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三尖瓣反流中的右心室动力学:经导管瓣膜干预后逆向重构及预后预测的见解

Right Ventricular Dynamics in Tricuspid Regurgitation: Insights into Reverse Remodeling and Outcome Prediction Post Transcatheter Valve Intervention.

作者信息

Doldi Philipp M, Thienel Manuela, Willy Kevin

机构信息

Medizinische Klinik und Poliklinik I, LMU Klinikum, Marchioninistraße 15, 81377 Munich, Germany.

Kliniken für Kardiologie II & III, Universitätsklinikum Münster, 48149 Muenster, Germany.

出版信息

Int J Mol Sci. 2025 Jun 30;26(13):6322. doi: 10.3390/ijms26136322.

Abstract

Tricuspid regurgitation (TR) represents a significant, often silently progressing, valvular heart disease with historically suboptimal management due to perceived high surgical risks. Transcatheter tricuspid valve interventions (TTVI) offer a promising, less invasive therapeutic avenue. Central to the success of TTVI is Right Ventricular Reverse Remodelling (RVRR), defined as an improvement in RV structure and function, which strongly correlates with enhanced patient survival. The right ventricle (RV) undergoes complex multi-scale biomechanical maladaptations, progressing from adaptive concentric to maladaptive eccentric hypertrophy, coupled with increased stiffness and fibrosis. Molecular drivers of this pathology include early failure of antioxidant defenses, metabolic shifts towards glycolysis, and dysregulation of microRNAs. Accurate RV function assessment necessitates advanced imaging modalities like 3D echocardiography, Cardiac Magnetic Resonance Imaging (CMR), and Computed Tomography (CT), along with strain analysis. Following TTVI, RVRR typically manifests as a biphasic reduction in RV volume overload, improved myocardial strain, and enhanced RV-pulmonary arterial coupling. Emerging molecular biomarkers alongside advanced imaging-derived biomechanical markers like CT-based 3D-TAPSE and RV longitudinal strain, are proving valuable. Artificial intelligence (AI) and machine learning (ML) are transforming prognostication by integrating diverse clinical, laboratory, and multi-modal imaging data, enabling unprecedented precision in risk stratification and optimizing TTVI strategies.

摘要

三尖瓣反流(TR)是一种严重的瓣膜性心脏病,通常进展隐匿,由于以往认为手术风险高,其管理一直不尽人意。经导管三尖瓣介入治疗(TTVI)提供了一种有前景的、侵入性较小的治疗途径。TTVI成功的关键在于右心室逆向重构(RVRR),即右心室结构和功能的改善,这与患者生存率的提高密切相关。右心室(RV)经历复杂的多尺度生物力学适应不良,从适应性向心性肥厚发展为适应性离心性肥厚,同时伴有硬度增加和纤维化。这种病理状态的分子驱动因素包括抗氧化防御的早期失败、代谢向糖酵解的转变以及微小RNA的失调。准确评估右心室功能需要先进的成像方式,如三维超声心动图、心脏磁共振成像(CMR)和计算机断层扫描(CT),以及应变分析。TTVI后,RVRR通常表现为右心室容量超负荷的双相减少、心肌应变改善以及右心室与肺动脉耦合增强。新兴的分子生物标志物以及基于CT的3D-TAPSE和右心室纵向应变等先进成像衍生的生物力学标志物正证明具有重要价值。人工智能(AI)和机器学习(ML)正在通过整合各种临床、实验室和多模态成像数据来改变预后,在风险分层中实现前所未有的精准度,并优化TTVI策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/382e/12249904/f645651617ca/ijms-26-06322-g001.jpg

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