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Understanding white matter pathology through correlating longitudinal and quantitative MRI metrics weekly in the cuprizone mouse model of demyelination

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dc.contributor.supervisor Martin, Melanie (Physics) Lin, Francis (Physics) en_US
dc.contributor.author Palmer, Vanessa Leanne
dc.date.accessioned 2016-04-12T19:42:41Z
dc.date.available 2016-04-12T19:42:41Z
dc.date.issued 2016
dc.identifier.uri http://hdl.handle.net/1993/31207
dc.description.abstract Magnetic resonance imaging (MRI) methods thought to assess myelin and axon integrity are improving the understanding of white matter diseases like multiple sclerosis (MS). This thesis improved the understanding of how microstructural tissue changes caused by various pathologies influence MRI metrics by developing and applying MRI methods in a longitudinal study using the cuprizone mouse model of MS. In vivo and ex vivo MRI measurments (T1 and T2 relaxometry, diffusion tensor imaging, and quantitative magnetization transfer imaging) were correlated with tissue measurements taken from electron microscopy images of control and cuprizone fed mice at weeks 2 and 3 of cuprizone feeding. Significant Spearman correlations included mean diffusivity vs. myelinated axon fraction (ρ=0.84), ex vivo T2 vs. myelinated axon fraction (ρ=0.68), and normalized T2-weighted signal vs. myelinated axon fraction (ρ =-0.80). Multiparametric MRI studies show promise in bridging the gap between damage detected in images and clinical status associated with MS. en_US
dc.rights info:eu-repo/semantics/openAccess
dc.subject MRI en_US
dc.subject Electron Microscopy en_US
dc.subject Cuprizone mouse model en_US
dc.subject White matter en_US
dc.title Understanding white matter pathology through correlating longitudinal and quantitative MRI metrics weekly in the cuprizone mouse model of demyelination en_US
dc.type info:eu-repo/semantics/masterThesis
dc.degree.discipline Biomedical Engineering en_US
dc.contributor.examiningcommittee Elbakri, Idris (Internal,Radiology) Shafai, Cyrus (Internal, Electrical and Computer Engineering) Suh, Miyoung (External, Human Nutritional Sciences) en_US
dc.degree.level Master of Science (M.Sc.) en_US
dc.description.note May 2016 en_US


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