A novel technique for modeling susceptibility-based contrast mechanisms for arbitrary microvascular geometries:: The finite perturber method
A novel technique for modeling susceptibility-based contrast mechanisms for arbitrary microvascular geometries:: The finite perturber method
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DOI：
10.1016/j.neuroimage.2008.01.022
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发表时间：
2008-04-15
期刊：
影响因子：
5.7
通讯作者：
Schmainda, Kathleen M.
中科院分区：
文献类型：
--
作者：
Pathak, Arvind P.;Ward, B. Douglas;Schmainda, Kathleen M.
最近，我们证明了血管的几何形状是磁共振成像（MRI）中磁敏感性诱导对比度的重要决定因素。这对于具有特征性异常血管形态的肿瘤的磁共振增强MRI尤其相关。为了更好地理解这种对比机制的生物物理学，对各种因素（包括微血管形态）如何对测量的MR信号做出贡献进行建模是有意义的，并且是开发称为有限微扰方法（FPM）的新型计算机建模方法的主要动机。FPM规避了传统的固定几何方法的局限性，使我们能够研究三维中任意微血管形态所产生的易变性诱导的对比度，例如通常观察到的脑肿瘤血管生成。在这里，我们描述这种新的建模方法和它的一些应用。FPM与理论和现存的磁化率建模数据的良好一致性，加上其计算效率，表明它有可能改变我们对MRI中产生磁化率对比的因素的理解。(C)2008年爱思唯尔公司All rights reserved.
Recently, we demonstrated that vessel geometry is a significant determinant of susceptibility-induced contrast in MRI. This is especially relevant for susceptibility-contrast enhanced MRI of tumors with their characteristically abnormal vessel morphology. In order to better understand the biophysics of this contrast mechanism, it is of interest to model how various factors, including microvessel morphology contribute to the measured MR signal, and was the primary motivation for developing a novel computer modeling approach called the Finite Perturber Method (FPM). The FPM circumvents the limitations of traditional fixed-geometry approaches, and enables us to study susceptibility-induced contrast arising from arbitrary microvascular morphologies in 3D, such as those typically observed with brain tumor angiogenesis. Here we describe this new modeling methodology and some of its applications. The excellent agreement of the FPM with theory and the extant susceptibility modeling data, coupled with its computational efficiency demonstrates its potential to transform our understanding of the factors that engender susceptibility contrast in MRI. (C) 2008 Elsevier Inc. All rights reserved.