|Author's Email Address
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||Computer Science and Engineering|
|Type of Document
||The Quantitative Investigation of LCModel BASIS Using GAMMA Visual Analysis (GAVA) for in vivo 1H MR Spectroscopy|
|Date of Defense
magnetic resonance spectroscopy
magnetic resonance imaging
||Magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) has been developed and applied to clinical analysis studies due to its non-invasive properties. Because of the increasing clinical interests of applying MRS, a lot of post-processing tools has been developed, among which LCModel is one of the most popular.|
LCModel estimates the absolute metabolite concentrations in vivo according to the basis file, so basis files play an important role for the accuracy of absolute metabolite concentrations. The default basis sets of LCModel were made by phantom experiments. However, some special metabolites are difficult to get them, so the basis sets lack for these metabolites. In order to avoid this trouble, LCModel provides a special method called “spectra offering”.
In this study, we use GAMMA Visual Analysis (GAVA) software to create basis sets and compare the shape of LCModel default basis sets with the shape of GAVA basis sets. Some metabolites which are not included in the LCModel phantom experiments are also generated. Finally, we estimate the absolute concentrations in normal subjects and patients by using these two kinds of basis sets respectively.
Using LCModel “spectra offering” method to append extra metabolites for LCModel basis sets is applicable to those metabolites of singlet resonance but not of J-coupling resonance in the meanwhile. Our results demonstrate that using GAVA simulation as the basis set leads to different quantitative results from using basis sets of in vitro. We believe that using GAVA simulation as the basis set would provide better consistency among all metabolites and thus achieve more accurate quantification of MRS.
||Ping-Hong Lai - chair|
Tzu-Chao Chuang - co-chair
Hsiao-Wen Chung - co-chair
Cheng-Wen Ko - advisor
indicate in-campus access in a year and off_campus not accessible|
|Date of Submission