3 resultados para stiffness tensor

em Digital Commons at Florida International University


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This dissertation establishes the foundation for a new 3-D visual interface integrating Magnetic Resonance Imaging (MRI) to Diffusion Tensor Imaging (DTI). The need for such an interface is critical for understanding brain dynamics, and for providing more accurate diagnosis of key brain dysfunctions in terms of neuronal connectivity. ^ This work involved two research fronts: (1) the development of new image processing and visualization techniques in order to accurately establish relational positioning of neuronal fiber tracts and key landmarks in 3-D brain atlases, and (2) the obligation to address the computational requirements such that the processing time is within the practical bounds of clinical settings. The system was evaluated using data from thirty patients and volunteers with the Brain Institute at Miami Children's Hospital. ^ Innovative visualization mechanisms allow for the first time white matter fiber tracts to be displayed alongside key anatomical structures within accurately registered 3-D semi-transparent images of the brain. ^ The segmentation algorithm is based on the calculation of mathematically-tuned thresholds and region-detection modules. The uniqueness of the algorithm is in its ability to perform fast and accurate segmentation of the ventricles. In contrast to the manual selection of the ventricles, which averaged over 12 minutes, the segmentation algorithm averaged less than 10 seconds in its execution. ^ The registration algorithm established searches and compares MR with DT images of the same subject, where derived correlation measures quantify the resulting accuracy. Overall, the images were 27% more correlated after registration, while an average of 1.5 seconds is all it took to execute the processes of registration, interpolation, and re-slicing of the images all at the same time and in all the given dimensions. ^ This interface was fully embedded into a fiber-tracking software system in order to establish an optimal research environment. This highly integrated 3-D visualization system reached a practical level that makes it ready for clinical deployment. ^

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This study examined the relationships among ethnicity/race, lifestyle factors, phylloquinone (vitamin K₁) intake, and arterial pulse pressure in a nationally representative sample of older adults from four ethnic/racial groups: non-Hispanic Whites, non-Hispanic Blacks, Mexican Americans, and other Hispanics. This was a cross-sectional study of U.S. representative sample with data from the National Health and Nutrition Examination Surveys, 2007-2008 and 2009-2010 of adults aged 50 years and older (N = 5296). Vitamin K intake was determined by 24-hour recall. Pulse pressure was calculated as the difference between the averages of systolic blood pressure and diastolic blood pressure. Compared to White non-Hispanics, the other ethnic/racial groups were more likely to have inadequate vitamin K₁ intake. Inadequate vitamin K₁ intake was an independent predictor of high arterial pulse pressure. This was the first study that compared vitamin K₁ inadequacy with arterial pulse pressure across ethnicities/races in U.S. older adults. These findings suggest that vitamin K screening may be a beneficial marker for the health of older adults.

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The present study characterized two fiber pathways important for language, the superior longitudinal fasciculus/arcuate fasciculus (SLF/AF) and the frontal aslant tract (FAT), and related these tracts to speech, language, and literacy skill in children five to eight years old. We used Diffusion Tensor Imaging (DTI) to characterize the fiber pathways and administered several language assessments. The FAT was identified for the first time in children. Results showed no age-related change in integrity of the FAT, but did show age-related change in the left (but not right) SLF/AF. Moreover, only the integrity of the right FAT was related to phonology but not audiovisual speech perception, articulation, language, or literacy. Both the left and right SLF/AF related to language measures, specifically receptive and expressive language, and language content. These findings are important for understanding the neurobiology of language in the developing brain, and can be incorporated within contemporary dorsal-ventral-motor models for language.