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

Cortical thickness measurement from magnetic resonance images using partial volume estimation

Measurement of the cortical thickness from 3D Magnetic Resonance Imaging (MRI) can aid diagnosis and longitudinal studies of a wide range of neurodegenerative diseases. We estimate the cortical thickness using a Laplacian approach whereby equipotentials analogous to layers of tissue are computed. The thickness is then obtained using an Eulerian approach where partial differential equations (PDE) are solved, avoiding the explicit tracing of trajectories along the streamlines gradient. This method has the advantage of being relatively fast and insure unique correspondence points between the inner and outer boundaries of the cortex. The original method is challenged when the thickness of the cortex is of the same order of magnitude as the image resolution since partial volume (PV) effect is not taken into account at the gray matter (GM) boundaries. We propose a novel way to take into account PV which improves substantially accuracy and robustness. We model PV by computing a mixture of pure Gaussian probability distributions and use this estimate to initialize the cortical thickness estimation. On synthetic phantoms experiments, the errors were divided by three while reproducibility was improved when the same patients was scanned three consecutive times

Arbeiten zur Optischen Kohärenztomographie, Magnetresonanzspektroskopie und Ultrahochfeld-Magnetresonanztomographie

Abstrakt (Deutsch) Hintergrund: Die Multiple Sklerose ist eine der häufigsten neurologischen Erkrankungen, die zu Behinderung bereits im jungen Erwachsenenalter führen kann. Hierzu tragen im Krankheitsprozess sowohl neuroinflammatorische wie auch neurodegenerative Komponenten bei. Moderne bildgebende Verfahren wie die Ultrahochfeld-Magnetresonanztomographie (UHF-MRT), die Optische Kohärenztomographie (OCT) und die Magnetresonanzspektroskopie (MRS) können benutzt werden, um diese neurodegenerativen Prozesse näher zu charakterisieren und im zeitlichen Verlauf zu beobachten. Zielsetzung: Ziel ist es, die genannten Verfahren zur Charakterisierung von Kohorten von MS-Patienten einzusetzen und die Verfahren zueinander, sowie mit klinischen Parametern in Beziehung zu setzen oder diagnostisch zu nutzen. Methodik: Patienten mit Multipler Sklerose oder Neuromyelitis optica wurden klinisch-neurologisch, mit Optischer Kohärenztomographie, Sehprüfungen, Untersuchungen der visuell evozierten Potentiale (VEP), (Ultrahochfeld-) Magnetresonanztomographie und Magnetresonanzspektroskopie untersucht. Ergebnisse: Die in der Studie eingesetzten bildgebenden Verfahren konnten dazu beitragen, Neuroinflammation und Neurodegeneration bei an Multiple Sklerose erkrankten Patienten näher zu charakterisieren. So steht eine mittels OCT messbare Verdünnung retinaler Nervenfaserschichten (RNFL) in Zusammenhang mit dem per MRT gemessenen Hirnparenchymvolumen und Neurodegeneration anzeigenden Parametern, die mithilfe der Magnetresonanzspektroskopie untersucht wurden. Mithilfe der UHF-MRT konnte ein Zusammenhang zwischen dem Volumen und der entzündlichen Läsionslast der Sehstrahlung, der RNFL-Dicke, VEP-Latenzen und Einschränkungen des Sehvermögens dargestellt werden. Außerdem ließen sich mit der UHF-MRT auch neurogenerative Aspekte im Sinne von bleibenden Parenchymdefekten innerhalb entzündlicher Läsionen und einer Verschmächtigung der Sehstrahlung nachweisen und die Detektion insbesondere kortikaler MS-Läsionen wurde im Vergleich zur konventionellen MRT verbessert. Zusammenfassung: OCT, MRS und UHF-MRT sind Verfahren, die eine genauere Beschreibung von Neuroinflammation und Neurodegeneration bei MS-Patienten ermöglichen, wie hier vor allem für die Sehbahn gezeigt wurde. Sie sind nichtinvasiv und lassen sich zur näheren Charakterisierung des aktuellen Zustandes und zur Beobachtung des Krankheitsverlaufs von MS-Patienten benutzen.Abstract (English) Background: Multiple sclerosis (MS) is the most common disabling neurologic disease, that causes impairment in younger people. Both neuroinflammatory and neurodegenerative processes contribute to the pathogenesis of multiple sclerosis. Innovative imaging methods, such as ultra-high field magnetic resonance tomography (UHF-MRI), optic coherence tomography (OCT) and magnetic resonance spectroscopy (MRS) can be used for characterizing these neurodegenerative processes in detail and over time course. Objective: To use the imaging methods mentioned above to further characterize cohorts of MS patients and to correlate the parameters with themselves as well as with clinical parameters and to evaluate their prognostic and diagnostic relevance. Methods: Patients with multiple sclerosis were examined clinically, by OCT, visual acuity testing, examination of visually evoked potentials, ultra high field magnetic resonance tomography and magnetic resonance spectroscopy. Results: The imaging methods used in these studies contributed to further characterize neuroinflammation und neurodegeneration in multiple sclerosis patients. A thinning of the retinal nerve fiber layer (RNFL) is correlated with brain parenchyma volume measured by MRI, and markers indicating ongoing neurodegenerative processes as detected by MRS. Using UHF-MRI, a correlation between optic radiation properties (such as inflammatory lesion load and its volume) and RNFL thickness, VEP latencies and visual impairment could be demonstrated. Furthermore, UHF-MRI demonstrated neurodegenerative aspects such as parenchymal defects within inflammatory lesions, an optic radiation thinning and allowed a more precise detection of MS lesions than conventional MRI, in particular cortical grey matter lesions. Summary: OCT, MRS and UHF-MRI are feasible methods to provide a more detailed description of neuroinflammation and neurodegeneration in MS patients, as demonstrated in these studies particularly for the visual pathway. They are non-invasive and can be utilized for clinical to study the disease course and also in differential diagnostic procedures

Investigation of the neurovascular coupling in positive and negative BOLD responses in human brain at 7T

Decreases in stimulus-dependent blood oxygenation level dependent (BOLD) signal and their underlying neurovascular origins have recently gained considerable interest. In this study a multi-echo, BOLD-corrected vascular space occupancy (VASO) functional magnetic resonance imaging (fMRI) technique was used to investigate neurovascular responses during stimuli that elicit positive and negative BOLD responses in human brain at 7 T. Stimulus-induced BOLD, cerebral blood volume (CBV), and cerebral blood flow (CBF) changes were measured and analyzed in ‘arterial’ and ‘venous’ blood compartments in macro- and microvasculature. We found that the overall interplay of mean CBV, CBF and BOLD responses is similar for tasks inducing positive and negative BOLD responses. Some aspects of the neurovascular coupling however, such as the temporal response, cortical depth dependence, and the weighting between ‘arterial’ and ‘venous’ contributions, are significantly different for the different task conditions. Namely, while for excitatory tasks the BOLD response peaks at the cortical surface, and the CBV change is similar in cortex and pial vasculature, inhibitory tasks are associated with a maximum negative BOLD response in deeper layers, with CBV showing strong constriction of surface arteries and a faster return to baseline. The different interplays of CBV, CBF and BOLD during excitatory and inhibitory responses suggests different underlying hemodynamic mechanisms

Partial Volume Correction in Quantitative Amyloid Imaging.

Amyloid imaging is a valuable tool for research and diagnosis in dementing disorders. As positron emission tomography (PET) scanners have limited spatial resolution, measured signals are distorted by partial volume effects. Various techniques have been proposed for correcting partial volume effects, but there is no consensus as to whether these techniques are necessary in amyloid imaging, and, if so, how they should be implemented. We evaluated a two-component partial volume correction technique and a regional spread function technique using both simulated and human Pittsburgh compound B (PiB) PET imaging data. Both correction techniques compensated for partial volume effects and yielded improved detection of subtle changes in PiB retention. However, the regional spread function technique was more accurate in application to simulated data. Because PiB retention estimates depend on the correction technique, standardization is necessary to compare results across groups. Partial volume correction has sometimes been avoided because it increases the sensitivity to inaccuracy in image registration and segmentation. However, our results indicate that appropriate PVC may enhance our ability to detect changes in amyloid deposition

Grey-matter texture abnormalities and reduced hippocampal volume are distinguishing features of schizophrenia

Neurodevelopmental processes are widely believed to underlie schizophrenia. Analysis of brain texture from conventional magnetic resonance imaging (MRI) can detect disturbance in brain cytoarchitecture. We tested the hypothesis that patients with schizophrenia manifest quantitative differences in brain texture that, alongside discrete volumetric changes, may serve as an endophenotypic biomarker. Texture analysis (TA) of grey matter distribution and voxel-based morphometry (VBM) of regional brain volumes were applied to MRI scans of 27 patients with schizophrenia and 24 controls. Texture parameters (uniformity and entropy) were also used as covariates in VBM analyses to test for correspondence with regional brain volume. Linear discriminant analysis tested if texture and volumetric data predicted diagnostic group membership (schizophrenia or control). We found that uniformity and entropy of grey matter differed significantly between individuals with schizophrenia and controls at the fine spatial scale (filter width below 2 mm). Within the schizophrenia group, these texture parameters correlated with volumes of the left hippocampus, right amygdala and cerebellum. The best predictor of diagnostic group membership was the combination of fine texture heterogeneity and left hippocampal size. This study highlights the presence of distributed grey-matter abnormalities in schizophrenia, and their relation to focal structural abnormality of the hippocampus. The conjunction of these features has potential as a neuroimaging endophenotype of schizophrenia