Neurite orientation dispersion and density imaging reveals white matter microstructural alterations in adults with autism

Abstract

Abstract Background Evidences suggesting the association between behavioral anomalies in autism and white matter (WM) microstructural alterations are increasing. Diffusion tensor imaging (DTI) is widely used to infer tissue microstructure. However, due to its lack of specificity, the underlying pathology of reported differences in DTI measures in autism remains poorly understood. Herein, we applied neurite orientation dispersion and density imaging (NODDI) to quantify and define more specific causes of WM microstructural changes associated with autism in adults. Methods NODDI (neurite density index [NDI], orientation dispersion index, and isotropic volume fraction [ISOVF]) and DTI (fractional anisotropy [FA], mean diffusivity [MD], axial diffusivity, and radial diffusivity [RD]) measures were compared between autism (N = 26; 19 males and 7 females; 32.93 ± 9.24 years old) and age- and sex-matched typically developing (TD; N = 25; 17 males and 8 females; 34.43 ± 9.02 years old) groups using tract-based spatial statistics and region-of-interest analyses. Linear discriminant analysis using leave-one-out cross-validation (LDA-LOOCV) was also performed to assess the discriminative power of diffusion measures in autism and TD. Results Significantly lower NDI and higher ISOVF, suggestive of decreased neurite density and increased extracellular free-water, respectively, were demonstrated in the autism group compared with the TD group, mainly in commissural and long-range association tracts, but with distinct predominant sides. Consistent with previous reports, the autism group showed lower FA and higher MD and RD when compared with TD group. Notably, LDA-LOOCV suggests that NDI and ISOVF have relatively higher accuracy (82%) and specificity (NDI, 84%; ISOVF, 88%) compared with that of FA, MD, and RD (accuracy, 67–73%; specificity, 68–80%). Limitations The absence of histopathological confirmation limit the interpretation of our findings. Conclusions Our results suggest that NODDI measures might be useful as imaging biomarkers to diagnose autism in adults and assess its behavioral characteristics. Furthermore, NODDI allows interpretation of previous findings on changes in WM diffusion tensor metrics in individuals with autism.

Keywords

• Autism
• Diffusion tensor imaging
• Linear discriminant analysis
• Neuronal loss
• Neuroinflammation
• Neurite orientation dispersion and density imaging