Queen's University - Utility Bar

QSpace at Queen's University >
Theses, Dissertations & Graduate Projects >
Queen's Theses & Dissertations >

Please use this identifier to cite or link to this item: http://hdl.handle.net/1974/6085

Title: Variability of DTI Values in the Human Cervical and Lumbar Spinal Cord
Authors: NAHANNI, Celina

Files in This Item:

File Description SizeFormat
Nahanni_Celina_201009_MSc.pdf5.39 MBAdobe PDFView/Open
Keywords: Diffusion Tensor Imaging
human
Spinal Cord
classification
motion
partial volume effects
Issue Date: 2010
Series/Report no.: Canadian theses
Abstract: Diffusion Tensor Imaging (DTI) is a medical imaging method that measures tissue structure. This is valuable when applied to the central nervous system (CNS) because it can provide structural information about white matter tracts. DTI of the spinal cord has been suggested as the next great leap in clinical diagnostics for spinal cord injury and disease because it may provide a measurable correlate of the physical structure of the cord with the associated functional deficit. Collecting precise structural information from the site of injury could be used to improve diagnostics and guide treatments. While these are the long term goals of DTI research, there are currently fundamental questions with regards to image resolution and motion-related artifacts in spinal cord which have not been thoroughly addressed. DTI is a sensitive imaging method which requires multiple mathematical calculations and approximations to complete. The limitations of the method compound with the limitations of imaging the spinal cord leading to the query: How reliable is DTI in the spinal cord? It is the goal of this study to begin to address these concerns. First, the effect of spinal cord motion on tissue discrimination was examined by comparing DTI results obtained in the presence and absence of a correctional measure for cardiac-induced motion called 'cardiac gating'. Tissue discriminability was found to be greatest in the cervical cord. Second, DTI results were subjected to two classification algorithms and compared with known anatomy to assess tissue discrimination accuracy as well as the types of associated errors. The proportion of errors in tissue classification was very high, presenting itself in all subjects. This result indicated that the DTI values associated with particular tissues were not unique to only those tissues. Finally, a theoretical model was implemented to assess the degree to which image resolution specifically affected the tissue classification accuracy obtained in the above experiments, as opposed to other errors such as MRI ghosting, blurring or distortions. It was found that DTI provides a systematically biased representation of spinal cord tissues. To overcome this limitation, future studies should concentrate efforts on increasing image resolution.
Description: Thesis (Master, Neuroscience Studies) -- Queen's University, 2010-09-24 02:29:32.619
URI: http://hdl.handle.net/1974/6085
Appears in Collections:Queen's Theses & Dissertations
Neuroscience Studies Graduate Theses

Items in QSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

 

  DSpace Software Copyright © 2002-2008  The DSpace Foundation - TOP