Mut Fernando, Wright Susan, Ascoli Giorgio A, Cebral Juan R
Center for Computational Fluid Dynamics, College of Sciences, George Mason University, 4400 University Drive, MSN 3F3 Fairfax, Virginia 22030, USA.
Int J Numer Method Biomed Eng. 2014 Jul;30(7):755-66. doi: 10.1002/cnm.2627. Epub 2014 Jan 27.
Morphometric information of the brain vascularization is valuable for a variety of clinical and scientific applications. In particular, this information is important when creating arterial tree models for imposing boundary conditions in numerical simulations of the brain hemodynamics. The purpose of this work is to provide quantitative descriptions of arterial branches, bifurcation patterns, shape, and geographical distribution of the arborization of the main cerebral arteries as well as estimations of the corresponding vascular territories. For this purpose, subject-specific digital reconstructions of the brain vascular network created from 3T magnetic resonance angiography images of healthy volunteers are used to derive population-averaged morphometric characteristics of the cerebral arterial trees. Copyri
脑血管形成的形态测量信息对于各种临床和科学应用都很有价值。特别是，在创建动脉树模型以在脑血流动力学的数值模拟中施加边界条件时，这些信息非常重要。这项工作的目的是提供对大脑主要动脉分支、分叉模式、形状和分支的地理分布的定量描述，以及对相应血管区域的估计。为此，利用从健康志愿者的3T磁共振血管造影图像创建的特定受试者脑血管网络数字重建，来推导脑动脉树的总体平均形态测量特征。版权所有
