Characterization of PC-MRI data
The work in this thesis focuses on the development and implementation of practical approaches to measure and characterise flow data using phase contrast magnetic resonance imaging (PC-MRI), and to use some of the body's natural physiological processes to modulate blood flow with the aim of prod...
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ndltd-bl.uk-oai-ethos.bl.uk-5555022015-03-20T04:57:29ZCharacterization of PC-MRI dataTotman, John2011The work in this thesis focuses on the development and implementation of practical approaches to measure and characterise flow data using phase contrast magnetic resonance imaging (PC-MRI), and to use some of the body's natural physiological processes to modulate blood flow with the aim of producing additional probes to study pathologies. The use of low spatial resolution PC-MRI is investigated to allow high sampling rates and near-simultaneous measurement at multiple sites to be performed. The precision of this was validated and used to demonstrate changes in flow provoked by the use of glucose as a probe to alter abdominal blood flow. Waveform analysis to interrogate the phasic temporal flow waveform (PTFW) was also used to further characterise impact of the glucose on normal physiology. Through further experimentation, optimised sequences for the quantification of flow in the much more challenging environment of the right coronary artery (RCA) were implemented. New mathematical models were developed to perform waveform analysis on the RCA unique waveform shape flow data. A Gaussian model proved the most robust model successfully able to model the RCA PTFW with 84% flux and 93% velocity data modelled with over all total residual R2 = 0.68 ± 0.15 flux and R2 = 0.65 ± 0.14 velocity PC-MRI data respectively providing a good fit in all areas except the incisure (the recover period of the wave form after systole and before diastole) and the best overall fit across the entire PTFW. The physiological impact of blood flow during respiratory suspension at defined pressures, as a proxy for inter thoracic pressure, was explored. PC-MR blood flow, and PTFW measurements in the thoracic descending aorta and RCA were assessed for modulation.616.07548University of Nottinghamhttp://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.555502Electronic Thesis or Dissertation |
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616.07548 Totman, John Characterization of PC-MRI data |
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The work in this thesis focuses on the development and implementation of practical approaches to measure and characterise flow data using phase contrast magnetic resonance imaging (PC-MRI), and to use some of the body's natural physiological processes to modulate blood flow with the aim of producing additional probes to study pathologies. The use of low spatial resolution PC-MRI is investigated to allow high sampling rates and near-simultaneous measurement at multiple sites to be performed. The precision of this was validated and used to demonstrate changes in flow provoked by the use of glucose as a probe to alter abdominal blood flow. Waveform analysis to interrogate the phasic temporal flow waveform (PTFW) was also used to further characterise impact of the glucose on normal physiology. Through further experimentation, optimised sequences for the quantification of flow in the much more challenging environment of the right coronary artery (RCA) were implemented. New mathematical models were developed to perform waveform analysis on the RCA unique waveform shape flow data. A Gaussian model proved the most robust model successfully able to model the RCA PTFW with 84% flux and 93% velocity data modelled with over all total residual R2 = 0.68 ± 0.15 flux and R2 = 0.65 ± 0.14 velocity PC-MRI data respectively providing a good fit in all areas except the incisure (the recover period of the wave form after systole and before diastole) and the best overall fit across the entire PTFW. The physiological impact of blood flow during respiratory suspension at defined pressures, as a proxy for inter thoracic pressure, was explored. PC-MR blood flow, and PTFW measurements in the thoracic descending aorta and RCA were assessed for modulation. |
author |
Totman, John |
author_facet |
Totman, John |
author_sort |
Totman, John |
title |
Characterization of PC-MRI data |
title_short |
Characterization of PC-MRI data |
title_full |
Characterization of PC-MRI data |
title_fullStr |
Characterization of PC-MRI data |
title_full_unstemmed |
Characterization of PC-MRI data |
title_sort |
characterization of pc-mri data |
publisher |
University of Nottingham |
publishDate |
2011 |
url |
http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.555502 |
work_keys_str_mv |
AT totmanjohn characterizationofpcmridata |
_version_ |
1716788019401326592 |