Developments in the use of diffusion tensor imaging data to investigate brain structure and connectivity

Diffusion tensor imaging (DTI) is a specialist MRI modality that can identify microstructural changes or abnormalities in the brain. It can also be used to show fibre tract pathways. Both of these features were used in this thesis. Firstly, standard imaging analysis techniques were used to study the...

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Main Author: Chappell, Michael Hastings
Language:en
Published: University of Canterbury. Physics and Astronomy 2008
Subjects:
Online Access:http://hdl.handle.net/10092/1476
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spelling ndltd-canterbury.ac.nz-oai-ir.canterbury.ac.nz-10092-14762015-03-30T15:30:06ZDevelopments in the use of diffusion tensor imaging data to investigate brain structure and connectivityChappell, Michael Hastingsdiffusion tensor imagingmicrostructural brain damagemild repetitive head injuryHotelling's T2 analysislineardiscriminant analysisParkinson's diseasetracking cognitive declinetractographyDiffusion tensor imaging (DTI) is a specialist MRI modality that can identify microstructural changes or abnormalities in the brain. It can also be used to show fibre tract pathways. Both of these features were used in this thesis. Firstly, standard imaging analysis techniques were used to study the effects of mild, repetitive closed head injury on a group of professional boxers. Such data is extremely rare, so the findings of regions of brain abnormalities in the boxers are important, adding to the body of knowledge about more severe traumatic brain injury. The author developed a novel multivariate analysis technique which was used on the same data. This new technique proved to be more sensitive than the standard univariate methods commonly used. An important part of diagnosing and monitoring brain damage involves the use of biomarkers. A novel investigation of whether diffusion parameters obtained from DTI data could serve as bio-markers of cognitive impairment in Parkinson's disease was conducted. This also involved developing a multivariate approach, which displayed increased sensitivity compared with any of the component parameters used singly, and suggested these diffusion measures could be robust bio-markers of cognitive impairment. Fibre tract connectivity between regions of the brain is also a potentially valuable measure for diagnosis and monitoring brain integrity. The feasibility of this was investigated in a multi-modal MRI study. Functional MRI (fMRI) identifies regions of activation associated with a particular task. DTI can then find the pathway of the fibre bundles connecting these regions. The feasibility of using regional connectivity to interrogate brain integrity was investigated using a single healthy volunteer. Fibre pathways between regions activated and deactivated by a working memory paradigm were determined. Though the results are only preliminary, they suggest that this line of research should be continued.University of Canterbury. Physics and Astronomy2008-09-08T00:39:29Z2008-09-08T00:39:29Z2007Electronic thesis or dissertationTexthttp://hdl.handle.net/10092/1476enNZCUCopyright Michael Hastings Chappellhttp://library.canterbury.ac.nz/thesis/etheses_copyright.shtml
collection NDLTD
language en
sources NDLTD
topic diffusion tensor imaging
microstructural brain damage
mild repetitive head injury
Hotelling's T2 analysis
lineardiscriminant analysis
Parkinson's disease
tracking cognitive decline
tractography
spellingShingle diffusion tensor imaging
microstructural brain damage
mild repetitive head injury
Hotelling's T2 analysis
lineardiscriminant analysis
Parkinson's disease
tracking cognitive decline
tractography
Chappell, Michael Hastings
Developments in the use of diffusion tensor imaging data to investigate brain structure and connectivity
description Diffusion tensor imaging (DTI) is a specialist MRI modality that can identify microstructural changes or abnormalities in the brain. It can also be used to show fibre tract pathways. Both of these features were used in this thesis. Firstly, standard imaging analysis techniques were used to study the effects of mild, repetitive closed head injury on a group of professional boxers. Such data is extremely rare, so the findings of regions of brain abnormalities in the boxers are important, adding to the body of knowledge about more severe traumatic brain injury. The author developed a novel multivariate analysis technique which was used on the same data. This new technique proved to be more sensitive than the standard univariate methods commonly used. An important part of diagnosing and monitoring brain damage involves the use of biomarkers. A novel investigation of whether diffusion parameters obtained from DTI data could serve as bio-markers of cognitive impairment in Parkinson's disease was conducted. This also involved developing a multivariate approach, which displayed increased sensitivity compared with any of the component parameters used singly, and suggested these diffusion measures could be robust bio-markers of cognitive impairment. Fibre tract connectivity between regions of the brain is also a potentially valuable measure for diagnosis and monitoring brain integrity. The feasibility of this was investigated in a multi-modal MRI study. Functional MRI (fMRI) identifies regions of activation associated with a particular task. DTI can then find the pathway of the fibre bundles connecting these regions. The feasibility of using regional connectivity to interrogate brain integrity was investigated using a single healthy volunteer. Fibre pathways between regions activated and deactivated by a working memory paradigm were determined. Though the results are only preliminary, they suggest that this line of research should be continued.
author Chappell, Michael Hastings
author_facet Chappell, Michael Hastings
author_sort Chappell, Michael Hastings
title Developments in the use of diffusion tensor imaging data to investigate brain structure and connectivity
title_short Developments in the use of diffusion tensor imaging data to investigate brain structure and connectivity
title_full Developments in the use of diffusion tensor imaging data to investigate brain structure and connectivity
title_fullStr Developments in the use of diffusion tensor imaging data to investigate brain structure and connectivity
title_full_unstemmed Developments in the use of diffusion tensor imaging data to investigate brain structure and connectivity
title_sort developments in the use of diffusion tensor imaging data to investigate brain structure and connectivity
publisher University of Canterbury. Physics and Astronomy
publishDate 2008
url http://hdl.handle.net/10092/1476
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