From the Departments of Cardiology (Y.L., Y.X., W.L., J.G., J.W., Z.X., Y.C.), Geriatrics (K.W.), and Radiology (J.S.), West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, China; and Wexner Medical Center, College of Medicine, The Ohio State University, Columbus, Ohio (Y.H.).
Radiology. 2023 May;307(3):e222552. doi: 10.1148/radiol.222552. Epub 2023 Mar 14.
Background Sudden cardiac death (SCD) is one of the leading causes of death in individuals with nonischemic dilated cardiomyopathy (DCM). However, the risk stratification of SCD events remains challenging in clinical practice. Purpose To determine whether myocardial tissue characterization with cardiac MRI could be used to predict SCD events and to explore a SCD stratification algorithm in nonischemic DCM. Materials and Methods In this prospective single-center study, adults with nonischemic DCM who underwent cardiac MRI between June 2012 and August 2020 were enrolled. SCD-related events included SCD, appropriate implantable cardioverter-defibrillator shock, and resuscitation after cardiac arrest. Competing risk regression analysis and Kaplan-Meier analysis were performed to identify the association of myocardial tissue characterization with outcomes. Results Among the 858 participants (mean age, 48 years; age range, 18-83 years; 603 men), 70 (8%) participants experienced SCD-related events during a median follow-up of 33.0 months. In multivariable competing risk analysis, late gadolinium enhancement (LGE) (hazard ratio [HR], 1.87; 95% CI: 1.07, 3.27; = .03), native T1 (per 10-msec increase: HR, 1.07; 95% CI: 1.04, 1.11; < .001), and extracellular volume fraction (per 3% increase: HR, 1.26; 95% CI: 1.11, 1.44; < .001) were independent predictors of SCD-related events after adjustment of systolic blood pressure, atrial fibrillation, and left ventricular ejection fraction. An SCD risk stratification category was developed with a combination of native T1 and LGE. Participants with a native T1 value 4 or more SDs above the mean (1382 msec) had the highest annual SCD-related events rate of 9.3%, and participants with a native T1 value 2 SDs below the mean (1292 msec) and negative LGE had the lowest rate of 0.6%. This category showed good prediction ability (C statistic = 0.74) and could be used to discriminate SCD risk and competing heart failure risk. Conclusion Myocardial tissue characteristics derived from cardiac MRI were independent predictors of sudden cardiac death (SCD)-related events in individuals with nonischemic dilated cardiomyopathy and could be used to stratify participants according to different SCD risk categories. Clinical trial registration no. ChiCTR1800017058 © RSNA, 2023 See also the editorial by Sakuma in this issue.
背景 非缺血性扩张型心肌病（DCM）患者中，心源性猝死（SCD）是导致死亡的主要原因之一。然而，SCD 事件的风险分层在临床实践中仍然具有挑战性。目的 确定心脏 MRI 心肌组织特征是否可用于预测 SCD 事件，并探讨非缺血性 DCM 中的 SCD 分层算法。材料与方法 这是一项前瞻性单中心研究，纳入了 2012 年 6 月至 2020 年 8 月期间接受心脏 MRI 的非缺血性 DCM 成人患者。与 SCD 相关的事件包括 SCD、适当的植入式心律转复除颤器电击、心脏骤停后的复苏。采用竞争风险回归分析和 Kaplan-Meier 分析确定心肌组织特征与结局的关联。结果 在 858 名参与者（平均年龄 48 岁；年龄范围 18-83 岁；603 名男性）中，70 名（8%）参与者在中位随访 33.0 个月期间发生了与 SCD 相关的事件。在多变量竞争风险分析中，晚期钆增强（LGE）（危险比 [HR]，1.87；95%CI：1.07，3.27； =.03）、自然 T1（每增加 10 毫秒：HR，1.07；95%CI：1.04，1.11；<.001）和细胞外容积分数（每增加 3%：HR，1.26；95%CI：1.11，1.44；<.001）是调整了收缩压、房颤和左心室射血分数后与 SCD 相关事件相关的独立预测因素。采用自然 T1 和 LGE 的组合制定了 SCD 风险分层类别。自然 T1 值比平均值高 4 个标准差（1382 毫秒）的参与者，SCD 相关事件的年发生率最高，为 9.3%，自然 T1 值比平均值低 2 个标准差（1292 毫秒）且 LGE 为阴性的参与者发生率最低，为 0.6%。该类别具有良好的预测能力（C 统计值=0.74），可用于区分 SCD 风险和竞争的心力衰竭风险。结论 源自心脏 MRI 的心肌组织特征是非缺血性扩张型心肌病患者 SCD 相关事件的独立预测因素，可用于根据不同的 SCD 风险类别对参与者进行分层。临床试验注册号 ChiCTR1800017058 © RSNA，2023 本期杂志中还刊登了 Sakuma 的社论。
