A Diffusion Weighted Imaging Tract Based Spatial Statistics Study of Autism Spectrum Disorder in Preschool Aged Children

Poster Presentation
Thursday, May 2, 2019: 5:30 PM-7:00 PM
Room: 710 (Palais des congres de Montreal)
D. S. Andrews1, J. K. Lee1, M. Solomon2, S. Rogers1, D. G. Amaral1 and C. W. Nordahl1, (1)Department of Psychiatry and Behavioral Sciences, The Medical Investigation of Neurodevelopmental Disorders (MIND) Institute, UC Davis School of Medicine, University of California Davis, Sacramento, CA, (2)Department of Psychiatry & Behavioral Sciences, The Medical Investigation of Neurodevelopmental Disorders (MIND) Institute, University of California, Davis, Sacramento, CA
Background: The core symptoms of Autism Spectrum Disorder (ASD) are widely theorized to result from altered brain connectivity. Diffusion weighted magnetic resonance imaging (DWI) has been a versatile method for investigating underlying microstructural properties of white matter (WM) in ASD. Despite phenotypic and etiological heterogeneity, DWI studies in majority male samples of older children, adolescents and adults with ASD have largely reported findings of decreased fractional anisotropy (FA) across several commissural, projection, and associative fiber tracts. However, studies in young preschool aged children (<30-40 months) suggest an inverse relationship between WM diffusion properties and ASD earlier in development

Objectives: We sought to characterize WM diffusion properties associated with ASD in a sample of male and female preschool aged children.

Methods: We analyzed 127 individuals with ASD diagnoses (85♂,42♀) and 54 typically developing controls (42♂,26♀), aged 25.1-49.6 months. DWI were acquired in 30 independent directions with five interleaved non-diffusion weighted images. An accompanying phase map image was acquired to correct for field inhomogeneities. Images were preprocessed using MRtrix3 and the FSL diffusion toolbox and included; 1) denoising, 2) Gibbs artifact correction, 3) eddy current correction, 4) between and within volume motion correction, and 5) field distortion correction. Tensor maps were used to calculate corresponding maps of FA, mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD). Whole brain voxel-wise statistical analysis of FA, MD, RD, and AD maps was conducted using tract based spatial statistics (TBSS). Voxel-wise effects of group were estimated by regression of a general linear model including sex, age in months, mean absolute and relative RMS motion parameters as covariates. Interaction effects between group, sex, and age were also tested by adding the appropriate term to the above model.

Results: Males and females with ASD had significantly increased measures of FA in eight clusters (TFCE p<0.05) that incorporated several WM tracts including regions of the genu, body, and splenium of the corpus callosum as well as the corona radiata, inferior and superior longitudinal fasciculi, cerebellar peduncles and corticospinal tract. No significant between group differences were observed for measures of MD, RD, or AD. A group-by-sex interaction was observed in measures of AD across six significant clusters (TFCE p<0.05) incorporating areas of the body, genu, and splenium of the corpus collosum as well as areas of the right corona radiata and external capsule. In these tracts ASD females showed increased AD compared to TD females while ASD males showed decreased AD compared to TD males. No significant group-by-age, sex-by-age, or group-by-sex-by-age interaction effects were observed.

Conclusions: The current findings support growing evidence that young children with ASD have atypical measures of WM microstructure that appear to differ in directionality from alterations observed in older individuals with the condition. To our knowledge this study represents the largest sample of females with ASD to be evaluated using DWI. Microstructural differences associated with ASD largely overlapped between sexes. However, differential relationships of AD measures indicate that sex likely modulates ASD neural phenotypes.

See more of: Neuroimaging
See more of: Neuroimaging