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Diffusion Tensor Imaging Study Of Children With Retrogressive Autism Spectrum Disorder

Posted on:2020-01-24Degree:DoctorType:Dissertation
Country:ChinaCandidate:H FangFull Text:PDF
GTID:1364330614959082Subject:Mental illness and mental hygiene
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PART ? Tract-based spatial statistics of children with autism spectrum disorder with regressionPURPOSE: The objective of this study was to use tract-based spatial statistics(TBSS)to compare the differences in white matter fiber structure in children with autism spectrum disorder(ASD)and developmental delay(DD),in children with autism spectrum disorders with(ASD-R)and without(ASD-NR)regressive.METHODS: In this study,97 ASD children(male/female: 81/16;age: 37.02±11.85 months)and 40 DD(male/female: 29/11;age: 39.98±12.32 months)were recruited.There were 29 with regression(male/female: 21/8;age: 40.24±12.78 months)and 68 without regression(male/female: 60/8;age: 35.65±11.25 months)in the ASD group.Based on the tract-based spatial statistics analysis of fiber bundle tracing,the fractional anisotropy(FA)value of each subject was analyzed,and the merged FA skeleton of the whole group was obtained.Randomize statistics were used to compare the differences of FA skeleton between the two groups.Statistical analyses were performed using IBM SPSS(version 23).RESULTS: 1.There were significant differences between the two groups: right cerebral peduncle,posterior limb of internal capsule,inferior fronto-occipital fasciculus and right uncinate fasciculus,left cerebral peduncle,cingulum(cingulate gyrus),superior longitudinal fasciculu and inferior fronto-occipital fasciculus(t=2.300,p=0.023;t=2.242,p=0.027;t=2.724,p=0.007;t=1.979,p=0.050;t=2.136,p=0.034;t=2.155,p=0.033;t=1.987,p=0.049;t=2.046,p=0.043),the FA values increased in ASD group than in DD group.2.Covariate analysis was performed on the FA values of the two groups of children with childhood autism rating scale(CARS)total scores.There were significant differences between the two groups: right sagittal stratum,left sagittal stratum,posterior thalamic radiation and anterior corona radiata(F=4.035,p=0.021;F=4.741,p=0.011;F=3.092,p=0.050;F=3.492,p=0.034),and FA values increased in ASD-R group than in ASD-NR group.3.There were significant negative correlations between the total CARS scores and the FA values of right sagittal stratum,external capsule and superior longitudinal fasciculus,left sagittal stratum,posterior thalamic radiation and fornix(cres)/Stria terminalis(r=-0.522,p=0.004;r=-0.391,p=0.036;r=-0.467,p=0.011;r=-0.492,p=0.007;r=-0.419,p=0.024;r=-0.377,p=0.044).CONCLUSIONS: The FA of the bilateral cerebral peduncle,inferior frontooccipital fasciculus,left cingulum(cingulate gyrus),left superior longitudinal fasciculus,right posterior limb of internal capsule,and right uncinate fasciculus in children with ASD were higher than children with developmental delay.The FA of the ASD-R group increased in the bilateral sagittal stratum,left anterior corona radiata and left posterior thalamic radiation than the ASD-NR group.And the FA of bilateral sagittal stratum and left posterior thalamic radiation was related to the severity of autism symptoms in ASD-R children.PART? Structural networks in children with autism spectrum disorder with regressionPURPOSE: To explore the network topological properties in autism spectrum disorder(ASD)children and developmental delay(DD)children.To analysis the network topological properties in autism spectrum disorder children with(ASD-R)and without(ASD-NR)regression.METHODS: In this study,97 ASD children(including 29 with regression and 68 without regression)and 40 developmental delay.Structural networks were constructed using diffusion tensor imaging(DTI)and T1-weighted imaging on a 3.0T magnetic resonance system.We utilized graph theory to characterize the white matter structure networks.Statistical analyses were performed using IBM SPSS(version 23).RESULTS: 1.The global topological properties global efficiency(Eg),local efficiency(Eloc),clustering coefficient(Cp)increased(t=3.599,p=0.000;t=2.233,p=0.027;t=2.099,p=.038)increased,and the characteristic path length(Lp)decreased in the ASD group.Both groups presented small-world organization(? > 1).2.There were 10 common hubs based on regional degree and regional efficiency(bilateral insula,hippocampus,caudate nucleus and putamen,left precuneus and right superior frontal gyrus-dorsolateral)in both ASD and DD groups.The hubness of the right precuneus were enhanced(by both regional degree and efficiency)in ASD children.3.We identified 12 in 90(by regional degree)and 33 in 90(by regional efficiency)nodes showing significant difference(all p(27)0.05)by comparing the nodal properties respectively between ASD and DD,and all of them were higher in ASD group.4.There were 10 common hubs based on regional degree and regional efficiency(bilateral insula,hippocampus,caudate nucleus and putamen,left precuneus and right superior frontal gyrus-dorsolateral)in both ASD-R and ASD-NR groups.The hubness of the left superior frontal gyrus-dorsolateral,left middle occipital gyrus and right precuneus were enhanced(by regional degree)and the hubness of the right thalamus was reduced(by regional efficiency)in the ASD-R relative to the ASD-NR.Pearson correlation analysis was performed on the regional degree and regional efficiency of hub regions with different hubness and the Childhood autism rating scale(CARS).There were significant negative correlations between the total CARS scores and the regional degree and regional efficiency(r=-0.535,p=0.049;r=-0.557,p=0.038).5.Both global and regional network property showed no significant difference between the two groups.CONCLUSIONS: The global efficiency of the children's brain network in the ASD group increased,indicating that children with ASD have higher connectivity.The hubness of the right precuneus was enhanced in ASD group.The ASD-R children were different from the ASD-NR children in the distribution of hub regions,although there were no global network property differences between them.In ASD-R children,the right precuneus(PCUN.R)might play an important role and relate to autism symptom severity.
Keywords/Search Tags:Autism spectrum disorder, Regression, Diffusion tensor imaging, Tract-based spatial statistics, White matter structural networks, Graph theory
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