Association of Glymphatic and White Matter Impairment With the Postoperative Outcome of Pediatric Hydrocephalus.

BACKGROUND AND OBJECTIVES: Assessment of postoperative outcomes on pediatric hydrocephalus is critical for adjusting treatment strategies. The aim of this work was to investigate the ability of MRI metrics to predict postoperative outcomes. METHODS: A total of 55 children with hydrocephalus who underwent MRI and ventriculoperitoneal shunt surgery were prospectively enrolled. MRI was also performed at 6 months postoperatively in 33 of the 55 children. A total of 92 controls matched for age and sex were enrolled and divided into preoperative and postoperative control groups. We calculated the diffusion tensor imaging along the perivascular space (DTI-ALPS) index, Evans index, and diffusion tensor imaging metrics. The ability of various metrics to predict postoperative outcomes was assessed using receiver operating characteristic curve analysis. RESULTS: The DTI-ALPS index was significantly lower in patients with hydrocephalus than in controls. The abnormal DTI-ALPS index trended toward the normal range after surgery. Patients with lower preoperative DTI-ALPS index, lower fractional anisotropy (FA), and higher radial diffusivity in association fibers had less favorable short-term outcomes. Patients with worse long-term outcomes had lower postoperative DTI-ALPS index, higher postoperative Evans index, and lower FA and higher radial diffusivity in association fibers. Predictive performance was better when the DTI-ALPS index and FA in association fibers were used in combination than when either of these metrics was used alone. CONCLUSION: The DTI-ALPS index and FA in association fibers provided complementary information for prognostic assessment after the ventriculoperitoneal shunt surgery on pediatric hydrocephalus. A combination of DTI-ALPS index and FA would improve our ability to predict postoperative outcomes in these patients.

Abnormal Degree Centrality in Children with Low-Function Autism Spectrum Disorders: A Sleeping-State Functional Magnetic Resonance Imaging Study.

Purpose: This study used the graph-theory approach, degree centrality (DC) to analyze whole-brain functional networks at the voxel level in children with ASD, and investigated whether DC changes were correlated with any clinical variables in ASD children. Methods: The current study included 86 children with ASD and 54 matched healthy subjects Aged 2-5.5 years. Next, chloral hydrate induced sleeping-state functional magnetic resonance imaging (ss-fMRI) datasets were acquired from these ASD and healthy subjects. For a given voxel, the DC was calculated by calculating the number of functional connections with significantly positive correlations at the individual level. Group differences were tested using two-sample t-tests (p < 0.01, AlphaSim corrected). Finally, relationships between abnormal DCs and clinical variables were investigated via Pearson's correlation analysis. Results: Children with ASD exhibited low DC values in the right middle frontal gyrus (MFG) (p < 0.01, AlphaSim corrected). Furthermore, significantly negative correlations were established between the decreased average DC values within the right MFG in ASD children and the total ABC scores, as well as with two ABC subscales measuring highly relevant impairments in ASD (ie, stereotypes and object-use behaviors and difficulties in language). Conclusion: Taken together, the results of our ss-fMRI study suggest that abnormal DC may represent an important contribution to elucidation of the neuropathophysiological mechanisms of preschoolers with ASD.

Altered Functional Connectivity in Children With Low-Function Autism Spectrum Disorders.

Neuroimaging studies have shown that autism spectrum disorders (ASDs) may be associated with abnormalities in brain structures and functions at rest as well as during cognitive tasks. However, it remains unclear if functional connectivity (FC) of all brain neural networks is also changed in these subjects. In this study, we acquired functional magnetic resonance imaging scans from 93 children with ASD and 79 matched healthy subjects. Group independent component analysis was executed for all of the participants to estimate FC. One-sample t-tests were then performed to obtain the networks for each group. Group differences in the different brain networks were tested using two-sample t-tests. Finally, relationships between abnormal FC and clinical variables were investigated with Pearson's correlation analysis. The results from one-sample t-tests revealed nine networks with similar spatial patterns in these two groups. When compared with the controls, children with ASD showed increased connectivity in the right dorsolateral superior frontal gyrus and left middle frontal gyrus (MFG) within the occipital pole network. Children with ASD also showed decreased connectivity in the left gyrus rectus, left middle occipital gyrus, right angular gyrus, right MFG and right inferior frontal gyrus (IFG), orbital part within the lateral visual network (LVN), the left IFG, right precuneus, and right angular gyrus within the left frontoparietal (cognition) network. Furthermore, the mean FC values within the LVN showed significant positive correlations with total score of the Childhood Autism Rating Scale. Our findings indicate that abnormal FC extensively exists within some networks in children with ASD. This abnormal FC may constitute a biomarker of ASD. Our results are an important contribution to the study of neuropathophysiological mechanisms in children with ASD.