In two separate studies, we used diffusion tensor imaging (DTI)to examine white matter changes secondary to traumatic brain injury (TBI) and spinal cord injury (SCI). The first study examined the utility of DTI for a single case diagnosis of mild TBI (mTBI) and demonstrated that the anterior limb of the internal capsule and the genu of the corpus callosum were sensitive and specific to mTBI. The second study examined the sub-acute effects of SCI on white matter tissue in the brain and demonstrated that SCI patients have a significantly greater degree of FA asymmetry than control subjects in the superior and posterior corona radiata. The first study has provided preliminary proof of principal evidence that DTI can be used to diagnose mTBI in individual cases. The second study suggests that the degree of asymmetry may be a useful biomarker for detecting subtle white matter changes.

Diffusion Tensor Imaging (DTI) can quantify tissue integrity in normal-appearing white matter (NAWM). NAWM abnormalities present at the earliest time point implicate neurodegeneration operative from the outset of multiple sclerosis (MS). DTI scans were obtained at first attacks from 6 children later diagnosed with MS and 6 children with monophasic demyelination, and from 6 controls, matched for age. DTI scans were also obtained from 22 children with established MS with clinical onset before age 12 years and compared to age-matched controls. Atlas- and tractography-based image processing methods were utilized. DTI metrics distinguished MS patients from patients with monophasic demyelination and from controls at the first attack. Differences in NAWM between children with established early-onset MS and controls were only notable when DTI was obtained in adolescence. DTI provides valuable insights into NAWM in children with MS, although in the youngest patients such changes may require time to develop.

A complete scientific understanding of human nature requires delineation of the neurobiological characteristics underlying the unique features of the human mind. This effort can be facilitated by comparing the human brain with the brains of other living primate species. Humans are more susceptible to neurodegenerative diseases than other primate species, including our closest living primate relatives, the chimpanzees. Comparing age-related changes in brain structure between humans and non-human primates could, therefore, potentially shed light on the neurological basis of this human vulnerability. Further, human brains are lateralized with specialized cognitive and behavioral functions. Comparing the magnitude of hemispheric asymmetries in brain structure between humans and non-human primates can probe insights into this human specific capability and learn more about human evolution. Diffusion weighted MRI protocols were developed for different species, taking into account their neuroanatomical differences. For Chimpanzees, a multi-shot DWI sequence was developed and compared with a single-shot DWI sequence to determine which provided a better quality diffusion data free of acquisition related artifacts. Different simulation techniques were used to evaluate the effect of segmentation-related motion artifact (ghosting) on the multi-shot DTI data. Although both protocols generated high-resolution diffusion MRI data with correctable susceptibility-induced distortions, the single-shot protocol enables the acquisition of the high-resolution diffusion MRI data freed of ghosting and with twice the signal-to-noise ratio (SNR), for the same scan duration. The acquired chimpanzee and macaque diffusion data were used to compare the magnitude of microstructural asymmetries and age-related decline of brain white matter with those in humans. Hemispheric asymmetry results show a pattern of strong leftward asymmetry in human DTI indices that differs markedly from the chimpanzee (multi-shot data) and the rhesus macaque patterns involving both rightward and leftward asymmetries. The magnitude of leftward asymmetry increased for chimpanzees scanned with single-shot DTI sequence. Region of interest analyses within the corpus callosum revealed a significant age-related increase in fractional anisotropy (FA) in the genu for chimpanzees (multi-shot data) and no significant change in any region for macaques. Additionally, voxel-wise analysis using Tract Based Spatial Statistics (TBSS) revealed widespread age-related FA increases for chimpanzees (multi-shot data) and weak age-related decreases in FA for macaques across most white matter tracts. Overall, results from these multi-shot data analyses suggest that rhesus monkeys show age-related decreases in white matter integrity that parallel changes found in humans, whereas chimpanzees show age-related increases in white matter integrity. On the contrary, the single-shot data results for chimpanzees revealed no significant relationship between age and the different DTI indices. These noteworthy species differences may help to explain the unique features of the human mind and why humans are more susceptible to neurodegenerative diseases. Furthermore, these studies demonstrate the need for complementary histological studies of white matter microstructure in humans, chimpanzees and macaques to clarify the cellular and molecular basis of these findings.

Thesis (Ph.D)--Biomedical Engineering, Georgia Institute of Technology, 2009. / Committee Chair: Hu, Xiaoping; Committee Member: Brummer, Marijn; Committee Member: Duong, Tim; Committee Member: Keilholz, Shella; Committee Member: Schumacher, Eric. Part of the SMARTech Electronic Thesis and Dissertation Collection.

No description available.

Diffusion Tensor Imaging (DTI) is a medical imaging method that measures tissue structure. This is valuable when applied to the central nervous system (CNS) because it can provide structural information about white matter tracts. DTI of the spinal cord has been suggested as the next great leap in clinical diagnostics for spinal cord injury and disease because it may provide a measurable correlate of the physical structure of the cord with the associated functional deficit. Collecting precise structural information from the site of injury could be used to improve diagnostics and guide treatments. While these are the long term goals of DTI research, there are currently fundamental questions with regards to image resolution and motion-related artifacts in spinal cord which have not been thoroughly addressed. DTI is a sensitive imaging method which requires multiple mathematical calculations and approximations to complete. The limitations of the method compound with the limitations of imaging the spinal cord leading to the query: How reliable is DTI in the spinal cord? It is the goal of this study to begin to address these concerns. First, the effect of spinal cord motion on tissue discrimination was examined by comparing DTI results obtained in the presence and absence of a correctional measure for cardiac-induced motion called 'cardiac gating'. Tissue discriminability was found to be greatest in the cervical cord. Second, DTI results were subjected to two classification algorithms and compared with known anatomy to assess tissue discrimination accuracy as well as the types of associated errors. The proportion of errors in tissue classification was very high, presenting itself in all subjects. This result indicated that the DTI values associated with particular tissues were not unique to only those tissues. Finally, a theoretical model was implemented to assess the degree to which image resolution specifically affected the tissue classification accuracy obtained in the above experiments, as opposed to other errors such as MRI ghosting, blurring or distortions. It was found that DTI provides a systematically biased representation of spinal cord tissues. To overcome this limitation, future studies should concentrate efforts on increasing image resolution. / Thesis (Master, Neuroscience Studies) -- Queen's University, 2010-09-24 02:29:32.619

No description available.

Diffusion tensor imaging (DTI) is a structural magnetic resonance imaging (MRI) technique to record incoherent motion of water molecules and has been used to detect micro structural white matter alterations in clinical studies to explore certain brain disorders. A variety of DTI based techniques for detecting brain disorders and facilitating clinical group analysis have been developed in the past few years. However, there are two crucial issues that have great impacts on the performance of those algorithms. One is that brain neural pathways appear in complicated 3D structures which are inappropriate and inaccurate to be approximated by simple 2D structures, while the other involves the computational efficiency in classifying white matter tracts. The first key area that this dissertation focuses on is to implement a novel computing scheme for estimating regional white matter alterations along neural pathways in 3D space. The mechanism of the proposed method relies on white matter tractography and geodesic distance mapping. We propose a mask scheme to overcome the difficulty to reconstruct thin tract bundles. Real DTI data are employed to demonstrate the performance of the pro- posed technique. Experimental results show that the proposed method bears great potential to provide a sensitive approach for determining the white matter integrity in human brain. Another core objective of this work is to develop a class of new modeling and clustering techniques with improved performance and noise resistance for separating reconstructed white matter tracts to facilitate clinical group analysis. Different strategies are presented to handle different scenarios. For whole brain tractography reconstructed white matter tracts, a Fourier descriptor model and a clustering algorithm based on multivariate Gaussian mixture model and expectation maximization are proposed. Outliers are easily handled in this framework. Real DTI data experimental results show that the proposed algorithm is relatively effective and may offer an alternative for existing white matter fiber clustering methods. For a small amount of white matter fibers, a modeling and clustering algorithm with the capability of handling white matter fibers with unequal length and sharing no common starting region is also proposed and evaluated with real DTI data.

In der vorliegenden Arbeit wird der Hypothalamus, eine kleine, aber bedeutsame Struktur des Zwischenhirns untersucht. Er spielt unter anderem eine Rolle bei der Regulation des Schlaf-Wach-Rhythmus, des Sexualverhaltens, der Stimmungslage, autonomer und Stoffwechsel-Funktionen. Veränderungen einzelner oder mehrerer spezifischer Kerngruppen sind bei neuropsychiatrischen bzw. -endokrinologischen Erkrankungen, wie Narkolepsie, Schizophrenie, affektiver Störung, Demenz, Borderline-Persönlichkeitsstörung, Pädophilie oder Adipositas zu beobachten. Die Substrukturierung und Darstellung der einzelnen Kerngruppen gelang bisher nur in Postmortem-Studien. Im Rahmen dieser Studie konnte mit Hilfe der Diffusions-Tensor-Bildgebung erstmals eine in-vivo Substrukturierung des Hypothalamus konsistent bei zehn gesunden Probanden vorgenommen werden. Dabei wurden nach einem Algorithmus zunächst die Segmentierung und anschließend die Parzellierung durchgeführt, woraus sich drei konsistente Cluster ergaben. Der topografische Vergleich der erhaltenen Cluster mit Postmortem-Studien der Literatur ergab vergleichbare und anatomisch plausible Korrelate. Mit der von uns entwickelten Methode könnten anhand einer größeren Patientengruppe pathophysiologische Zusammenhänge neuropsychiatrischer und –endokrinologischer Störungen genauer eruiert werden und zu einem besseren Verständnis des Krankheitsverlaufs und der Therapie beitragen.

<p>Understanding the structure of the brain has been a major goal of neuroscience research over the past century, driven in part by the understanding that brain structure closely follows function. Normative brain maps, or atlases, can be used to understand normal brain structure, and to identify structural differences resulting from disease. Recently, diffusion tensor magnetic resonance imaging has emerged as a powerful tool for brain atlasing; however, its utility is hindered by image resolution and signal limitations. These limitations can be overcome by imaging fixed ex-vivo specimens stained with MRI contrast agents, a technique known as diffusion tensor magnetic resonance histology (DT-MRH). DT-MRH represents a unique, quantitative tool for mapping the brain with unprecedented structural detail. This technique has engendered a new generation of 3D, digital brain atlases, capable of representing complex dynamic processes such as neurodevelopment. This dissertation explores the use of DT-MRH for quantitative brain atlasing in an animal model and initial work in the human brain. </p><p>Chapter 1 describes the advantages of the DT-MRH technique, and the motivations for generating a quantitative atlas of rat postnatal neurodevelopment. The second chapter covers optimization of the DT-MRH hardware and pulse sequence design for imaging the developing rat brain. Chapter 3 details the acquisition and curation of rat neurodevelopmental atlas data. Chapter 4 describes the creation and implementation of an ontology-based segmentation scheme for tracking changes in the developing brain. Chapters 5 and 6 pertain to analyses of volumetric changes and diffusion tensor parameter changes throughout rat postnatal neurodevelopment, respectively. Together, the first six chapters demonstrate many of the unique and scientifically valuable features of DT-MRH brain atlases in a popular animal model.</p><p>The final two chapters are concerned with translating the DT-MRH technique for use in human and non-human primate brain atlasing. Chapter 7 explores the validity of assumptions imposed by DT-MRH in the primate brain. Specifically, it analyzes computer models and experimental data to determine the extent to which intravoxel diffusion complexity exists in the rhesus macaque brain, a close model for the human brain. Finally, Chapter 8 presents conclusions and future directions for DT-MRH brain atlasing, and includes initial work in creating DT-MRH atlases of the human brain. In conclusion, this work demonstrates the utility of a DT-MRH brain atlasing with an atlas of rat postnatal neurodevelopment, and lays the foundation for creating a DT-MRH atlas of the human brain.</p> / Dissertation