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博碩士論文 etd-0723110-175516 詳細資訊
Title page for etd-0723110-175516
論文名稱
Title
使用GAMMA模擬針對氫質子磁振頻譜之丙氨酸、乳酸與脂質的定量分析
Quantitative Analysis of Alanine, Lactate and Lipid Using Proton MR Spectroscopy with GAMMA Simulation
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
76
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2010-06-28
繳交日期
Date of Submission
2010-07-23
關鍵字
Keywords
磁振頻譜、LCModel、定量分析、丙氨酸、乳酸、脂質
lipid, alanine, magnetic resonance spectroscopy, quantitative analysis, LCModel, lactate
統計
Statistics
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中文摘要
將腦濃瘍從其它腦部的疾病(例如:神經膠質瘤)中區分出來,對於臨床上的診斷與治療是相當重要的。而氨基酸、丙氨酸、琥珀酸鹽和醋酸鹽,這些代謝物是被認定為腦濃瘍病患的腦中會出現的指標性代謝物,此外LCModel是一個眾所周知用來分析磁振頻譜的工具,它亦提供了對這些指標性代謝物作濃度定量分析的機會,因此利用LCModel去分析這些指標性代謝物的磁振頻譜,並進一步對它們作辨識與濃度定量,那將會對臨床上患有腦濃瘍的病患帶來更準確且非侵入性的診斷與治療。
然而部份代謝物彼此之間因為重疊而造成了區分上的困難,是目前相當困擾的問題,在這次實驗中我們想要驗證LCModel在分析這些重疊代謝物的可靠性,於是利用一些GAVA模擬出來的訊號讓LCModel分析,藉此了解各種變數對其分析重疊訊號時的影響。我們最終的目的是討論出可能的較佳、較可靠分析方法,希望對臨床上腦濃瘍病患的診斷有所幫助。從我們的實驗結果顯示,在用LCModel分析丙氨酸,乳酸和脂質這些互相重疊的代謝物時,可能會因使用不同的Basis set分析而造成定量上的結果有所不同,所以在使用LCModel去分析臨床病患的這些代謝物時,對於basis set應審慎選擇。
Abstract
To differentiate pyogenic brain abscess from other brain diseases such as necrotic glioblastomas is very important for clinic treatment. Cytosolic animo acids, lactate, alanine, succinate and acetate have been recognized as potential abscess markers. LCModel is a well-known tool to analyze the MRS data, as it provides opportunity of quantitative of metabolite concentration. Using MRS with LCModel to identify and quantitate these metabolites would benefit more precisely noninvasive diagnosis and treatment of pyogenic brain abscess.
However, to differentiate the MR spectra of strongly overlapping metabolites are not easy. In this study, we validate the accuracy of LCModel on detecting these overlapping metabolites. We use some GAVA-simulated resonance spectra as our input signals and figure out the performance of LCModel analysis in different conditions. Our goal is to find an optimal analysis method to help the clinic diagnosis of abscess patients. Our result shows that the determination of basis sets is very important since the analyzed result might be different due to the improper selection of basis sets.
目次 Table of Contents
Chapter 1 Introduction 1
1.1 Background 1
1.2 Literature review 2
1.3 Motivation 5
Chapter 2 Materials and Methods 7
2.1 GAMMA and GAVA 7
2.2 LCModel 8
2.3 Experiment Design 8
2.3.1 Simulated MR Spectroscopy (MRS) Signals 9
2.3.2 Analysis Parameters of LCModel 11
2.3.3 Error evaluation 12
Chapter 3 Results 26
3.1 Lactate v.s. Alanine 26
3.2 Lactate v.s. Lipid 31
3.2.1 The results of relative concentration ratios of metabolites 31
3.2.2 The results of peak area ratios of metabolites 33
Chapter 4 Discussion 50
4.1 Lactate v.s. Alanine 50
4.2 Lactate v.s Lipid 53
Chapter 5 Conclusion 64
Reference 66


參考文獻 References
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