Computerized Analysis of Magnetic Resonance Images to Study Cerebral Anatomy in Developing Neonates

The study of cerebral anatomy in developing neonates is of great importance for the understanding of brain development during the early period of life. This dissertation therefore focuses on three challenges in the modelling of cerebral anatomy in neonates during brain development. The methods that have been developed all use Magnetic Resonance Images (MRI) as source data. To facilitate study of vascular development in the neonatal period, a set of image analysis algorithms are developed to automatically extract and model cerebral vessel trees. The whole process consists of cerebral vessel tracking from automatically placed seed points, vessel tree generation, and vasculature registration and matching. These algorithms have been tested on clinical Time-of- Flight (TOF) MR angiographic datasets. To facilitate study of the neonatal cortex a complete cerebral cortex segmentation and reconstruction pipeline has been developed. Segmentation of the neonatal cortex is not effectively done by existing algorithms designed for the adult brain because the contrast between grey and white matter is reversed. This causes pixels containing tissue mixtures to be incorrectly labelled by conventional methods. The neonatal cortical segmentation method that has been developed is based on a novel expectation-maximization (EM) method with explicit correction for mislabelled partial volume voxels. Based on the resulting cortical segmentation, an implicit surface evolution technique is adopted for the reconstruction of the cortex in neonates. The performance of the method is investigated by performing a detailed landmark study. To facilitate study of cortical development, a cortical surface registration algorithm for aligning the cortical surface is developed. The method first inflates extracted cortical surfaces and then performs a non-rigid surface registration using free-form deformations (FFDs) to remove residual alignment. Validation experiments using data labelled by an expert observer demonstrate that the method can capture local changes and follow the growth of specific sulcus

Pattern classification using principal components of cortical thickness and its discriminative pattern in schizophrenia

We proposed pattern classification based on principal components of cortical thickness between schizophrenic patients and healthy controls, which was trained using a leave-one-out cross-validation. The cortical thickness was measured by calculating the Euclidean distance between linked vertices on the inner and outer cortical surfaces. Principal component analysis was applied to each lobe for practical computational issues and stability of principal components. And, discriminative patterns derived at every vertex in the original feature space with respect to support vector machine were analyzed with definitive findings of brain abnormalities in schizophrenia for establishing practical confidence. It was simulated with 50 randomly selected validation set for the generalization and the average accuracy of classification was reported. This study showed that some principal components might be more useful than others for classification, but not necessarily matching the ordering of the variance amounts they explained. In particular, 40-70 principal components rearranged by a simple two-sample t-test which ranked the effectiveness of features were used for the best mean accuracy of simulated classification (frontal: (left(%)|right(%))=91.07|88.80, parietal: 91.40|91.53, temporal: 93.60|91.47, occipital: 88.80|91.60). And, discriminative power appeared more spatially diffused bilaterally in the several regions, especially precentral, postcentral, superior frontal and temporal, cingulate and parahippocampal gyri. Since our results of discriminative patterns derived from classifier were consistent with a previous morphological analysis of schizophrenia, it can be said that the cortical thickness is a reliable feature for pattern classification and the potential benefits of such diagnostic tools are enhanced by our finding

Statistical Shape and Intensity Modeling of the Shoulder

Anatomical variability in the shoulder is inherently present and can influence healthy and pathologic biomechanics and ultimately clinical decision-making. Characterizing variation in bony morphology and material properties in the population can support treatment and specifically the design, via shape and sizing, of shoulder implants. Total Shoulder Arthroplasty (TSA) is the treatment of choice for glenohumeral osteoarthritis as well as bone fracture. Complications and poor outcomes in TSA are generally influenced by the inability of the implant to replicate the natural joint biomechanics and by the bone quality around the fixation features. For this reason, knowledge of bony morphology and mechanical properties can support optimal implant design and sizing, and thus improve TSA results. Statistical shape and intensity modeling is a powerful tool to represent the shape and mechanical properties variation in a training set. Accordingly, the objectives of this thesis were: 1) to develop a statistical shape model (SSM) of the proximal humeral cortical and cancellous bone; 2) to develop an SSM and a statistical intensity model (SIM) of the scapular bone. A training set of 85 humeri and 53 scapulae were reconstructed from CT scans and registered to common templates. Principal Component Analysis (PCA) was applied to the registered geometries to quantify morphological and bone properties variation in the population. For both the humerus and the scapula SSM, the first mode of variation accounted for most of the variation and described scaling. Subsequent modes described changes in the scapular plate, acromion process and scapular notch for the scapula, and in the neck angle, head inclination, greater and lesser tubercles for the humerus. Variation in cortical thickness of the humeral diaphysis was largely independent of size and statistically significant differences with ethnicity were noted. Asian subjects showed higher humeral cortical thickness with respect to Caucasians, regardless of gender. The first mode of variation in the scapular SIM described scaling in material properties distribution, with higher bone density located centrally and anteriorly in the glenoid region. The bone property maps developed for the scapular training set realistically captured inter-subject variability and they represent a valuable tool to assess fixation features and screw location and trajectories for TSA glenoid component. The SSMs and SIM developed in this thesis represent a useful infrastructure to support population-based evaluations and assess possible anatomical differences with gender and ethnicity, SSM and SIM can also provide anatomical relationship in support of implant design and sizing

Intact Bilateral Resting-State Networks in the Absence of the Corpus Callosum

Temporal correlations between different brain regions in the resting-state BOLD signal are thought to reflect intrinsic functional brain connectivity (Biswal et al., 1995; Greicius et al., 2003; Fox et al., 2007). The functional networks identified are typically bilaterally distributed across the cerebral hemispheres, show similarity to known white matter connections (Greicius et al., 2009), and are seen even in anesthetized monkeys (Vincent et al., 2007). Yet it remains unclear how they arise. Here we tested two distinct possibilities: (1) functional networks arise largely from structural connectivity constraints, and generally require direct interactions between functionally coupled regions mediated by white-matter tracts; and (2) functional networks emerge flexibly with the development of normal cognition and behavior and can be realized in multiple structural architectures. We conducted resting-state fMRI in eight adult humans with complete agenesis of the corpus callosum (AgCC) and normal intelligence, and compared their data to those from eight healthy matched controls. We performed three main analyses: anatomical region-of-interest-based correlations to test homotopic functional connectivity, independent component analysis (ICA) to reveal functional networks with a data-driven approach, and ICA-based interhemispheric correlation analysis. Both groups showed equivalently strong homotopic BOLD correlation. Surprisingly, almost all of the group-level independent components identified in controls were observed in AgCC and were predominantly bilaterally symmetric. The results argue that a normal complement of resting-state networks and intact functional coupling between the hemispheres can emerge in the absence of the corpus callosum, favoring the second over the first possibility listed above

Persistent topology for natural data analysis - A survey

Natural data offer a hard challenge to data analysis. One set of tools is being developed by several teams to face this difficult task: Persistent topology. After a brief introduction to this theory, some applications to the analysis and classification of cells, lesions, music pieces, gait, oil and gas reservoirs, cyclones, galaxies, bones, brain connections, languages, handwritten and gestured letters are shown

The potential of Antheraea pernyi silk for spinal cord repair

This work was supported by the Institute of Medical Sciences of the University of Aberdeen, Scottish Rugby Union and RS McDonald Charitable Trust. We are grateful to Mr Nicholas Hawkins from Oxford University and Ms Annette Raffan from the University of Aberdeen for assistance with tensile testing. We thank Ms Michelle Gniβ for her help with the microglial response experiments. We also thank Mr Gianluca Limodio for assisting with the MATLAB script for automation of tensile testing’s data analysis.Peer reviewedPublisher PD

Multiscale neural gradients reflect transdiagnostic effects of major psychiatric conditions on cortical morphology

It is increasingly recognized that multiple psychiatric conditions are underpinned by shared neural pathways, affecting similar brain systems. Here, we carried out a multiscale neural contextualization of shared alterations of cortical morphology across six major psychiatric conditions (autism spectrum disorder, attention deficit/hyperactivity disorder, major depression disorder, obsessive-compulsive disorder, bipolar disorder, and schizophrenia). Our framework cross-referenced shared morphological anomalies with respect to cortical myeloarchitecture and cytoarchitecture, as well as connectome and neurotransmitter organization. Pooling disease-related effects on MRI-based cortical thickness measures across six ENIGMA working groups, including a total of 28,546 participants (12,876 patients and 15,670 controls), we identified a cortex-wide dimension of morphological changes that described a sensory-fugal pattern, with paralimbic regions showing the most consistent alterations across conditions. The shared disease dimension was closely related to cortical gradients of microstructure as well as neurotransmitter axes, specifically cortex-wide variations in serotonin and dopamine. Multiple sensitivity analyses confirmed robustness with respect to slight variations in analytical choices. Our findings embed shared effects of common psychiatric conditions on brain structure in multiple scales of brain organization, and may provide insights into neural mechanisms of transdiagnostic vulnerability

Factors associated with clinical progression to severe COVID-19 in people with cystic fibrosis: A global observational study

BACKGROUND This international study aimed to characterise the impact of acute SARS-CoV-2 infection in people with cystic fibrosis and investigate factors associated with severe outcomes. Methods Data from 22 countries prior to 13$^{th}$ December 2020 and the introduction of vaccines were included. It was de-identified and included patient demographics, clinical characteristics, treatments, outcomes and sequalae following SARS-CoV-2 infection. Multivariable logistic regression was used to investigate factors associated with clinical progression to severe COVID-19, using the primary outcome of hospitalisation with supplemental oxygen. RESULTS SARS-CoV-2 was reported in 1555 people with CF, 1452 were included in the analysis. One third were aged 70%: a 17-fold increase in odds. Worse outcomes were independently associated with older age, non-white race, underweight body mass index, and CF-related diabetes. Prescription of highly effective CFTR modulator therapies was associated with a significantly reduced odds of being hospitalised with oxygen (AOR 0.43 95%CI 0.31-0.60 p<0.001). Transplanted patients were hospitalised with supplemental oxygen therapy (21.9%) more often than non-transplanted (8.8%) and was independently associated with the primary outcome (Adjusted OR 2.45 95%CI 1.27-4.71 p=0.007). CONCLUSIONS This is the first study to show that there is a protective effect from the use of CFTR modulator therapy and that people with CF from an ethnic minority are at more risk of severe infection with SARS-CoV-2

Evaluating osteological ageing from digital data

YesAge at death estimation of human skeletal remains is one of the key issues in constructing a biological profile both in forensic and archaeological contexts. The traditional adult osteological methods evaluate macroscopically the morphological changes that occur with increasing age of specific skeletal indicators, such as the cranial sutures, the pubic bone, the auricular surface of the ilium and the sternal end of the ribs. Technologies such as CT and laser scanning are becoming more widely used in anthropology, and several new methods have been developed. This review focuses on how the osteological age-related changes have been evaluated in digital data. Firstly, the 3D virtual copies of the bones have been used to mimic the appearance of the dry bones and the application of the traditional methods. Secondly, the information directly extrapolated from CT scan has been used to qualitatively or quantitatively assess the changes of the trabecular bones, the thickness of the cortical bones, and to perform morphometric analyses. Lastly, the most innovative approach has been the mathematical quantification of the changes of the pelvic joints, calculating the complexity of the surface. The importance of new updated reference datasets, created thanks to the use of CT scanning in forensic settings, is also discussed.CV was supported from the Danish Council for Independent Research (DFF – 4005-00102B – FTP

Anomalous morphology in left hemisphere motor and premotor cortex of children who stutter

Stuttering is a neurodevelopmental disorder that affects the smooth flow of speech production. Stuttering onset occurs during a dynamic period of development when children first start learning to formulate sentences. Although most children grow out of stuttering naturally, ∼1% of all children develop persistent stuttering that can lead to significant psychosocial consequences throughout one’s life. To date, few studies have examined neural bases of stuttering in children who stutter, and even fewer have examined the basis for natural recovery versus persistence of stuttering. Here we report the first study to conduct surface-based analysis of the brain morphometric measures in children who stutter. We used FreeSurfer to extract cortical size and shape measures from structural MRI scans collected from the initial year of a longitudinal study involving 70 children (36 stuttering, 34 controls) in the 3–10-year range. The stuttering group was further divided into two groups: persistent and recovered, based on their later longitudinal visits that allowed determination of their eventual clinical outcome. A region of interest analysis that focused on the left hemisphere speech network and a whole-brain exploratory analysis were conducted to examine group differences and group × age interaction effects. We found that the persistent group could be differentiated from the control and recovered groups by reduced cortical thickness in left motor and lateral premotor cortical regions. The recovered group showed an age-related decrease in local gyrification in the left medial premotor cortex (supplementary motor area and and pre-supplementary motor area). These results provide strong evidence of a primary deficit in the left hemisphere speech network, specifically involving lateral premotor cortex and primary motor cortex, in persistent developmental stuttering. Results further point to a possible compensatory mechanism involving left medial premotor cortex in those who recover from childhood stuttering.This study was supported by Award Numbers R01DC011277 (SC) and R01DC007683 (FG) from the National Institute on Deafness and other Communication Disorders (NIDCD). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIDCD or the National Institutes of Health. (R01DC011277 - National Institute on Deafness and other Communication Disorders (NIDCD); R01DC007683 - National Institute on Deafness and other Communication Disorders (NIDCD))Accepted manuscrip