A new class of polymer stabilized gadolinium trifluoride nanoparticles (NPs) have been developed as contrast agents for magnetic resonance imaging (MRI) and computed tomography (CT), with potential long term goals in targeted imaging and anti-cancer therapy. The NPs are comprised of a 90/10 mixture of GdF3/EuF3 and are coated with linear polyacrylic acid (PAA) chains consisting of 25 repeating units. The resulting aggregates are stable in serum and possess unprecedented mass relaxivities [i.e. ~100-200 s-1(mg/mL)-1]. Electron microscopy images reveal various NP morphologies which depend on the exact synthesis protocol. These include highly cross-linked oblong clusters with 30-70 nm cross sections, extensively cross-linked aggregates with 100-300 nm cross sections, and distinct polymer stabilized nanocrystals with 50 nm diameters. Their application as contrast agents in T1-weighted MRI studies, CT imaging at various X-ray energies, and preliminary rat brain perfusion studies was also tested. NP contrast enhancement was compared to Gd-DPTA (Magnevist®) and iopramide (Ultravist 300®) to demonstrate their high contrasting properties and potential as multimodal contrast agents.

This thesis addresses the challenge of prognosis, in terms of survival prediction, for patients with Glioblastoma Multiforme brain tumors. Glioblastoma is the most malignant brain tumor, which has a median survival time of no more than a year. Accurate assessment of prognostic factors is critical in deciding amongst different treatment options and in designing stratified clinical trials. This thesis is motivated by two observations. Firstly, clinicians often refer to properties of glioblastoma tumors based on magnetic resonance images when assessing prognosis. However, clinical data, along with histological and most recently, molecular and gene expression data, have been more widely and systematically studied and used in prognosis assessment than image based information. Secondly, patient survival times are often used along with clinical data to conduct population studies on brain tumor patients. Recursive Partitioning Analysis is typically used in these population studies. However, researchers validate and assess the predictive power of these models by measuring the statistical association between survival groups and survival times. In this thesis, we propose a learning approach that uses historical training data to produce a system that predicts patient survival. We introduce a classification model for predicting patient survival class, which uses texture based features extracted from magnetic resonance images as well as other patient properties. Our prognosis approach is novel as it is the first to use image-extracted textural characteristics of glioblastoma scans, in a classification model whose accuracy can be reliably validated by cross validation. We show that our approach is a promising new direction for prognosis in brain tumor patients.

Posttraumatic Stress Disorder (PTSD) is an anxiety disorder characterised by disturbed arousal, altered attention, and fear processing, and a reduction in the ability to perform cognitive tasks. Predominant neurophysiological models of PTSD have been focused on alterations in fear-related regulation, and few incorporate broader changes in generic executive control which may underlie many of the clinical symptoms and cognitive deficits in PTSD. This thesis aimed to investigate the neurophysiology of executive inhibitory control in PTSD using a Go/NoGo response inhibition task and converging functional imaging, structural imaging and electrophysiological measures. The first series of studies aimed to elucidate a normative neural network model of inhibitory control, and are consistent with normative control involving the activation of a mainly right-lateralised ventral lateral prefrontal cortex (VLPFC) network. Inhibitory control-related activation was found to be affected by levels of anxiety and changes in underlying neural structure; alterations in frontal cortical maturation and volume were related to additional activation of bilateral frontal cortical regions and the dorsal striatum, with anxiety increasing the demand on inhibitory control-related activation. In contrast to healthy participants, PTSD was associated with reduced inhibitory control as indexed by inhibitory behaviour, diminished activation of the right VLPFC, and slowed inhibition-related information processsing. PTSD participants relied on the greater activation of a left fronto-striatal inhibition network to support control, with the activation affected by levels of PTSD severity and comorbid anxiety. This left fronto-striatal activation in PTSD was related to underlying increases in fronto-striatal neural structure. Further, the ability to efficiently engage a left fronto-striatal network in PTSD during inhibitory control predicted better response to cognitive behavior for PTSD, consistent with the proposal that an improved ability to flexibly engage control systems may facilitate the resolution of PTSD symptoms. Taken together, this program of research extends current neurophysiological model of PTSD to show that PTSD involves a fundamental disturbance in the function and structure of key fronto-striatal response control networks associated with inhibitory control.

This thesis describes the development of a model of cerebral atrophic change associated with neurodegeneration. Neurodegenerative diseases such as Alzheimer's dementia present a significant health problem within the elderly population. Effective treatment relies upon the early detection of anatomic change, and the subsequent differential diagnosis of the disorder from other closely related neurological conditions. Importantly, this also includes the investigation of the relationship between atrophic change and cognitive function. In unison with the growth in neuroimaging technology, myriad methodologies have been developed since the first quantitative measures of atrophic change were deduced via manual tracing. Subsequently, automated region of interest analysis, segmentation, voxel-based morphometry and non-linear registration have all been used to investigate atrophy. These methods commonly report findings of ventricular enlargement and temporal lobe change in AD and other dementias. Whilst these results are accurate indicators of atrophy, they are largely non-specific in their diagnostic utility. In addition, the aforementioned methods have been employed to discern change observed at discrete intervals during a disease process. In order to gain a greater understanding of the temporal characteristics of changes that occur as a result of atrophy, a deformation modelling method that allows the continuous tracking of these changes in a cohort of AD patients and elderly control subjects is presented in this thesis. Deformation modelling involves non-linear registration of images to investigate the change that is apparent between two or more images. The non- linear registration results are analysed and presented via three metrics: local volume loss (atrophy); volume (CSF) increase; and translation (interpreted as representing collapse of cortical structures). Changes observed in the analyses in this thesis are consistent with results from neuro-anatomical studies of AD. Results using the more traditional methods of analysis are presented for comparative purposes.

Diffusion Tensor Magnetic Resonance Imaging (DTI) is a recently-developed technique that can image in vivo the white matter pathways of the central nervous system. This study used 12-direction diffusion-weighted MRI data from nine stroke patients acquired as part of a three-year stroke rehabilitation study coordinated by the Movement Neuroscience Laboratory at the University of Auckland. DTI was used to investigate corticospinal connectivity. From the FA maps, it is found that in those patients whose motor connectivity has been compromised by the stroke to the extent that no motor evoked potential (MEP) can be elicited from a selected affected muscle group, the asymmetry in mean FA values in the posterior limbs of the internal capsules (PLICs) is correlated with functional recovery as measured by the Fugl-Meyer clinical score. Using probabilistic tractography in the contralesional hemisphere produced CST location and somatotopy results that were consistent with those of previous studies. However, in the ipsilesional hemisphere, connectivity results were highly variable. A measure of change in symmetry of mean connectivity is found to correlate with functional recovery as measured by change in FM score. This supports previous work which has correlated CST integrity and functional improvement and it supports the theory that functional recovery after stroke depends on the extent to which motor CNS symmetry can be regained in the new post-stroke architecture. It also suggests that the movement of the fMRI activations occurs in such a way as to make the most of the preserved white matter connectivity.

This thesis describes the development of a model of cerebral atrophic change associated with neurodegeneration. Neurodegenerative diseases such as Alzheimer's dementia present a significant health problem within the elderly population. Effective treatment relies upon the early detection of anatomic change, and the subsequent differential diagnosis of the disorder from other closely related neurological conditions. Importantly, this also includes the investigation of the relationship between atrophic change and cognitive function. In unison with the growth in neuroimaging technology, myriad methodologies have been developed since the first quantitative measures of atrophic change were deduced via manual tracing. Subsequently, automated region of interest analysis, segmentation, voxel-based morphometry and non-linear registration have all been used to investigate atrophy. These methods commonly report findings of ventricular enlargement and temporal lobe change in AD and other dementias. Whilst these results are accurate indicators of atrophy, they are largely non-specific in their diagnostic utility. In addition, the aforementioned methods have been employed to discern change observed at discrete intervals during a disease process. In order to gain a greater understanding of the temporal characteristics of changes that occur as a result of atrophy, a deformation modelling method that allows the continuous tracking of these changes in a cohort of AD patients and elderly control subjects is presented in this thesis. Deformation modelling involves non-linear registration of images to investigate the change that is apparent between two or more images. The non- linear registration results are analysed and presented via three metrics: local volume loss (atrophy); volume (CSF) increase; and translation (interpreted as representing collapse of cortical structures). Changes observed in the analyses in this thesis are consistent with results from neuro-anatomical studies of AD. Results using the more traditional methods of analysis are presented for comparative purposes.

Diss. (sammanfattning) Uppsala : Univ., 2007. / Härtill 4 uppsatser.

The Whitehall II (Stress and Health) study is a prospective study based on originally 10,308 British civil servants. Since 1985, rich socio-demographic, health and life-style measures have been acquired every 2-5 years. Eight hundred participants were randomly selected from the remaining 6,308 participants of Phase 11 for magnetic resonance imaging (MRI) and further examination in Oxford (2012-14). There is evidence of changes in brain anatomy and mental health following traumatic events, such as combat stress or sexual abuse, in patients with posttraumatic stress disorder, mood or personality disorders, but little is known about the association between everyday stress, brain structure and function, and mental health in the general population. The secondary stress markers, Allostatic Load (AL) index, Framingham Stroke Risk score (FSRS) and Metabolic Syndrome (MetS) were selected as potential predictors of brain changes at follow-up. This thesis focuses on measures of structural grey and white matter (GM, WM) integrity, collected with the Siemens 3T Verio scanner in the first 563 participants of the Oxford study. As hypothesised, stress markers measured as early as 20 years prior to the scan, predicted lower GM and WM integrity in older age. Unique linear relationships remained even after controlling for socio-demographic confounders between each stress marker and GM density but not with measures of WM integrity. This suggests that some, if not most variance is shared between the stress markers and the usual correlates of general health, such as age and employment class. The three markers did not have equal power to predict brain measures: AL added more unique predictive variance to GM density than MetS and FSRS. On the other hand, FSRS was the more powerful predictor of poor WM integrity compared with AL and MetS, and after removing confounding variable effects. This thesis thus provides some empirical support for the concept of allostatic load, linking 'everyday' stress and features of the ageing human brain.

Current thinking suggests that specialised modules process visual information in a hierarchical manner, using local circuitry in order to maximise efficiency both in terms of wiring costs and stimulus coverage (Reichl et al. (2012)). The resulting organisation has been shown to contain structure in the form of stripes, columns and pinwheels, which in animal models have been linked to functional segregation and specificity. In human cortex, post-mortem investigations have assisted in the visualisation of two such key features: ocular dominance columns (ODC) within V1, and a stripe system within V2 (Adams et al. (2007); Hockfield et al. (1990)). However, functional observations in humans have until recently been beyond the investigatory scope of in-vivo methodology, and as such, a role of these networks has yet to be conclusively determined. In the small number of instances of in-vivo investigations of human ODC and V2 stripes (Cheng et al. (2001); Yacoub et al. (2001); Nasr et al. (2016)), data have been acquired for a small number of carefully selected participants over long scan durations. I aimed to overcome these limitations and explore the functional similarities further, employing a novel, ultra-high resolution fMRI sequence to do so. I measured the cortical response to monocular stimulation and recorded a robust response within V1. However, the regular and repeating functional patterns of ODCs were not observed. Using multivariate techniques I concluded, based on robust classification, that reliable monocular signals were present but that they were subtle and difficult to differentiate from noise. I then investigated the segregation of colour, form and motion within V2, where I found evidence for spatially segregated signals in response to colour and motion, but not to form. I hypothesised that the form stimulus was sub-optimal in driving the neural population of the associated stripes. Based on a limited number of samples, activity in response to colour and motion stimulation conformed on average to the neuroanatomical profile of the V2 stripe system. I suggest that my results offer encouragement for in-vivo investigations of small-scale functional organisation in visual cortex.

Idiopathic Parkinson’s disease (IPD) is the second most common neurodegenerative disease, yet effective disease modifying treatments are still lacking. Neurodegeneration involves multiple interacting pathological pathways. The extent to which neurovascular mechanisms are involved in IPD is not well defined. Indeed within the umbrella term of IPD great heterogeneity of motor (and non-motor) features exists, suggesting that different phenotypes may have differing underlying pathophysiologies. We aimed to determine whether novel magnetic resonance imaging (MRI) techniques can reveal changes in structural or physiological neurovascular measures, herein also referred to as ‘altered neurovascular status (NVS)’, in IPD.Based on preliminary data from our initial exploratory study in a small IPD cohort, phenotypic differences in structural and physiological MRI measures of NVS were investigated in a larger study. The 3 Tesla (3T) MRI protocol included T2-weighted fluid-attenuated inversion recovery (FLAIR) imaging to assess white matter lesion (WML) burden, arterial spin labelling (ASL) measurements of cerebral blood flow (CBF) and arterial arrival time (AAT) and dynamic contrast enhanced (DCE) measures of blood-brain barrier (BBB) integrity. Analysis was undertaken of IPD clinical phenotypes, by comparison with two control groups. In total, fifty-one patients with IPD (mean age 69.0 ± 7.7 years) (21 tremor dominant [TD], 24 postural instability and gait disorder [PIGD] and 6 intermediates) were compared with 2 control groups, the first comprising 18 control positive (CP) subjects with a history of clinical cerebrovascular disease (CVD) (mean age 70.1 ± 8.0 years) and the second comprising 34 control negative (CN) subjects without a history of clinical CVD (mean age 67.4 ± 7.6 years). IPD patients showed diffuse regions of significantly prolonged AAT and lower CBF by comparison with CN subjects, and a few regions of prolonged AAT by comparison with CP subjects, despite significantly fewer vascular risk factors. TD patients showed regions of significantly prolonged AAT and lower WML volume by comparison with PIGD patients. IPD patients also showed increased leakiness of the BBB in basal ganglia regions compared to the CN group, with a similar pattern in both IPD phenotypes. These data provide evidence of altered NVS in IPD, with IPD phenotype specific differences.