Hypertrophic cardiomyopathy (HCM) causes sudden cardiac death (SCD) due to ventricular arrhythmias (VA) manifesting from myocardial fibrosis proliferation. Current clinical risk stratification criteria inadequately identify at-risk patients in need of primary prevention of VA. Here, we use mechanistic computational modeling of the heart to analyze how HCM-specific remodeling of the heart promotes arrhythmogenesis and to develop a personalized strategy to forecast risk of VAs in these patients. We combine contrast-enhanced cardiac magnetic-resonance (CMR) imaging and T1 mapping data to construct digital replicas of HCM patient hearts that represent the patient-specific distribution of focal and diffuse fibrosis and evaluate the substrate propensity to VA. Our analysis indicates that the presence of diffuse fibrosis, which is rarely assessed in these patients, increases arrhythmogenic propensity. In forecasting future VA events in HCM patients, the imaging-based computational heart approach achieved 84.6%, 76.9%, and 80.1% sensitivity, specificity, and accuracy, respectively, and significantly outperformed current clinical risk predictors. This novel VA risk assessment may have the potential to prevent SCD and help deploy primary prevention appropriately in HCM patients.

中文翻译：

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具有 T1 映射的纤维化重构的个性化计算心脏模型预测肥厚型心肌病患者猝死的风险

肥厚型心肌病 (HCM) 导致心源性猝死 (SCD)，原因是室性心律失常 (VA) 表现为心肌纤维化增殖。当前的临床风险分层标准未能充分识别需要 VA 一级预防的高危患者。在这里，我们使用心脏的机械计算模型来分析 HCM 特定的心脏重塑如何促进心律失常的发生，并制定个性化的策略来预测这些患者的 VA 风险。我们结合对比增强心脏磁共振 (CMR) 成像和 T1 映射数据来构建 HCM 患者心脏的数字复制品，代表局灶性和弥漫性纤维化的患者特定分布，并评估对 VA 的底物倾向。我们的分析表明存在弥漫性纤维化，这在这些患者中很少被评估，增加了致心律失常的倾向。在预测 HCM 患者未来 VA 事件时，基于成像的计算心脏方法分别实现了 84.6%、76.9% 和 80.1% 的灵敏度、特异性和准确性，并且显着优于当前的临床风险预测指标。这种新颖的 VA 风险评估可能有可能预防 SCD，并有助于在 HCM 患者中适当部署一级预防。