White matter abnormalities in children with chronic kidney disease. Abstract: Children suffering from chronic kidney disease demonstrate a wide range of neurocognitive difficulties and deficits. This cohort is also at risk for vascular disease and stroke. Those who have undergone a successful renal transplantation show improved cognitive scores when compared to chronic kidney disease patients without transplant. Tissue injury and changes in white matter microstructure are associated with cognitive deficits. Diffusion tensor imaging allows for a quantitative measurement of water diffusion within brain tissues. Fractional anisotropy, mean diffusivity and radial diffusivity are measures that are sensitive to injury or changes in white matter microstructure. We analyzed diffusion tensor imaging data from three groups of children; normal children (n=18), chronic kidney disease patients (n=16) and patients who had undergone renal transplant (n=6). Tract based spatial statistics was used to objectively identify regions of interest for analysis in each subject’s native space. We hypothesized that chronic kidney disease patients would have lower fractional anisotropy and higher mean and radial diffusivity than both the control and transplant groups. We also expected the transplant group to have lower fractional anisotropy and higher mean and radial diffusivity than the control group. Tract based spatial statistics identified 3 regions of interest that displayed group differences in diffusion measures: Anterior limb of the internal capsule, posterior limb of the internal capsule and the optic radiations. Region of interest analysis showed decreased fractional anisotropy in the left anterior limb of the internal capsule in both CKD and transplant groups compared to the control group. Project type: Analysis of existing data Imaging keywords: Diffusion tensor imaging (DTI) Application / disease keywords: Chronic kidney disease (CKD) Renal transplantation Stroke Supervisor(s): Dr Steven Miller Dr Susana Muñoz-Maniega Programme: Neuroimaging for Research MSc Year: 11-12 This article was published on 2024-08-22