Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland; Alliance for Cardiovascular Diagnostic and Treatment Innovation, Whiting School of Engineering and School of Medicine, Johns Hopkins University, Baltimore, Maryland.
Division of Pediatric Cardiology, Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Heart Rhythm. 2020 Mar;17(3):408-414. doi: 10.1016/j.hrthm.2019.10.002. Epub 2019 Oct 4.
Adults with repaired tetralogy of Fallot (rTOF) are at increased risk for ventricular tachycardia (VT) due to fibrotic remodeling of the myocardium. However, the current clinical guidelines for VT risk stratification and subsequent implantable cardioverter-defibrillator deployment for primary prevention of sudden cardiac death in rTOF remain inadequate.
The purpose of this study was to determine the feasibility of using an rTOF-specific virtual-heart approach to identify patients stratified incorrectly as being at low VT risk by current clinical criteria.
This multicenter retrospective pilot study included 7 adult rTOF patients who were considered low risk for VT based on clinical criteria. Patient-specific computational heart models were generated from late gadolinium enhanced magnetic resonance imaging (LGE-MRI), incorporating the individual distribution of rTOF fibrotic remodeling in both ventricles. Simulations of rapid pacing determined VT inducibility. Model creation and simulations were performed by operators blinded to clinical outcome.
Two patients in the study experienced clinical VT. The virtual hearts constructed from LGE-MRI scans of 7 rTOF patients correctly predicted reentrant VT in the models from VT-positive patients and no arrhythmia in those from VT-negative patients. There were no statistically significant differences in clinical criteria commonly used to assess VT risk, including QRS duration and age, between patients who did and those who did not experience clinical VT.
This study demonstrates the feasibility of image-based virtual-heart modeling in patients with congenital heart disease and structurally abnormal hearts. It highlights the potential of the methodology to improve VT risk stratification in patients with rTOF.
修复后的法洛四联症（rTOF）患者由于心肌纤维化重塑，患室性心动过速（VT）的风险增加。然而，目前用于 rTOF 患者 VT 风险分层和随后植入式心脏复律除颤器（ICD）预防心源性猝死的临床指南仍然不足。
本研究旨在确定使用 rTOF 特异性虚拟心脏方法识别当前临床标准错误地分层为低 VT 风险的患者的可行性。
这项多中心回顾性试点研究纳入了 7 名基于临床标准被认为 VT 风险低的成年 rTOF 患者。通过对钆延迟增强磁共振成像（LGE-MRI）进行个体化分析，生成患者特异性计算心脏模型，同时考虑到左右心室的 rTOF 纤维化重塑的分布情况。快速起搏模拟确定 VT 的诱发性。模型创建和模拟由对临床结果不知情的操作人员进行。
研究中有 2 名患者经历了临床 VT。从 7 名 rTOF 患者的 LGE-MRI 扫描构建的虚拟心脏正确预测了来自 VT 阳性患者模型中的折返性 VT，以及来自 VT 阴性患者模型中的无心律失常。在经历临床 VT 和未经历临床 VT 的患者之间，通常用于评估 VT 风险的临床标准，包括 QRS 持续时间和年龄，没有统计学上的显著差异。
本研究证明了基于图像的虚拟心脏建模在先天性心脏病和结构异常心脏患者中的可行性。它突出了该方法在 rTOF 患者 VT 风险分层中的潜在应用价值。
