Division of Neuroimaging Sciences, Brain Research Imaging Centre, Edinburgh University, UK.
Comput Math Methods Med. 2013;2013:283593. doi: 10.1155/2013/283593. Epub 2013 Jun 18.
The spatiotemporal evolution of stroke lesions, from acute injury to final tissue damage, is complex. Diffusion-weighted (DWI) and perfusion-weighted (PWI) imaging is commonly used to detect early ischemic changes and attempts to distinguish between permanently damaged and salvageable tissues. To date, 2D and 3D measures of diffusion/perfusion regions at individual timepoints have been widely used but may underestimate the true lesion spatio-temporal dynamics. Currently there is no spatio-temporal 4D dynamic model that simulates the continuous evolution of ischemic stroke from MR images. We determined whether a 4D current-based diffeomorphic model, developed in the field of statistical modeling for measuring the variability of anatomical surfaces, could estimate patient-specific spatio-temporal continuous evolution for MR PWI (measured as mean transit time, (MTT)) and DWI lesions. In our representative pilot sample, the model fitted the data well. Our dynamic analysis of lesion evolution showed different patterns; for example, some DWI/PWI dynamic changes corresponded with DWI lesion expansion into PWI lesions, but other patterns were much more complex and diverse. There was wide variation in the time when the final tissue damage was reached after stroke for DWI and MTT.
从急性损伤到最终组织损伤,中风病变的时空演变是复杂的。弥散加权(DWI)和灌注加权(PWI)成像常用于检测早期缺血性改变,并试图区分永久性损伤和可挽救的组织。迄今为止,在各个时间点对弥散/灌注区域的 2D 和 3D 测量已被广泛应用,但可能低估了真实病变的时空动态。目前,还没有模拟磁共振图像中缺血性中风连续演变的时空 4D 动态模型。我们确定了一种基于电流的 4D 仿射模型,该模型在用于测量解剖表面可变性的统计建模领域中得到了发展,是否可以估计特定于患者的磁共振灌注加权成像(测量为平均通过时间(MTT))和 DWI 病变的时空连续演变。在我们具有代表性的试点样本中,该模型很好地拟合了数据。我们对病变演变的动态分析显示出不同的模式;例如,一些 DWI/PWI 动态变化与 DWI 病变向 PWI 病变扩展相对应,但其他模式则更为复杂和多样化。在中风后到达最终组织损伤的时间上,DWI 和 MTT 存在很大差异。