重水微灌流之自動選擇及分離式動脈輸入函數

重水因具有高滲透性且幾乎不帶有毒性的性質，早期作為對比劑應用於微灌流磁振造影技術中，但是受限於磁振造影偵測靈敏度的限制，使氘影像無法提供足夠的信雜比，然而在之前研究中利用收氫原子訊號間接量測重水造成的訊號衰減，成功地獲得高空間解析度的微灌流影像。為了得到準確的量化結果我們必須先有可靠的動脈輸入函數，因此在本實驗中，我們試著建立了一套以K-means演算法自動選擇動脈輸入函數的方式，克服手動選擇所造成的人為偏差，得到一條更客觀的動脈輸入函數曲線，並將這條動脈輸入函數擬合雙指數衰減模型。從實驗結果發現我們所選出來的動脈輸入函數曲線前段雖然符合動脈的特性，然而後段卻有一段高濃度的殘留，因此從雙指數衰減中取出快的衰減作為單指數衰減的動脈輸入函數，並利用曲線擬合和奇異值分解的方式量化出微灌流的資訊，而由線性擬合的結果發現雙室模型較能夠描述重水於大腦內灌流的特性，且搭配單指數衰減的動脈輸入函數捲積回去的結果與量測曲線有最小的均方根誤差，而在奇異值分解也有同樣的結果，推測原因為單指數的動脈輸入函數形狀較類似訊號與系統中的單位脈衝函數，因此我們可以得到更真實的組織特性。此技術改善了手動選擇的缺點且方便臨床診斷使用，提供更高準確的微灌流資訊。

關鍵字

氧化氘；磁振造影對比劑；動脈輸入函數； K-means演算法

並列摘要

Deuterium oxide (D2O) had been used as contrast agent in early perfusion MRI due to its diffusibility and nontoxicity. However, the detection of D2O in MRI is limited to its sensitivity and the signal-to-noise ratio of perfusion image is low. Recently, a novel contrast-enhanced strategy has been proposed to address this issue. D2O is indirectly detected by monitoring the signal change of 1H signal after D2O administration. In order to quantify the cerebral blood flow precisely, a reliable arterial input function (AIF) is essential. Thus we aim to develop an automatic process in AIF selection to avoid the bias from manual selection. K-means cluster analysis was used to determine the most suitable AIF of D2O perfusion in mice experiments. The selected AIF time curve was then fitted using bi-exponential model to obtain a derived AIF [19-20]. However, we found that the wash out part of the derived AIF has a high concentration level. As a result, we extracted the fast rate constant from the bi-exponential model to generate a novel AIF with mono-exponential decay and compared their fitting performances. The AIF was then used to calculate the perfusion parameters by both model-dependent and model-free method. Our result shows that two-compartment model with fast-exponential AIF could describe the D2O perfusion properly. A similar result can be found in the analysis by SVD method. This could be reasonable since the shape of fast-exponential AIF is similar to unit impulse response (delta function). The deconvolution process with fast-exponential AIF can bring to a more accurate tissue residual function. In summary, our method has improved the selection process and also provides more accurate perfusion information.

並列關鍵字

D2O ； MRI contrast agent ； Arterial input function ； K-means algorithm

參考文獻

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2. Wu, O., et al., Predicting tissue outcome in acute human cerebral ischemia using combined diffusion- and perfusion-weighted MR imaging. Stroke, 2001. 32(4): p. 933-942.

3. Bernstein, E.J., C. Schmidt-Lauber, and J. Kay, Nephrogenic systemic fibrosis: A systemic fibrosing disease resulting from gadolinium exposure. Best Practice & Research in Clinical Rheumatology, 2012. 26(4): p. 489-503.

4. Ackerman, J.J., et al., Deuterium nuclear magnetic resonance measurements of blood flow and tissue perfusion employing 2H2O as a freely diffusible tracer. Proc Natl Acad Sci U S A, 1987. 84(12): p. 4099-102.

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重水微灌流之自動選擇及分離式動脈輸入函數

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