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

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.

Atypical structural connectivity of language networks in autism spectrum disorder: A meta‐analysis of diffusion tensor imaging studies

“…On the other hand, MD increases were observed in language‐related tracts in children and adults with ASD. The distinction between FA and MD results in adults was also reported in previous experimental DTI studies (Andica et al, 2021; Catani et al, 2016). These deviations may result from the distinctive trajectories of diffusion parameters with age.…”

“…Besides, a few studies disposed of the artifacts and head motion in the image acquisition (Kumar et al, 2010; Samson et al, 2016; Thomas et al, 2011). For the ROI tracts, 29 articles investigated the dorsal pathway (AF/SLF) (such as Andica et al, 2021; Kato et al, 2019; Lei et al, 2019), and 17, 13, and 17 studies involved UF, IFOF, and ILF, respectively. For DTI metrics, FA and MD were reported more generally than other parameters (e.g., AD or RD) in the included studies.…”

Neurite Orientation Dispersion and Density Imaging in Psychiatric Disorders: A Systematic Literature Review and a Technical Note

“…, 2020 ( 44 ) Psychogenic nonepileptic seizures NR NR 37/34 a CG a : 39.7 ± 10.9 Pt: 36.7 ± 11.8 CG a : 56.8 Pt: 29.4 3 47, 46 directions b = 1500, 3000 ODI, NDI, FWF VBM WM ↓NDI in the UF, corticospinal tract, and cingulum pathways ↓FWF in the corticospinal tract ICVF in the corticospinal tract and posterior cingulum were negatively correlated with depression FWF in the corticospinal tract was negatively correlated with posttraumatic stress scores Andica et al. , 2021 ( 39 ) ASD Chronic NR 25/26 HC: 34.4 ± 9.0 Pt: 32.9 ± 9.2 HC: 68.0 Pt: 73.1 3 32 directions b = 1000, 2000 NDI, ODI, V iso TBSS, ROI WM ↓NDI in the right hemisphere and anterior left hemisphere ↑V iso in the posterior left hemisphere NDI in the ATR was negatively correlated with communication scores Matsuoka et al. , 2020 ( 38 ) ASD Chronic Mixed 29/28 HC: 27.3 ± 4.9 Pt: 28.9 ± 6.0 HC: 82.8 Pt: 85.7 3 30, 30 directions b = 1000, 2000 NDI, ODI VBM GM ↑ODI in the occipital gyrus ODI was positively correlated with low registration and a passive behavioral response Yasuno et al.…”

“…Three studies assessed NODDI indices in patients with autism spectrum disorder ( 37 , 38 , 39 ). One study investigated gray matter microstructure and found increased ODI in the left occipital gyrus.…”

Atlas-powered deep learning (ADL) -- application to diffusion weighted MRI

“…In this study, we focus on two biomarkers: 1) Fractional anisotropy (FA) from the diffusion tensor model, which is arguably the most widely used dMRI biomarker, and 2) Orientation dispersion (OD) from the NODDI model [39], which is a more complex model than diffusion tensor and which has been shown to be a more specific biomarker in some studies [4,29].…”