腦血流灌注影像在腦功能疾病的模型定量及研究

Abstract

在這篇論文裡面，我們將臨床拿到的血流灌注影像訊號與第一時間的血液動力學模型互相結合，並且嘗試將之應用在腦腫瘤和缺血性中風的病人身上，來研究該模型在臨床診斷上的可行性。我們先用蒙地卡羅的方式評估這個模型的準確性和重複價值，確定它的某個重要參數Ktrans受制於影像品質的好壞。儘管如此，我們發現，若是血流灌注影像的品質在可接受範圍內，可以精準算出腫瘤與中風區域的生理參數，尤其是後者，我們發現這個技術應用在急性中風的病人身上，有多數例子都可以在T1對比剤影像顯影之前而能更早預測最後中風的區域以及血腦屏障遭受破壞的範圍大小，這是前人所沒有做過的。

We employed the tracer kinetic model based on the T2* perfusion in the study to improve MR imaging analysis by adding noteworthy information of BBB permeability in brain tumors and ischemic strokes. We examined the accuracy and precision of estimated pharmacokinetic parameters, using the values of Monte Carlo simulations to better understand the origin of error distribution in fitting process. The FPPM model offers a potentially advantageous approach for simultaneous generation of the estimates of permeability and cerebral blood volume from dynamic T2*-weighted echo-planar images. This model accurately reflected the underlying cerebral pathophysiology in patient with brain tumors and ischemic stroke from observations with calculated maps of clinical practice in this study. We have applied the patients’ data in our institute to confirm that the FPPM model could be an effective means of detecting brain damage in patients with ischemic stroke at the onset of first few days in this study. These data suggest that only at the chronic phase can a leakage of contrast medium lead to a parenchymal enhancement such that brain blood barrier (BBB) disruption is severe enough to be monitored in contrast-enhanced T1-weighted images, while the abnormal permeability performance can already be clearly found with a higher sensitivity to the hemodynamic changes of lesion areas at the acute stage for these patients.