氧化氘(重水)早期被視為一高通透性的對比劑並應用於微灌流磁振造影技術中。但是受限於氘磁振造影的靈敏度，氘影像無法提供足夠的信雜比。近期的研究利用收取氫原子訊號的方式來間接偵測由重水所衰減訊號的微灌流磁振造影。其優異的信雜比提供了高空間解析度的成像。我們希望能夠藉由此技術，更進一步的去分析重水於生物體內的局部分布情形並且利用數學模型去描述其特性。在本實驗中，我們試著利用單室與雙室數學模型來描述大鼠腦中重水微灌流的特性。並對於所計算出的動力學參數進行分析。從實驗結果我們發現雙室模型較能夠描述重水於大腦內為灌流的特性，但是較容易受雜訊影響。我們根據不同的重水流出速率可以將不同的組織進行分類。其中，我們將流出速度為中等且占據大部分體積的貢獻視為腦血流。跟其他文獻相比本實驗所算出的血流數值在合理範圍內，且具有良好的灰白質對比。其餘部分則是可能包含著重水均勻分散至體內或是腎臟代謝水分以及腦脊髓液循環等訊息。但因受限於時間解析度以及訊號偏移難以將這些資訊分離出。未來進行影像參數上的改善後，此技術將可應用於臨床血液流速分析以及腦神經病變的研究。

In early perfusion MRI studies, D2O had been used as a high diffusible tracer. It was verified that D2O can be applied as an effective contrast agent. Due to the limitation of theoretical sensitivity on deuterium images, the signal to noise ratio (SNR) is too low to acquire distinctly anatomical details. In recent study, a new strategy for detecting D2O by monitoring the attenuation of 1H signal has been suggested. By using this new strategy, we further research the microcirculation of D2O and establish a kinetic model. In this study, one and two compartments models were proposed to depict the dynamics of D2O in rat brain. The kinetic parameters were derived from compartmental models by de-convolution. It is showed that the two compartments model could give a more accurate but less precise in the estimation of physiological parameters. Based on the efflux characteristic, brain tissue could be separated into three portions. The main portion of the derived efflux constant is referred as CBF, where the GM and WM can be differentiated successfully on the CBF map. The other portions may imply the process that D2O distributes into normal water or the secretion of cerebrospinal fluid. Improving the temporal resolution and avoiding the signal drift are essential work in following studies to recognize dynamics of D2O.

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