Age-associated sex and asymmetry differentiation in hemispheric and lobar cortical ribbon complexity across adulthood : A UK BioBank Imaging Study

Acknowledgements This research has been conducted using the UK Biobank resource. This work was supported by the Aberdeen Biomedical Imaging Centre with financial support from the Roland Sutton Academic Trust (RSAT-0067/R/19). The authors would like to thank the participants of the UK Biobank imaging study and our colleague Dr Naif Majrashi for performing image pre-processing using FreesurferPeer reviewedPublisher PD

Structural brain complexity and cognitive decline in late life : A longitudinal study in the Aberdeen 1936 Birth Cohort

Copyright © 2014 Elsevier Inc. All rights reserved.Peer reviewedPostprin

Doctor of Philosophy

dissertationNeurodegenerative diseases are an increasing health care problem in the United States. Quantitative neuroimaging provides a noninvasive method to illuminate individual variations in brain structure to better understand and diagnose these disorders. The overall objective of this research is to develop novel clinical tools that summarize and quantify changes in brain shape to not only help better understand age-appropriate changes but also, in the future, to dissociate structural changes associated with aging from those caused by dementing neurodegenerative disorders. Because the tools we will develop can be applied for individual assessment, achieving our goals could have a significant clinical impact. An accurate, practical objective summary measure of the brain pathology would augment current subjective visual interpretation of structural magnetic resonance images. Fractal dimension is a novel approach to image analysis that provides a quantitative measure of shape complexity describing the multiscale folding of the human cerebral cortex. Cerebral cortical folding reflects the complex underlying architectural features that evolve during brain development and degeneration including neuronal density, synaptic proliferation and loss, and gliosis. Building upon existing technology, we have developed innovative tools to compute global and local (voxel-wise and regional) cerebral cortical fractal dimensions and voxel-wise cortico-fractal surfaces from high-contrast MR images. Our previous research has shown that fractal dimension correlates with cognitive function and changes during the course of normal aging. We will now apply unbiased diffeomorphic atlasing methodology to dramatically improve the alignment of complex cortical surfaces. Our novel methods will create more accurate, detailed geometrically averaged images to take into account the intragroup differences and make statistical inferences about spatiotemporal changes in shape of the cerebral cortex across the adult human lifespan

Employing Symmetry Features for Automatic Misalignment Correction in Neuroimages

A novel method to automatically compute the symmetry plane and to correct the 3D orientation of neuro-images is presented. In acquisition of neuroimaging scans, the lack of perfect alignment of a patient's head makes it challenging to evaluate brain images. By deploying a shape-based criterion, the symmetry plane is defined as a plane that best matches external surface points on one side of the head, with their counterparts on the other side. In our method, the head volume is represented as a re-parameterized surface point cloud, where each location is parameterized by its elevation (latitude), azimuth (longitude), and radius. The search for the best matching surfaces is implemented in a multi-resolution paradigm, and the computation time is significantly decreased. The algorithm was quantitatively evaluated using in both simulated data and in real T1, T2, Flair magnetic resonance patient images. This algorithm is found to be fast (< 10s per MR volume), robust and accurate (< .6 degree of Mean Angular Error), invariant to the acquisition noise, slice thickness, bias field, and pathological asymmetries

Genetic influences on gyrification of the cerebral cortex in schizophrenia: a twin study

Veränderungen in der kortikalen Gyrifizierung, d.h. in der Formation der Windungen und Furchen im Gehirn, wurden bei Patienten mit Schizophrenie wiederholt berichtet. In der vorliegenden Arbeit wurde der Parameter der Absoluten Mittleren Kurvatur (engl. „Absolute Mean Curvature“, AMC) herangezogen, um den regionalen kortikalen Gyrifizierungsindex (GI) zu quantifizieren. In einer ersten Studie konnte hierbei festgestellt werden, dass diese Methode zur Untersuchung der Gyrifizierung die kombinierte Auswertung von Magnetresonanztomographie (MRT) Daten unterschiedlicher Untersuchungszentren erlaubt. Hierfür wurden strukturelle MRT Messungen an (a) einem gesunden Probanden, der insgesamt 12 mal in MRT Scannern zweier unterschiedlicher Untersuchungszentren und (b) sechs gesunden Probanden, die in vier MRT Scannern unterschiedlicher Untersuchungszentren gemessen wurden, durchgeführt. Im Anschluss wurde die kortikale Oberfläche jeder Hemisphäre sowie die Absolute Mittlere Kurvatur für jeden Vertex im Gehirn berechnet. Die Koeffizienten der Intra-Klassen-Korrelation (engl. ”intra-class correlation”, ICC) erwiesen sich sowohl für die Daten desselben Probanden als auch die Daten der verschiedenen Untersuchungszentren als hoch. In einer zweiten Studie wurden sodann strukturelle MRT Daten von 104 monozygoten Zwillingen, d.h. 27 monozygoten gesunden Zwillingspaaren und 25 monozygoten, im Hinblick auf Schizophrenie diskordanten Zwillingspaaren aus drei verschiedenen Untersuchungszentren kombiniert. Hier ergaben sich höhere Korrelationen in der Gyrifizierung innerhalb der diskordanten Zwillingspaare im Vergleich zu gesunden Zwillingpaaren. Dieser Befund deutet darauf hin, dass monozygote Zwillinge mit einer Diskordanz für die Erkrankung diesbezüglich eine größere Ähnlichkeit aufweisen und eine genetische Veranlagung zur schizophrenen Erkrankung möglicherweise eine relevante Rolle im Rahmen der Gyrifizierung spielen könnte. Zudem ließ sich eine erhöhte linksseitige Gyrifizierung im Bereich des frontopolaren Kortex sowie in mittleren temporalen, parahippokampalen und fusiformen Arealen sowohl bei erkrankten als auch nicht affizierten Co-Zwillingen im Vergleich zu den gesunden Zwillingen feststellen

Statistical shape analysis of neuroanatomical structures based on spherical wavelet transformation

Thesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, 2008.Includes bibliographical references.Evidence suggests that morphological changes of neuroanatomical structures may reflect abnormalities in neurodevelopment, or relate to a variety of disorders, such as schizophrenia and Alzheimer's disease (AD). Advances in high-resolution Magnetic Resonance Imaging (MRI) techniques allow us to study these alterations of brain structures in vivo. Previous work in studying the shape variations of brain structures has provided additional localized information compared with traditional volume-based study. However, challenges remain in finding an accurate shape presentation and conducting shape analysis with sound statistical principles. In this work, we develop methods for automatically extracting localized and multi-scale shape features and conducting statistical shape analysis of neuroanatomical structures obtained from MR images. We first develop a procedure to extract multi-scale shape features of brain structures using biorthogonal spherical wavelets. Using this wavelet-based shape representation, we build multi-scale shape models and study the localized cortical folding variations in a normal population using Principal Component Analysis (PCA). We then build a shape-based classification framework for detecting pathological changes of cortical surfaces using advanced classification methods, such as predictive Automatic Relevance Determination (pred-ARD), and demonstrate promising results in patient/control group comparison studies. Thirdly, we develop a nonlinear temporal model for studying the temporal order and regional difference of cortical folding development based on this shape representation. Furthermore, we develop a shape-guided segmentation method to improve the segmentation of sub-cortical structures, such as hippocampus, by using shape constraints obtained in the wavelet domain.(cont.) Finally, we improve upon the proposed wavelet-based shape representation by adopting a newly developed over-complete spherical wavelet transformation and demonstrate its utility in improving the accuracy and stability of shape representations. By using these shape representations and statistical analysis methods, we have demonstrated promising results in localizing shape changes of neuroanatomical structures related to aging, neurological diseases, and neurodevelopment at multiple spatial scales. Identification of these shape changes could potentially lead to more accurate diagnoses and improved understanding of neurodevelopment and neurological diseases.by Peng Yu.Ph.D

Novel methodologies and technologies for the multiscale and multimodal study of Autism Spectrum Disorders (ASDs)

The aim of this PhD thesis was the development of novel bioengineering tools and methodologies that provide a support in the study of ASDs. ASDs are very heterogeneous disturbs and their abnormalities are present both at local and global level. For this reason a multimodal and multiscale approach was followed. The analysis of microstructure was executed on single Purkinje neurons in culture and on organotypic slices extracted from cerebella of GFP wild-type mice and animal models of ASDs. A methodology for the non-invasive imaging of neurons during their growth was set up and a software called NEMO (NEuron MOrphological analysis tool) for the automatic analysis of morphology and connectivity was developed. Microstructure properties can be inferred also in vivo through the quite recent technique of Diffusion Tensor Imaging (DTI). DTI studies in ASDs are based on the hypothesis that the disorder involves aberrant brain connectivity and disruption of white matter tracts between regions implicated in social functioning. In this study DTI was used to investigate structural abnormalities in the white matter structure of young children with ASDs. Moreover the neurostructural bases of echolalia were investigated. The functionality of the brain was analyzed through Functional Magnetic Resonance Imaging (fMRI) using a novel task based on face processing of human, android and robotic faces. A case-control study was performed in order to study how the face processing network is altered in ASDs and how robots are differently processed in ASDs and control groups. Measurements characterizing physiology and behavior of ASD children were also collected using an innovative platform called FACE-T (FACE-Therapy). FACE-T consists of a specially equipped room in which the child, wearing unobtrusive devices for recording physiological and behavioral data as well as gaze information, can interact with an android (FACE, Facial Automaton for Conveying Emotions) and a therapist. The focus was on ECG, as from the analysis of power spectrum density of ECG it is possible to extract features related to the autonomic nervous system that is correlated with brain functionality. These studies give new insights in the study of ASDs exploring aspects not yet addressed. Moreover the methodologies and tools developed could help in the objective characterization of ASD subjects and in the definition of a personalized therapeutic protocol for each child

Analysis of the hemispheric asymmetry using fractal dimension of a skeletonized cerebral surface

We investigated hemispheric asymmetry using the fractal dimension (FD) of the skeletonized cerebral surface. Sixty-two T1-weighted magnetic resonance imaging volumes from normal Korean adults were used. The skeletonization of binary volume data, which corresponded to the union of the gray matter and cerebrospinal flow classified by fuzzy clustering, was performed slice by slice in the sagittal direction, and then skeletonized slices were integrated into the three-dimensional (3-D) hemisphere. Finally, the FD of the 3-D skeletonized cerebral surface was calculated using the box-counting method. We measured the FD of the skeletonized cerebral surface and the volumes of intracranial gray matter and white matter for the whole hemispheres and obtained the hemispheric asymmetries of each measurement. The FD, the gray matter, and the white matter volumes for the whole hemispheres decreased in the old group. The asymmetry of the FD revealed a significant right-greater-than-left asymmetry showed rightward, but did not change according to age and gender. None of the intracranial gray matter or white matter volumes showed any significant asymmetric changes. It could be said that the FD of the skeletonized cerebral surface is a novel measure of cerebral asymmetryrestrictio