臺灣博碩士論文加值系統

血流灌注磁振影像的血液動力參數包含相對腦血流體積(rCBV)、相對腦血流流量(rCBF)以及平均穿流時間(MTT)。rCBF和MTT可以藉由動脈輸入函數(Arterial input function)做捲積(convolution)來得到。然而藉由奇異值分解法(SVD)所得到的rCBF對於對比劑的延遲效應非常敏感，而這個現象會發生在有大腦血管有病變的地方。
我們模擬對比劑延遲效應對於SVD計算rCBF所造成的影響。模擬研究顯示在對比劑延遲的情況下，較短的MTT會造成rCBF有較大的低估，而這也會造成MTT高估。因此，可以透過曲線擬合找到延遲時間，把延遲的組織濃度時間曲線做時間平移，平移到和動脈輸入函數的濃度時間曲線同時到達，再經由SVD計算所得到的rCBF會比修正前來的準確。然而利用SVD所得到的rCBF主要和閥值有關，閥值的選取是經由模擬實驗得到，而每一個人的生理條件不同，所以模擬實驗所選取的條件並沒辦法符合每一個人，而rCBF的不準確會間接影響到MTT。
這裡我們提供了一個不用透過閥值，就可以直接同步計算出rCBF和MTT的方法，這個方法首先需假設殘餘函數(Residual function)是指數衰減型，接著透過曲線擬合找到延遲時間，把延遲的組織濃度時間曲線做時間平移，平移到和動脈輸入函數的濃度時間曲線同時到達，接著再經由最小平方差的曲線擬合來得到rCBF、MTT。模擬結果顯示，利用曲線擬合找到的rCBF及MTT，比SVD方法來的準確。我們利用三種計算血液動力參數的方法:(1)直接以SVD計算;(2)經過延遲校正後，再以SVD計算；(3)經過延遲校正後，以曲線擬合計算。分析了一位健康受試者和二位病人的rCBF、MTT和rCBV影像，最後再藉由二維散佈圖(scatter plot)比較影像的結果。

Hemodynamic parameters such as relative cerebral volume (rCBV), relative cerebral blood flow (rCBF), and mean transit time (MTT) are assessed using dynamic susceptibility contrast MRI (DSC-MRI). The rCBF and MTT can be determined by deconvolution with an arterial input function(AIF). However, the singular value decomposition (SVD) deconvolution method is sensitive to the tracer delay that it often occurs in patients with cerebrovascular disease.
We investigated the effect of tracer delay on rCBF determined by SVD deconvolution. Simulation study showed that shorter MTT will cause larger underestimation of rCBF and overestimation of MTT in tracer delay. Delay correction methods were developed to find tracer arrival delay between the AIF and concentration time curve, and concentration time curve was shifted to coincide with that of the AIF. The simulations showed that the corrected rCBF was more accurate than uncorrected one. However, rCBF was depended on threshold by SVD, threshold was found by simulation. Since everyone had different physics condition, therefore simulation condition was not fit to everyone. However, rCBF inaccuracy will affect MTT indirectly.
We proposed a method that did not depend on threshold, and rCBF and MTT can calculated directly. At first, we assumed residual function equaled exponential decay. A curve fitting technique was used to find tracer arrival delay between the AIF and concentration time curve, and concentration time curve was shifted to coincide with that of the AIF. Finally, rCBF and MTT were determined using curve fitting. The simulations showed that the rCBF and MTT obtained from curve fitting was more accurate than the two SVD methods. We applied three methods of calculating the rCBF, MTT, and rCBV images for one normal volunteer and two patients. Finally, we analysis the results of images by scatter plot.

摘要 2
ABSTRACT 4
目錄 6
1.緒論 7
2.理論 10
2.1奇異值分解(SVD) 11
2.2 利用積分長時間窗口來計算rCBV 13
2.3修正延遲效應 14
2.4利用least-squares curve fitting找到rCBV、rCBF、MTT 15
3.電腦模擬流程: 16
3.1 首先是模擬動脈輸入函數(AIF)： 17
3.2 模擬組織對比劑濃度(Ct(t)): 18
3.3 模擬延遲效應: 22
4.臨床影像分析 23
4.1受試者 23
4.2影像擷取 23
4.3影像後處理 24
5.結果 26
5.1.1 電腦模擬-修正延遲效應 26
5.1.2 電腦模擬-相對腦血流流量 27
5.1.3 電腦模擬-平均穿流時間 30
5.1.4 電腦模擬-相對腦血流體積 34
5.2.1 臨床影像分析-延遲時間圖譜 38
5.2.2 臨床影像分析-相對腦血流流量 39
5.2.3臨床影像分析-平均穿流時間 40
5.2.3臨床影像分析-平均穿流時間 41
5.2.4 臨床影像分析-相對腦血流體積 43
6.討論與結論 44
6.1 電腦模擬結果 44
6.2.1臨床影像分析-相對腦血流流量 46
6.2.2臨床影像分析-平均穿流時間 46
6.2.3臨床影像分析-相對腦血流體積 47
6.3 結論 48
參考文獻 49
附錄.大腦血流動力和自體調節 53

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