJECTIVES: To use meta-analytical techniques to investigate structural brain changes in bipolar disorder and to assess the effect of medication use and demographic and clinical variables. DATA SOURCES: The MEDLINE, EMBASE, and PsycINFO databases were searched from 1980-2007 for studies using magnetic resonance imaging or x-ray computed tomography to compare brain structure in patients with bipolar disorder and controls. STUDY SELECTION: We identified 1471 unique publications from which 141 studies were included in a database and 98 were selected for meta-analysis. DATA EXTRACTION: Twenty-six demographic and clinical variables were extracted from each study where available. For the meta-analysis, mean structure size and standard deviation were extracted for continuous variables, and numbers of patients and controls with an abnormality were extracted for binary variables. DATA SYNTHESIS: Bipolar disorder was associated with lateral ventricle enlargement (effect size = 0.39; 95% confidence interval, 0.24-0.55; P = 8 x 10(-7)) and increased rates of deep white matter hyperintensities (odds ratio = 2.49; 95% confidence interval, 1.64-3.79; P = 2 x 10(-5)) but not periventricular hyperintensities. Gray matter volume increased among patients when the proportion of patients using lithium increased (P = .004). Calculations from this meta-analysis show current imaging studies (which typically examine 8 regions) have a 34% chance of making a type I error. Type II errors are also appreciable (for example, 70% when measuring the lateral ventricular volume in a typical study involving 25 patients and 33 controls). CONCLUSIONS: The meta-analyses revealed robust but regionally nonspecific changes of brain structure in bipolar disorder. Individual studies will remain underpowered unless sample size is increased or improvements in phenotypic selection and imaging methods are made to reduce within-study heterogeneity. The provision of online databases, as illustrated herein, may facilitate a more refined design and analysis of structural imaging data sets in bipolar disorder.