Ringenberg Jordan, Deo Makarand, Filgueiras-Rama David, Pizarro Gonzalo, Ibañez Borja, Peinado Rafael, Merino José L, Berenfeld Omer, Devabhaktuni Vijay
EECS Department, College of Engineering, University of Toledo, Toledo, OH, USA.
Department of Engineering, Norfolk State University, Norfolk, VA, USA.
Clin Med Insights Cardiol. 2014 Sep 25;8(Suppl 1):1-13. doi: 10.4137/CMC.S15712. eCollection 2014.
Myocardial fibrosis detected via delayed-enhanced magnetic resonance imaging (MRI) has been shown to be a strong indicator for ventricular tachycardia (VT) inducibility. However, little is known regarding how inducibility is affected by the details of the fibrosis extent, morphology, and border zone configuration. The objective of this article is to systematically study the arrhythmogenic effects of fibrosis geometry and extent, specifically on VT inducibility and maintenance. We present a set of methods for constructing patient-specific computational models of human ventricles using in vivo MRI data for patients suffering from hypertension, hypercholesterolemia, and chronic myocardial infarction. Additional synthesized models with morphologically varied extents of fibrosis and gray zone (GZ) distribution were derived to study the alterations in the arrhythmia induction and reentry patterns. Detailed electrophysiological simulations demonstrated that (1) VT morphology was highly dependent on the extent of fibrosis, which acts as a structural substrate, (2) reentry tended to be anchored to the fibrosis edges and showed transmural conduction of activations through narrow channels formed within fibrosis, and (3) increasing the extent of GZ within fibrosis tended to destabilize the structural reentry sites and aggravate the VT as compared to fibrotic regions of the same size and shape but with lower or no GZ. The approach and findings represent a significant step toward patient-specific cardiac modeling as a reliable tool for VT prediction and management of the patient. Sensitivities to approximation nuances in the modeling of structural pathology by image-based reconstruction techniques are also implicated.
通过延迟增强磁共振成像(MRI)检测到的心肌纤维化已被证明是室性心动过速(VT)诱发的有力指标。然而,关于纤维化程度、形态和边界区配置的细节如何影响诱发情况,人们知之甚少。本文的目的是系统地研究纤维化几何形状和程度的致心律失常作用,特别是对VT诱发和维持的影响。我们提出了一套使用体内MRI数据构建高血压、高胆固醇血症和慢性心肌梗死患者的人体心室特定计算模型的方法。还推导了具有形态学上不同纤维化程度和灰色区域(GZ)分布的额外合成模型,以研究心律失常诱发和折返模式的改变。详细的电生理模拟表明:(1)VT形态高度依赖于作为结构基质的纤维化程度;(2)折返倾向于锚定在纤维化边缘,并显示激活通过纤维化内形成的狭窄通道进行透壁传导;(3)与相同大小和形状但GZ较低或没有GZ的纤维化区域相比,纤维化内GZ范围的增加倾向于使结构折返部位不稳定并加重VT。该方法和研究结果代表了朝着将特定患者心脏建模作为VT预测和患者管理的可靠工具迈出的重要一步。还涉及基于图像的重建技术在结构病理学建模中对近似细微差别的敏感性。