發(fā)布時(shí)間：2018-12-13 22:04

【摘要】：磁共振灌注成像是一種功能磁共振成像技術(shù),它可以反映組織的微血管分布和血流灌注情況,能夠提供解剖結(jié)構(gòu)、血管成像和組織功能狀態(tài)的多種血流動(dòng)力學(xué)方面的信息。在磁共振灌注成像動(dòng)力學(xué)參數(shù)中,平均渡越時(shí)間(MTT)對區(qū)分正常腦和缺血腦非常敏感,是診斷腦缺血疾病非常重要的參數(shù)。本論文首先對磁共振灌注成像技術(shù)的基本原理以及在腦部疾病和其他組織疾病中的應(yīng)用進(jìn)行了綜述。進(jìn)而,對MRI腦血灌注成像的基本原理進(jìn)行公式推導(dǎo),得出通過去卷積估算平均渡越時(shí)間的方法,并對其理想的動(dòng)力函數(shù)進(jìn)行了仿真模擬。而直接去卷積方法計(jì)算量比較大且繁瑣,因此本文采用了基于加權(quán)廣義交叉驗(yàn)證(W-GCV)的Tikhonov正則化法、總體最小二乘正則化法和修正截?cái)嗥娈愔嫡齽t化法進(jìn)行去卷積,對平均渡越時(shí)間求解,并對駐留函數(shù)進(jìn)行仿真分析。以及對三種正則化法的抗噪性能進(jìn)行評估和受到示蹤劑延遲的影響進(jìn)行分析討論,結(jié)果表明,隨著信噪比的增大,信噪比對三種正則化的估算結(jié)果影響逐漸減小�；赪-GCV的Tikhonov正則化方法所得平均渡越時(shí)間與參考值更接近,偏差程度最小;隨著示蹤劑延遲的增加,三種正則化方法估算出的平均渡越時(shí)間也在增加,且增加的值小于延遲的時(shí)間。最后,利用基于W-GCV的Tikhonov正則化方法對真實(shí)腦灌注圖像進(jìn)行了動(dòng)力參數(shù)偽彩圖成像,并選取正則化方法所得的估計(jì)結(jié)果,結(jié)合腦血流量(CBF)偽彩圖,分析了大腦感興趣區(qū)域的缺血情況。結(jié)果表明,患側(cè)與健側(cè)的平均渡越時(shí)間比值大于1.63,說明大腦處于缺血狀態(tài)。且從腦血流量偽彩圖可以得出患側(cè)的CBF值在20~35ml/min之間,提示N蛋白合成停止,若血量不繼續(xù)下降腦組織仍然存活。以上結(jié)果可為腦缺血的臨床診斷提供依據(jù)。
[Abstract]:Magnetic resonance perfusion imaging is a kind of functional magnetic resonance imaging technology, which can reflect the microvascular distribution and blood perfusion of tissues, and can provide various hemodynamic information of anatomical structure, vascular imaging and tissue functional state. Among the dynamic parameters of magnetic resonance perfusion imaging, the mean transit time (MTT) is very sensitive to differentiating the normal brain from the ischemic brain, and it is an important parameter in the diagnosis of cerebral ischemic diseases. In this paper, the basic principle of magnetic resonance perfusion imaging and its application in brain and other tissue diseases are reviewed. Then, the basic principle of MRI cerebral blood perfusion imaging is deduced, and the method of estimating the average transit time by deconvolution is obtained, and its ideal dynamic function is simulated. However, the direct deconvolution method is more complicated and complicated, so the Tikhonov regularization method based on weighted generalized cross validation (W-GCV), the total least square regularization method and the modified truncated singular value regularization method are used to deconvolution. The average transit time is solved and the resident function is simulated. The anti-noise performance of the three regularization methods is evaluated and the influence of tracer delay on the performance of the three regularization methods is analyzed and discussed. The results show that with the increase of SNR the influence of SNR on the estimation of the three regularization results decreases gradually. The average transit time obtained by Tikhonov regularization method based on W-GCV is closer to the reference value and the deviation is minimum. With the increase of tracer delay, the average transit time estimated by the three regularization methods is also increasing, and the increase is less than the delay time. Finally, the real cerebral perfusion image is imaged by Tikhonov regularization method based on W-GCV, and the estimated results of the regularization method are selected, combined with the (CBF) pseudocolor image of cerebral blood flow. Ischemia in the region of interest to the brain was analyzed. The results showed that the average transit time ratio between the affected side and the healthy side was greater than 1.63, indicating that the brain was in ischemic state. Moreover, the CBF value of the affected side was between 20~35ml/min and the pseudo-color map of cerebral blood flow, suggesting that the synthesis of N protein was stopped, and if the blood volume did not continue to decline, the brain tissue still survived. The above results may provide the basis for the clinical diagnosis of cerebral ischemia.
【學(xué)位授予單位】：河北工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TP391.41;R445.2

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