Detection of Neurotransmitters in the Human Brain Using Magnetic Resonance Spectroscopy
Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
There is an increasing interest in studying the concentration of the inhibitory neurotransmitter γ-Amino Butyric Acid (GABA), both in the healthy and diseased brain by using Magnetic Resonance Spectroscopy (MRS). Recent studies have shown correlations between an abnormal GABA concentration in certain regions of the brain and disorders as e.g. Parkinson’s disease and depressive disorders. There are presently many technical difficulties with the absolute quantification of GABA and the method MEGA-PRESS is currently the standard technique used in data acquisitions and processing of spectra. In this thesis, different techniques of GABA quantification have been evaluated and the most important aspect was to explore the precision of the method for further usage as a clinical tool. This project involved the exploration of data acquisitions by using a MEGA-PRESS sequence on a 3 T MR-system, processing of the resulting datasets using different methodologies, GABA quantification by using linear combination of model spectra (LCModel), and interpretation of the results by performing statistical analyses. The thesis resulted in a low resolution GABA-atlas of the brain which did not indicate any significant differences in the GABA concentration within the healthy subject group. However, a significant regional difference was observed in the brain. The main uncertainties arose mainly due to the relatively small subject groups and the large measurement error. Future measurements will require improvements both in the data acquisition and in analyzing these with an improved method of processing. The final conclusion was that the GABA quantification sequence MEGA-PRESS is useful both in diagnosis and as a research tool, although further improvements are required.
Place, publisher, year, edition, pages
2013. , 79 p.
GABA, MRS, MEGA-PRESS
Other Medical Engineering
IdentifiersURN: urn:nbn:se:liu:diva-95906ISRN: LIU-IMH/RV-A--13/001--SEOAI: oai:DiVA.org:liu-95906DiVA: diva2:640541
Subject / course