Sex-related differences in behavior are extensive, but their neuroanatomic substrate is unclear. Indirect perfusion data have suggested a higher percentage of gray matter (GM) in left hemisphere cortex and in women, but differences in volumes of the major cranial compartments have not been examined for the entire brain in association with cognitive performance. We used volumetric segmentation of dual echo (proton density and T2-weighted) magnetic resonance imaging (MRI) scans in healthy volunteers (40 men, 40 women) age 18-45. Supertentorial volume was segmented into GM, white matter (WM), and CSF. We confirmed that women have a higher percentage of GM, whereas men have a higher percentage of WM and of CSF. These differences sustained a correction for total intracranial volume. In men the slope of the relation between cranial volume and GM paralleled that for WM, whereas in women the increase in WM as a function of cranial volume was at a lower rate. In men the percentage of GM was higher in the left hemisphere, the percentage of WM was symmetric, and the percentage of CSF was higher in the right. Women showed no asymmetries. Both GM and WM volumes correlated moderately with global, verbal, and spatial performance across groups. However, the regression of cognitive performance and WM volume was significantly steeper in women. Because GM consists of the somatodendritic tissue of neurons whereas WM comprises myelinated connecting axons, the higher percentage of GM makes more tissue available for computation relative to transfer across distant regions. This could compensate for smaller intracranial space in women. Sex difference in the percentage and asymmetry of the principal cranial tissue volumes may contribute to differences in cognitive functioning.

In this work, we developed, implemented, and validated an image-processing system for qualitative and quantitative volumetric analysis of brain images. This system allows the visualization and quantitation of global and regional brain volumes. Global volumes were obtained via an automated adaptive Bayesian segmentation technique that labels the brain into white matter, gray matter, and cerebrospinal fluid. Absolute volumetric errors for these compartments ranged between 1 and 3% as indicated by phantom studies. Quantitation of regional brain volumes was performed through normalization and tessellation of segmented brain images into the Talairach space with a 3D elastic warping model. Retest reliability of regional volumes measured in Talairach space indicated errors of < 1.5% for the frontal, parietal, temporal, and occipital brain regions. Additional regional analysis was performed with an automated hybrid method combining a region-of-interest approach and voxel-based analysis, named Regional Analysis of Volumes Examined in Normalized Space (RAVENS). RAVENS analysis for several subcortical structures showed good agreement with operator-defined volumes. This system has sufficient accuracy for longitudinal imaging data and is currently being used in the analysis of neuroimaging data of the Baltimore Longitudinal Study of Aging.

Background: Cortical gray matter volume reductions and cerebrospinal fluid (CSF) volume increases are robust correlates of schizophrenia, but their sources have not been established conclusively.