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標題: | 以虛擬滴定評估功能性磁振頻譜之靈敏度與穩定度 Evaluation of Sensitivity and Reliability of Functional MR Spectroscopy Using Virtual Titration |
作者: | Chun-Jen Huang 黃俊仁 |
指導教授: | 鍾孝文 |
關鍵字: | 功能性磁振頻譜,定量靈敏度與穩定度,線性疊加模型, functional MRS,quantification sensitivity and reliability,LCModel, |
出版年 : | 2009 |
學位: | 碩士 |
摘要: | 核磁共振頻譜可以非侵入式的方式提供人體內化學物質的資訊。將它和功能性磁振造影的觀念結合後,功能性磁振頻譜已經成為研究神經生理學時一項有力的工具。然而,已有報告指出譜線的特性會受到血氧程度相關效應的影響,而這對於代謝物濃度定量所造成的影響尚未被完整地評估。但在功能性詞振頻譜的研究中,研究者感興趣的就是濃度的微小改變,因此這個影響可能是很關鍵性的。在這個研究中,我們模擬了13個頻譜裡肌酸、膽鹼與N-acetyl-L-aspartic acid的微小濃度改變,以評估線性疊加模型軟體(一個磁振頻譜定量軟體)的靈敏度與穩定度。此外,我們模擬了可能因為血氧程度相關效應所造成的線寬改變,以檢驗定量結果是否會受到影響。我們的結果顯示,三種代謝物在濃度改變超過±0.8%即可被偵測到,但對於肌酸和膽鹼,真實的濃度改變可能會被高估。此外,在高信雜比的條件下,線寬造成三種代謝物一致的濃度改變,但在有雜訊的情況下,各頻譜間的濃度改變有很大的差異。我們的結論是,線性疊加模型軟體對於微小的濃度改變敏感,但需要發展一個校正的流程以消除偽濃度改變量。 Magnetic resonance spectroscopy (MRS) can be used to provide chemical information within human body noninvasively. Combining it with the concept of functional magnetic resonance in imaging (fMRI), functional magnetic resonance spectroscopy (fMRS) has become a powerful tool to investigate neural physiology. However, it has been reported that spectral line properties can be affect by blood-oxygenation-level-dependent (BOLD) effect, and the resultant impact on metabolite quantification has not yet been thoroughly evaluated. But this impact could be critical since in fMRS studies, the tiny changes of the concentrations are of interest. In this study, we simulated tiny concentration changes of creatine, choline, and N-acetyl-L-aspartic acid of 13 spectra to evaluate the sensitivity and reliability of LCModel (MRS quantification software). In addition, we simulated linewidth alterations that could result from BOLD effect, to examine whether the quantification result will be affected or not. Our result shows that concentration changes exceeding ±0.8% could be detectable for the three metabolites, but the actual concentration change may be over-estimated when quantifying creatine and choline. Besides, linewidth alterations result in consistent concentration changes for the three metabolites under the condition of high SNR. But in the presence of noise, results of concentration changes shows large variations among spectra. We conclude that LCModel is sensitive to tiny concentration changes, but it would be necessary to develop a calibration procedure to eliminate pseudo concentration changes. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/43963 |
全文授權: | 有償授權 |
顯示於系所單位: | 生醫電子與資訊學研究所 |
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