title: Automated measurement of the human corpus callosum using MRI.
abstract: The corpus callosum includes the majority of fibers that connect the two cortical hemispheres. Studies of cross-sectional callosal morphometry and area have revealed developmental, gender, and hemispheric differences in healthy populations and callosal deficits associated with neurodegenerative disease and brain injury. However, accurate quantification of the callosum using magnetic resonance imaging is complicated by intersubject variability in callosal size, shape, and location and often requires manual outlining of the callosum in order to achieve adequate performance. Here we describe an objective, fully automated protocol that utilizes voxel-based images to quantify the area and thickness both of the entire callosum and of different callosal compartments. We verify the method's accuracy, reliability, robustness, and multisite consistency and make comparisons with manual measurements using public brain-image databases. An analysis of age-related changes in the callosum showed increases in length and reductions in thickness and area with age. A comparison of older subjects with and without mild dementia revealed that reductions in anterior callosal area independently predicted poorer cognitive performance after factoring out Mini-Mental Status Examination scores and normalized whole brain volume. Open-source software implementing the algorithm is available at www.nitrc.org/projects/c8c8.
authors.affiliation: Human Cognitive Neurophysiology Laboratory, Research Service, US Veterans Affairs, Northern California Health Care System Martinez, CA, USA.
authors.forename: Timothy J
authors.initials: TJ
authors.lastname: Herron
authors.forename: Xiaojian
authors.initials: X
authors.lastname: Kang
authors.forename: David L
authors.initials: DL
authors.lastname: Woods