|Koo, Bang-Bon -|
|Bergethon, Peter -|
|Qui, Wei Qiao -|
|Scott, Tammy -|
|Hussain, Mohammed -|
|Rosenberg, Irwin -|
|Caplan, Louis R. -|
|Bhadelia, Rafeeque A. -|
Submitted to: Archives of Neurology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: September 30, 2011
Publication Date: June 1, 2012
Citation: Koo, B., Bergethon, P., Qui, W., Scott, T., Hussain, M., Rosenberg, I., Caplan, L., Bhadelia, R. 2012. Clinical prediction of fall risk and white matter abnormalities: a diffusion tensor imaging study. Archives of Neurology. 69(6):733-738. Interpretive Summary: In the elderly, falls are the leading cause of injury death, and are also the most common cause of nonfatal injuries and hospital admissions for trauma. Determining reasons why some individuals are at higher risk for falling will lead to better understanding of this phenomenon and a reduction of related negative health outcomes. The objective of this work was to determine whether individuals who are assessed to be at higher risk for falling have a specific pattern of brain pathology evident during brain imaging. We found that people who are clinically assessed to be at risk for falls had abnormalities in the underlying pathways that connect areas of the brain and that facilitate integrated functioning. These abnormalities were also associated with greater impairment in cognitive function. This information will help us to understand why certain individuals are at higher risk of falling and will aid in assessing this risk.
Technical Abstract: The Tinetti scale is a simple clinical tool designed to predict risk of falling by focusing on gait and stance impairment in elderly persons. Gait impairment is also associated with white matter (WM) abnormalities. Objective: To test the hypothesis that elderly subjects at risk for falling, as determined by the Tinetti scale, have specific patterns of WM abnormalities on diffusion tensor imaging. Community-based cohort of 125 homebound elderly individuals. Diffusion tensor imaging scans were analyzed using tract-based spatial statistics analysis to determine the location of WM abnormalities in subjects with Tinetti scale scores of 25 or higher (without risk of falls) and lower than 25 (with risk of falls). Multivariate linear least squares correlation analysis was performed to determine the association between Tinetti scale scores and local fractional anisotropy values on each skeletal voxel controlling for possible confounders. In subjects with risk of falls (Tinetti scale score >25), clusters of abnormal WM were seen in the medial frontal and parietal subcortical pathways, genu and splenium of corpus callosum, posterior cingulum, prefrontal and orbitofrontal pathways, and longitudinal pathways that connect frontal-parietal-temporal lobes. Among these abnormalities, those in medial frontal and parietal subcortical pathways correlated with Mini-Mental State Examination scores, while the other locations were unrelated to these scores. Elderly individuals at risk for falls as determined by the Tinetti scale have WM abnormalities in specific locations on diffusion tensor imaging, some of which correlate with cognitive function scores.