GABA (γ-aminobutyric acid) 是一種胺基酸神經傳遞物質，在中樞神經系統中扮演非常重要的角色。GABA的濃度變化被認為與一些神經系統疾病有關聯，例如:癲癇(Epilepsy)、阿茲海默症(Alzheimer's disease)。磁共振頻譜是一個能夠量測體內代謝物濃度的工具，最常使用的脈衝序列為PRESS (Point-RESolved Spectroscopy sequence)。然而，GABA的訊號容易被其他代謝物的訊號遮蔽，PRESS脈衝序列在臨床上的實驗中無法提供足夠高的解析度，為了能夠得到GABA的訊號，近年來，漸漸使用MEGA-PRESS脈衝序列來取代PRESS脈衝序列在GABA的偵測實驗上。

MEGA-PRESS頻譜編輯技術主要是於原本的PRESS脈衝序列增加兩個選擇性180度射頻脈衝，藉由兩個選擇性射頻脈衝來調配具有J-耦合特性之代謝物的訊號，透過頻譜相減消除不具有J-耦合特性或是沒有被編輯到的代謝物訊號，觀察出具有J-耦合特性之代謝物的頻譜變化。我們的結果顯示，在一般常用的3T磁場下，此方法能有效取得具有J-耦合特性之代謝物的訊號，如：GABA、Lactate與Valine 。

關鍵字：磁共振頻譜、頻譜編輯、耦合系統、MEGA-PRESS、VeSPA

GABA (γ-aminobutyric acid) is one of amino acid neurotransmitter which plays an important role in the central nervous system (CNS). A change in GABA concentration is considered to be associated with some neurological disorders, such as: Epilepsy, Alzheimer's disease. Magnetic resonance spectroscopy is a tool that enables measurement of metabolic concentrations in vivo. One of the most commonly employed pulse sequences is PRESS (Point-RESolved Spectroscopy sequence). However, the signal of GABA is easily obstructed by signals of other metabolites. PRESS does not provide sufficiently high resolution in the clinical experiments. In recent years, in order to obtain signal from GABA, MEGA-PRESS has become popular in the detection of GABA.

MEGA-PRESS spectral editing technique is based on the original PRESS sequence along with two frequency-selective 〖180〗^° pulses to blend the signal of J-coupled metabolites. These edited J-coupled resonances can be enhanced by spectral subtraction removing non J-coupled resonances. Our results show that under conventional 3T magnetic field, MEGA-PRESS can be applied to detect signals of J-coupled metabolites, such as GABA, Lactate and Valine.

Key words: MRS, spectrum editing, coupled spin systems, MEGA-PRESS, VeSPA

致謝 i
摘要 ii
Abstract iii
目錄 iv
圖目錄 vi
表目錄 vii
第一章 簡介 1
1.1 背景 1
1.2 文獻回顧 1
1.3 研究動機 6
1.4 組織架構 6
第二章 原理 7
2.1 磁共振頻譜 7
2.2 人體大腦中常見具有J-耦合特性的代謝物 9
2.3 化學位移 15
2.4 J-耦合 17
2.5 MEGA-PRESS頻譜編輯 19
第三章 實驗方法設計與步驟 25
3.1 VeSPA 25
3.2 模擬與實驗的數值設計 32
3.2.1 VeSPA模擬參數設定 23
3.2.2 假體配方與正常人類大腦掃描參數設定 36
第四章 結果 40
4.1 VeSPA模擬分析結果 40
4.2 假體實驗分析結果 44
4.3 正常人類大腦分析結果 47
第五章 討論與結論 49
5.1 討論 49
5.2 結論 50
參考文獻 56

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