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Infarct tissue heterogeneity assessed with contrast-enhanced MRI predicts spontaneous ventricular arrhythmia in patients with ischemic cardiomyopathy and implantable cardioverter-defibrillator.用对比增强磁共振成像评估的梗死组织异质性可预测缺血性心肌病和植入式心律转复除颤器患者的自发性室性心律失常。
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Impact of the presence and amount of myocardial fibrosis by cardiac magnetic resonance on arrhythmic outcome and sudden cardiac death in nonischemic dilated cardiomyopathy.心脏磁共振检查心肌纤维化的存在和程度对非缺血性扩张型心肌病心律失常转归和心源性猝死的影响。
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Complexity of scar and ventricular arrhythmias in dilated cardiomyopathy of any etiology: Long-term data from the SCARFEAR (Cardiovascular Magnetic Resonance Predictors of Appropriate Implantable Cardioverter-Defibrillator Therapy Delivery) Registry.任何病因的扩张型心肌病中瘢痕与室性心律失常的复杂性：来自SCARFEAR（合适的植入式心脏复律除颤器治疗的心血管磁共振预测因素）注册研究的长期数据。
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本文引用的文献

1
Comprehensive Phenotypic Characterization of Late Gadolinium Enhancement Predicts Sudden Cardiac Death in Coronary Artery Disease.全面表型特征分析预测冠状动脉疾病患者的心脏性猝死。
JACC Cardiovasc Imaging. 2023 May;16(5):628-638. doi: 10.1016/j.jcmg.2022.10.020. Epub 2023 Jan 11.
2
Infarct quantification with cardiovascular magnetic resonance using "standard deviation from remote" is unreliable: validation in multi-centre multi-vendor data.采用“远程标准差”进行心血管磁共振的梗死量化不可靠：多中心多供应商数据的验证。
J Cardiovasc Magn Reson. 2022 Nov 7;24(1):53. doi: 10.1186/s12968-022-00888-8.
3
Artificial Intelligence and Cardiovascular Magnetic Resonance Imaging in Myocardial Infarction Patients.人工智能与心肌梗死患者的心血管磁共振成像
Curr Probl Cardiol. 2022 Dec;47(12):101330. doi: 10.1016/j.cpcardiol.2022.101330. Epub 2022 Jul 21.
4
Greyzone myocardial fibrosis and ventricular arrhythmias in patients with a left ventricular ejection fraction >35.左心室射血分数＞35%患者的灰色区域心肌纤维化与室性心律失常。
Europace. 2022 Jan 4;24(1):31-39. doi: 10.1093/europace/euab167.
5
Scar channels in cardiac magnetic resonance to predict appropriate therapies in primary prevention.心脏磁共振瘢痕通道预测一级预防中合适的治疗方法。
Heart Rhythm. 2021 Aug;18(8):1336-1343. doi: 10.1016/j.hrthm.2021.04.017. Epub 2021 Apr 21.
6
Myocardial Fibrosis as a Predictor of Sudden Death in Patients With Coronary Artery Disease.心肌纤维化作为冠心病患者猝死的预测因子。
J Am Coll Cardiol. 2021 Jan 5;77(1):29-41. doi: 10.1016/j.jacc.2020.10.046.
7
Substrate Spatial Complexity Analysis for the Prediction of Ventricular Arrhythmias in Patients With Ischemic Cardiomyopathy.底物空间复杂度分析预测缺血性心肌病患者的室性心律失常。
Circ Arrhythm Electrophysiol. 2020 Apr;13(4):e007975. doi: 10.1161/CIRCEP.119.007975. Epub 2020 Mar 18.
8
Sudden Cardiac Death in Ischemic Heart Disease: From Imaging Arrhythmogenic Substrate to Guiding Therapies.缺血性心脏病中的心脏性猝死：从心律失常基质的影像学评估到治疗策略的指导。
JACC Cardiovasc Imaging. 2020 Oct;13(10):2223-2238. doi: 10.1016/j.jcmg.2019.10.021. Epub 2019 Dec 18.
9
Peri-Infarct Quantification by Cardiac Magnetic Resonance to Predict Outcomes in Ischemic Cardiomyopathy: Prognostic Systematic Review and Meta-Analysis.心肌梗死周边定量的心脏磁共振成像预测缺血性心肌病患者预后的系统评价和荟萃分析。
Circ Cardiovasc Imaging. 2019 Nov;12(11):e009156. doi: 10.1161/CIRCIMAGING.119.009156. Epub 2019 Nov 18.
10
Scar shape analysis and simulated electrical instabilities in a non-ischemic dilated cardiomyopathy patient cohort.非缺血性扩张型心肌病患者队列中的瘢痕形态分析和模拟电不稳定性。
PLoS Comput Biol. 2019 Oct 28;15(10):e1007421. doi: 10.1371/journal.pcbi.1007421. eCollection 2019 Oct.

Myocardial Tissue Characterization to Predict Ventricular Arrhythmic Risk: Road Well-Traveled But So Far to Go.

作者信息

Wu Katherine C

机构信息

Division of Cardiology, Johns Hopkins Medical Institutions, Baltimore, Maryland, USA.

出版信息

JACC Cardiovasc Imaging. 2023 May;16(5):639-641. doi: 10.1016/j.jcmg.2022.12.017. Epub 2023 Jan 25.

DOI:10.1016/j.jcmg.2022.12.017
PMID:36707355
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10159956/
Abstract
摘要