Article

High Connectivity Between Reduced Cortical Thickness and Disrupted White Matter Tracts in Long-Standing Type 1 Diabetes

University of Minnesota Medical School, Minneapolis, USA.
Diabetes (Impact Factor: 8.47). 10/2010; 60(1):315-9. DOI: 10.2337/db10-0598
Source: PubMed

ABSTRACT Previous studies have observed disruptions in brain white and gray matter structure in individuals with type 1 diabetes, and these structural differences have been associated with neurocognitive testing deficiencies. This study investigated the relationship between cerebral cortical thickness reductions and white matter microstructural integrity loss in a group of patients with type 1 diabetes and in healthy control subjects using diffusion tensor imaging (DTI).
Twenty-five subjects with type 1 diabetes for at least 15 years and 25 age- and sex-matched control subjects underwent structural T1 and proton-density and DTI on a 3.0 Tesla scanner. Fractional anisotropy measurements were made on major cerebral white matter tracts, and DTI tractography was performed to identify cortical regions with high connectivity to these tracts.
Posterior white matter tracts with reduced fractional anisotropy (optic radiations, posterior corona radiata, and the splenium region of the corpus callosum) were found to have high connectivity with a number of posterior cortical regions, including the cuneus, precuneus, fusiform, and posterior parietal cortical regions. A significant reduction in cortical thickness in the diabetic group was observed in the regions with high connectivity to the optic radiations and posterior corona radiata tracts (P < 0.05).
The direct relationship between white and gray matter structural pathology has not been previously demonstrated in subjects with long-standing type 1 diabetes. The relationship between posterior white matter microstructural integrity disruption and lower cortical thickness demonstrated using a novel DTI connectivity technique suggests a common or interrelated pathophysiological mechanism in type 1 diabetes.

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