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Diffusion Tensor Imaging (DTI) identifies deficits in white matter microstructure in subjects with type 1 diabetes mellitus that correlate with reduced neurocognitive function

¹University Of Minnesota, Division of Endocrinology, Diabetes, and Metabolism
²University Of Minnesota, Medical Scientist Training Program
³University of Minnesota, Division of Pediatric Clinical Neuroscience
⁴University Of Minnesota, Division of Biostatistics, School of Public Health
⁵University Of Minnesota, Department of Psychiatry
⁶Minneapolis VA Medical Center, Department of Psychiatry and the GRECC

Objective: Long-standing type 1 diabetes mellitus is associated with deficits on neurocognitive testing that suggest central white matter dysfunction. This study investigated whether diffusion tensor imaging, a type of magnetic resonance imaging that measures white matter integrity quantitatively, could identify white matter microstructural deficits in patients with long standing type 1 diabetes and whether these differences would be associated with deficits found by neurocognitive tests.

Research Design and Methods: 25 subjects with type 1 diabetes for at least 15 years and 25 age- and gender-matched control subjects completed diffusion tensor imaging on a 3.0 Tesla scanner and a battery of neurocognitive tests. Fractional anisotropy was calculated for the major white matter tracts of the brain.

Results: Subjects with diabetes had significantly lower mean fractional anisotropy than control subjects in the posterior corona radiata and the optic radiation (p<0.002). In subjects with type 1 diabetes, reduced fractional anisotropy correlated with poorer performance on the copy portion of the Rey-Osterreith Complex Figure Drawing Test and the Grooved Peg Board Test, both of which are believed to assess white matter function. Reduced fractional anisotropy also correlated with duration of diabetes and increased hemoglobin A1c. A history of severe hypoglycemia did not correlate with fractional anisotropy.

Conclusions: Diffusion tensor imaging can detect white matter microstructural deficits in subjects with long standing type 1 diabetes. These deficits correlate with poorer performance on selected neurocognitive tests of white matter function.

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