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Title: A multimodality magnetic resonance system for studying free radicals in biological systems
Author: McCallum, Stephen John
ISNI:       0000 0001 3622 7563
Awarding Body: University of Aberdeen
Current Institution: University of Aberdeen
Date of Award: 1997
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Free radicals are defined as molecules with one or more unpaired electrons in their outer orbits. They have been implicated in a large number of disease states and consequently there is increasing interest in detecting them in vivo. Having an un-cancelled electron spin, free radicals are amenable to magnetic resonance experiments. For reasons of sensitivity commercially available electron paramagnetic resonance (EPR) spectrometers operate in the X-band (9 GHz). Such frequencies are unsuitable for large biological samples because of excessive electromagnetic losses. This thesis describes the development of a radio frequency continuous wave (RFCW) EPR spectrometer operating around 280 MHz suitable for in vivo studies. The instrument is based around an existing low field NMR imager. The spectrometer includes both automatic frequency control and automatic coupling systems to combat the problems of animal motion. The instrument has been able to detect free radicals in living animals. PEDRI is a technique that can provide high resolution images showing free radical distribution in living systems. The method is based on conventional pulsed NMR imaging combined with dynamic nuclear polarisation The disadvantage of PEDRI is that it is difficult to obtain spectral information such as EPR line-width and g-factor. These parameters are easy to obtain by CW-EPR, and can give useful information. A further development was the combining of the RF CW-EPR instrument with a PEDRI imager to produce a multimodality instrument capable of sequential PEDRI and CW-EPR on the same sample. Switch-over between the two modes of operation takes less than 5 seconds. This instrument combines the advantages of the two types of free radical detection in a single instrument providing an extremely useful and flexible tool.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Pattern recognition & image processing