Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.733426
Title: Novel applications of surface based morphometry and pattern classification in autism spectrum disorders
Author: Andrews, Derek Sayre
ISNI:       0000 0004 6498 1696
Awarding Body: King's College London
Current Institution: King's College London (University of London)
Date of Award: 2018
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Abstract:
Autism spectrum disorder (ASD) is a lifelong, behaviorally defined neurodevelopmental condition that is characterized by deficits in social communication, interaction, and repetitive behaviors. These behavioral symptoms are associated with atypical brain structure, function, and connectivity. The studies that comprise this thesis employed structural magnetic resonance imaging (MRI) to address aims in three areas of ASD research. First, we examined a novel neuroimaging feature based on signal intensity contrast between grey and white matter to quantify atypical microstructure at the greywhite matter boundary in ASD. We found reduced tissue contrast at the grey-white matter boundary among adults with ASD when compared typically developing (TD) controls. This result indicates that measures of tissue contrast may serve as an in vivo proxy measure of atypical cortical microstructure that has previously been reported in histological studies. Second, we trained multivariate pattern recognition models to identify individuals with ASD based on measures of cortical morphometry, and examined the predictive value of these models in a representative clinical sample. We demonstrated that these models have modest ability to distinguish cases from controls in the research setting. Only one model that was based on measures of grey-white matter tissue contrast identified individuals with and without ASD diagnoses at high overall accuracy (81%) in the clinical setting. However, this model did not provide significant accuracies above chance in the research setting, and therefore these results should be considered as preliminary and suggestive only. Third, we established normative models of phenotypic diversity in brain structure associated with biological sex in a sample of TD males and females which was subsequently applied to males and females with ASD. Across different morphometric features, females with ASD displayed a significant shift towards a more male-typical presentation of the brain. Sample probabilities for ASD also increased with predicted probabilities for male-typical brain phenotypes across both sexes. These studies highlight advances in the field of structural neuroimaging research in areas of feature development, clinical translation, and efforts to understand the modulating role of biological sex on the prevalence of ASD. Taken together, the work presented within this thesis thus constitutes an important step toward establishing translational imaging tools for ASD that may one day be applied in the clinical setting.
Supervisor: Daly, Eileen M. ; Ecker, Christine ; Marquand, Andre Frank Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.733426  DOI: Not available
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