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postgraduate thesis: Magnetic resonance diffusion characterization of brain diseases

TitleMagnetic resonance diffusion characterization of brain diseases
Authors
Issue Date2012
PublisherThe University of Hong Kong (Pokfulam, Hong Kong)
Citation
Ding, Y. [丁莹]. (2012). Magnetic resonance diffusion characterization of brain diseases. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4961762
AbstractMagnetic resonance imaging (MRI) is a valuable imaging technique. It provides excellent soft tissue contrast and multi-parametric non-invasive imaging protocols. Among those various techniques, diffusion MRI measures the water diffusion properties of biological tissue. It is a useful tool in characterizing various brain tissue microstructures quantitatively. With its rapid development, it is emerging that subtle changes can be probed by diffusion tensor imaging (DTI) quantitation. The objectives of this doctoral work are to access the subtle microstructural alterations in rodent brains due to hemodynamic changes, fear conditioning and sleep deprivation using in vivo DTI. With the improved reproducibility and specificity achieved by using advanced post-processing and animal preparation procedures, in vivo DTI is expected to be useful to explore the underlying biological mechanisms for posttraumatic stress disorder and memory deficit following sleep loss in human. Firstly, as DTI could be influenced by the presence of water molecules in brain vasculature, for better understand the reproducibility and sensitivity of in vivo DTI measurements, conventional DTI protocol was applied to a well-controlled rat model of hypercapnia. Our data demonstrated that diffusivities increased in whole brain, gray and white matter regions in response to hypercapnia. These results indicate that in vivo DTI quantitation in brain can be interfered by vascular factors on the order of few percents. Cautions should be taken in designing and interpreting quantitative DTI studies as all DTI indices can be potentially confounded by physiologic conditions, cerebrovascular and hemodynamic characteristics. Secondly, recent DTI studies have shown detection of long-term neural plasticity weeks to months following relatively extensive periods of training in animals. However, rapid plasticity within a short period (24 hours) after learning is important for observing the time course of training-evoked changes and narrow down candidate mechanisms. Fear conditioning (FC), which typically occurs over a short timescale (in minutes), was selected as a paradigm for investigation. Using voxel-wise repeated measures analysis, FA was found to increase in amygdala and decrease in hippocampus 1-hour post-FC, and it reversed in both regions 1-day post-FC. Results indicate that DTI can detect rapid microstructural changes in brain regions known to mediate fear conditioning in vivo. DTI indices could be explored as a translational tool to capture potential early biological changes in individuals at risk for developing post-traumatic stress disorder. Thirdly, in vivo DTI was employed to access regional specific microstructural changes following rapid eye movement sleep deprivation (SD), and explore possible temporal differentiation of these changes. With voxel-base analysis, MD is found to decrease in post-SD time points in bilateral hippocampi and cerebral cortex. The distributions of these clusters exhibited differentiable layer specific patterns, which were pointing to dentate gyrus and CA1 layer in hippocampus, and parietal cortex and barrel field layers in cerebral cortex. Results indicate that in vivo DTI is capable to detect microstructural changes in specific layers and reveal temporal distinction between them. These specific layers are possibly more susceptible to sleep loss, and the temporal distinction of changes between these layers might underlie learning and memory decline after SD.
DegreeDoctor of Philosophy
SubjectBrain - Imaging.
Diffusion tensor imaging.
Dept/ProgramElectrical and Electronic Engineering
Persistent Identifierhttp://hdl.handle.net/10722/180942

 

DC FieldValueLanguage
dc.contributor.authorDing, Ying-
dc.contributor.author丁莹-
dc.date.accessioned2013-02-07T06:21:03Z-
dc.date.available2013-02-07T06:21:03Z-
dc.date.issued2012-
dc.identifier.citationDing, Y. [丁莹]. (2012). Magnetic resonance diffusion characterization of brain diseases. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4961762-
dc.identifier.urihttp://hdl.handle.net/10722/180942-
dc.description.abstractMagnetic resonance imaging (MRI) is a valuable imaging technique. It provides excellent soft tissue contrast and multi-parametric non-invasive imaging protocols. Among those various techniques, diffusion MRI measures the water diffusion properties of biological tissue. It is a useful tool in characterizing various brain tissue microstructures quantitatively. With its rapid development, it is emerging that subtle changes can be probed by diffusion tensor imaging (DTI) quantitation. The objectives of this doctoral work are to access the subtle microstructural alterations in rodent brains due to hemodynamic changes, fear conditioning and sleep deprivation using in vivo DTI. With the improved reproducibility and specificity achieved by using advanced post-processing and animal preparation procedures, in vivo DTI is expected to be useful to explore the underlying biological mechanisms for posttraumatic stress disorder and memory deficit following sleep loss in human. Firstly, as DTI could be influenced by the presence of water molecules in brain vasculature, for better understand the reproducibility and sensitivity of in vivo DTI measurements, conventional DTI protocol was applied to a well-controlled rat model of hypercapnia. Our data demonstrated that diffusivities increased in whole brain, gray and white matter regions in response to hypercapnia. These results indicate that in vivo DTI quantitation in brain can be interfered by vascular factors on the order of few percents. Cautions should be taken in designing and interpreting quantitative DTI studies as all DTI indices can be potentially confounded by physiologic conditions, cerebrovascular and hemodynamic characteristics. Secondly, recent DTI studies have shown detection of long-term neural plasticity weeks to months following relatively extensive periods of training in animals. However, rapid plasticity within a short period (24 hours) after learning is important for observing the time course of training-evoked changes and narrow down candidate mechanisms. Fear conditioning (FC), which typically occurs over a short timescale (in minutes), was selected as a paradigm for investigation. Using voxel-wise repeated measures analysis, FA was found to increase in amygdala and decrease in hippocampus 1-hour post-FC, and it reversed in both regions 1-day post-FC. Results indicate that DTI can detect rapid microstructural changes in brain regions known to mediate fear conditioning in vivo. DTI indices could be explored as a translational tool to capture potential early biological changes in individuals at risk for developing post-traumatic stress disorder. Thirdly, in vivo DTI was employed to access regional specific microstructural changes following rapid eye movement sleep deprivation (SD), and explore possible temporal differentiation of these changes. With voxel-base analysis, MD is found to decrease in post-SD time points in bilateral hippocampi and cerebral cortex. The distributions of these clusters exhibited differentiable layer specific patterns, which were pointing to dentate gyrus and CA1 layer in hippocampus, and parietal cortex and barrel field layers in cerebral cortex. Results indicate that in vivo DTI is capable to detect microstructural changes in specific layers and reveal temporal distinction between them. These specific layers are possibly more susceptible to sleep loss, and the temporal distinction of changes between these layers might underlie learning and memory decline after SD.-
dc.languageeng-
dc.publisherThe University of Hong Kong (Pokfulam, Hong Kong)-
dc.relation.ispartofHKU Theses Online (HKUTO)-
dc.rightsThe author retains all proprietary rights, (such as patent rights) and the right to use in future works.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.source.urihttp://hub.hku.hk/bib/B4961762X-
dc.subject.lcshBrain - Imaging.-
dc.subject.lcshDiffusion tensor imaging.-
dc.titleMagnetic resonance diffusion characterization of brain diseases-
dc.typePG_Thesis-
dc.identifier.hkulb4961762-
dc.description.thesisnameDoctor of Philosophy-
dc.description.thesislevelDoctoral-
dc.description.thesisdisciplineElectrical and Electronic Engineering-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.5353/th_b4961762-
dc.date.hkucongregation2013-

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