Stroke is one of the leading causes of death and adult disability worldwide. The major therapeutic intervention for acute ischemic stroke is the administration of recombinant tissue plasminogen activator (rtPA) to help to restore blood flow to the brain. This has been shown to increase the survival rate and to reduce the disability of ischemic stroke patients. However, rtPA is associated with intracranial haemorrhage and thus its administration is currently limited to only about 5% of ischemic stroke patients. More advanced imaging techniques can be used to better stratify patients for rtPA treatment. One new imaging technique, chemical exchange saturation transfer (CEST) magnetic resonance imaging, can potentially image intracellular pH and since tissue acidification happens prior to cerebral infarction, CEST has the potential to predict ischemic injury and hence to improve patient selection. Despite this potential, most studies have generated pH-weighted rather than quantitative pH maps; the most widely used metric to quantify the CEST effect is only able to generate qualitative contrast measurements and suffers from many confounds. The greatest clinical benefit of CEST imaging lies in its ability to non-invasively measure quantitative pH values which may be useful to identify salvageable tissue. The quantitative techniques and work presented in this thesis thus provide the necessary analysis to determine whether a threshold for the quantified CEST effect or for pH exists to help to define tissue outcome following stroke; to investigate the potential of CEST for clinical stroke imaging; and subsequently to facilitate clinical translation of CEST for acute stroke management.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:618346 |
Date | January 2013 |
Creators | Tee, Yee Kai |
Contributors | Payne, Stephen; Chappell, Michael |
Publisher | University of Oxford |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | http://ora.ox.ac.uk/objects/uuid:e5634676-55a5-43ef-92e7-12166f3d6bf0 |
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