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|Title||Improved analysis of MRI tractography data: Group comparisons of parameters along fibre tracks|
Medical Physics Programme
|Full-text||Available as PDF|
Diffusion MRI is an imaging technique capable of inferring information about the tissue microstructure, based on magnetic resonance imaging (MRI). Diffusion MRI data can be analysed using tractography, a tool able to represent the structure of the white matter (WM) in the brain. Tractography is commonly used qualitatively, but in this report, an algorithm for quantitative tractography was developed.
A new evaluation method was developed in order to analyse diffusion parameters in all positions along WM pathways. The developed algorithm was then applied to WM pathways that had been calculated and extracted in a software, based on streamline tractography calculations of the diffusion data. Co-registrations of the data made comparisons across subjects and between groups possible. The algorithm was tested by analysing the inferior-fronto occipital fasciculus (IFO) in males versus females as well as young versus old healthy volunteers. Comparisons were also performed to clinical research projects, by analyzing the IFO in semantic dementia (SD) patients versus healthy controls (HC-SD) and the inferior longitudinal fasciculus (IFL) in intrauterine growth restriction (IUGR) patients versus HC-IUGR.
The calculated values of the diffusion parameters were in agreement with was expected from earlier published results. In the SD patients, diffusion parameters were significant different from the parameters in HC-SD in anterior as well as in posterior parts of the IFO. Large regions of significant differences were present the temporal lobe, when diffusion parameters of the IFL were compared between IUGR patients and HC-IUGR.
In summary, with the aid of an in-house developed algorithm, diffusion parameters could be calculated along the WM pathways. This new evaluation method could lead to a higher sensitivity in detecting local deviations in the properties of the WM pathways, as compared to what could be achieved with conventional analysis methods.
Medicine and Health Sciences
|Document type||Master's Degree (Two Years)|