Myocardial strain analysis by cardiac magnetic resonance associated with arrhythmias in repaired tetralogy of Fallot patients.

IF 2.9 3区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING BMC Medical Imaging Pub Date : 2024-12-03 DOI:10.1186/s12880-024-01514-y
Watcharachai Kangvanskol, Paweena Chungsomprasong, Yonthakan Sanwong, Supaporn Nakyen, Chodchanok Vijarnsorn, Karnkawin Patharateeranart, Prakul Chanthong, Supaluck Kanjanauthai, Thita Pacharapakornpong, Ploy Thammasate, Kritvikrom Durongpisitkul, Jarupim Soongswang
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Abstract

Background: Evaluating myocardial function using cardiac magnetic resonance (CMR) feature tracking provides a comprehensive cardiac assessment, particularly a detailed evaluation for patients with repaired tetralogy of Fallot (rTOF). This study aimed to identify factors associated with arrhythmias in rTOF patients utilizing conventional CMR techniques, including myocardial strain measurements.

Methods: This single-center, retrospective study included 245 rTOF patients who underwent CMR between 2017 and 2023. Patients were stratified based on the presence or absence of arrhythmias during follow-up. The biventricular strain was assessed using CMR-derived feature tracking. Demographic, clinical, and imaging data were collected, and statistical analyses were performed to identify factors associated with arrhythmic events.

Results: The median age at surgery was 5.6 years (range 1-44 years), with the median age at CMR was 27.5 years (range 15-69 years). Over the follow-up period, 25 patients (10.2%) experienced atrial or ventricular arrhythmias. Univariate analysis revealed significant associations between arrhythmic events and older age at surgery and CMR, lower functional class, larger heart size on chest radiograph, and prolonged QRS duration (QRSd). Additionally, arrhythmias were associated with increased right ventricular (RV) volume, reduced RV and left ventricular (LV) ejection fraction (EF), and impaired strain values. Multivariate binary logistic regression, adjusting for age at surgery, NYHA class, QRSd, and cardiothoracic ratio, identified that a lower RV EF (adjusted odds ratio [aOR] 6.97), RV global radial strain (GRS) (aOR 6.68), RV global circumferential strain (GCS) (aOR 6.36), RV global longitudinal strain (GLS) (aOR 3.14), and LV GRS (aOR 3.02) were all significantly associated with arrhythmias.

Conclusion: This study highlights the significant contribution of CMR-derived myocardial strain measurements in predicting arrhythmic events in patients with rTOF. In addition to conventional RV EF, strain metrics-particularly those of the right ventricle- emerged as strong, independent predictors of arrhythmias, offering valuable prognostic information for clinical management in this patient population. These findings underscore the importance of myocardial strain analysis as a complementary tool to conventional imaging in evaluating arrhythmic risk in rTOF patients.

Clinical trial number: Not applicable.

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修复后法洛四联症患者心律失常的心脏磁共振心肌应变分析。
背景:使用心脏磁共振(CMR)特征跟踪评估心肌功能提供了全面的心脏评估,特别是对修复的法洛四联症(rTOF)患者进行了详细的评估。本研究旨在利用常规CMR技术,包括心肌应变测量,确定与rTOF患者心律失常相关的因素。方法:这项单中心回顾性研究纳入了2017年至2023年间接受CMR治疗的245例rTOF患者。根据随访期间是否存在心律失常对患者进行分层。使用cmr衍生的特征跟踪评估双心室应变。收集了人口统计学、临床和影像学资料,并进行统计分析,以确定与心律失常事件相关的因素。结果:手术时的中位年龄为5.6岁(范围1-44岁),CMR时的中位年龄为27.5岁(范围15-69岁)。在随访期间,25例患者(10.2%)出现房性或室性心律失常。单因素分析显示,心律失常事件与手术年龄和CMR年龄较大、功能等级较低、胸片上心脏尺寸较大和QRS持续时间(QRSd)延长之间存在显著关联。此外,心律失常与右心室(RV)容积增加、左心室(LV)射血分数(EF)降低以及应变值受损有关。多变量二元logistic回归,调整手术年龄、NYHA分级、QRSd和心胸比,发现较低的RV EF(校正优势比[aOR] 6.97)、RV整体径向应变(aOR 6.68)、RV整体周向应变(GCS) (aOR 6.36)、RV整体纵向应变(GLS) (aOR 3.14)和LV GRS (aOR 3.02)均与心律失常显著相关。结论:本研究强调了cmr衍生的心肌应变测量在预测rTOF患者心律失常事件方面的重要贡献。除了传统的RV EF外,应变指标-特别是右心室的应变指标-成为心律失常的强大,独立的预测指标,为该患者群体的临床管理提供了有价值的预后信息。这些发现强调了心肌应变分析作为常规影像学评估rTOF患者心律失常风险的补充工具的重要性。临床试验号:不适用。
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来源期刊
BMC Medical Imaging
BMC Medical Imaging RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-
CiteScore
4.60
自引率
3.70%
发文量
198
审稿时长
27 weeks
期刊介绍: BMC Medical Imaging is an open access journal publishing original peer-reviewed research articles in the development, evaluation, and use of imaging techniques and image processing tools to diagnose and manage disease.
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