Hirschvogel, Marc

Introduction Mitral regurgitation (MR) is a common valvular disease associated with complications such as pulmonary hypertension, atrial fibrillation, and heart failure. However, its full impact on the cardiovascular system, especially on right heart function, is not yet fully understood. Understanding this relationship is important because the right ventricle (RV) is critical for maintaining cardiovascular function. Dysfunction of the RV, which may be contributed by conditions like MR, is strongly associated with poor clinical outcomes. Despite its importance, comprehensively studying MR's effect on the RV has been challenging due to the complex, interdependent nature of cardiovascular dynamics, limited patient data, and the difficulty in synthesizing disparate information to clarify the left heart-right heart connection. Methods The primary goal of this study is to investigate the effects of MR on cardiovascular hemodynamics and RV function by integrating 3D models of the left heart with a closed-loop 0D models of the entire cardiovascular system. We further conduct detailed analyses using patient-specific models to explore how various system modifications impact the RV, providing insights into the nuanced effects of MR on the right heart. Results and Discussion This analysis provides several clinically relevant insights. First, progressive MR markedly increases RV afterload and predisposes the RV to dysfunction, even when intrinsic RV contractility is preserved or enhanced. Second, MR-specific severity indices and left-heart metrics alone fail to capture the true burden on the right heart; RV impairment can progress despite stable or only modestly changing MR descriptors. Finally, these findings highlight the need to incorporate direct assessment of RV structure and function into the evaluation of MR, as RV vulnerability plays a critical role in determining patient risk and guiding management decisions.

Abstract We present a high-fidelity, patient-specific computational framework for simulating cardiovascular hemodynamics in left ventricular assist device (LVAD) patients, with the ability to evaluate the impact of mitral and aortic valve repair. The method couples three-dimensional computational fluid dynamics (CFD) with a zero-dimensional lumped-parameter network representing the full cardiovascular system. Valve dynamics are governed by pressure–flow physics with patient-specific regurgitant areas, enabling the investigation of valve insufficiency and surgical repair. The model incorporates dynamic contrast-enhanced CT imaging, echocardiography, and catheter-based measurements. We demonstrate the utility of this framework using a clinical case involving a patient on long-term LVAD support with mitral regurgitation and aortic insufficiency. The coupled model resolves detailed pressure and velocity fields in the left heart, LVAD cannulae, and aortic root, while maintaining system-wide physiological consistency. Importantly, the framework also quantifies right ventricular loading and function, allowing assessment of how left-sided valve interventions propagate through the cardiopulmonary circulation. Using this pipeline, we simulate mitral and aortic valve repair by modulating valve closure mechanics and regurgitant area, revealing changes in both local and global hemodynamics. This modeling platform provides a powerful means to study the interplay between mechanical circulatory support, native valve physiology, and right heart function. It enables rigorous, patient-specific evaluation of surgical interventions in LVAD patients and delivers quantitative insight into clinically important metrics—such as aortic pulsatility, RV afterload, and chamber-level flow patterns—that are challenging to capture with current imaging modalities.