These findings have large implications for informing clinical practice, as the annuloplasty procedure, which often results in fixing the mitral annulus, is the most common MV surgical intervention ( 6, 8). For example, by characterizing mitral annulus motion, researchers found that the cyclic, saddle-shape conformational changes of the annulus are important for efficient operation of the valve, reducing systolic strains on the posterior leaflet and peak leaflet stresses, potentially improving long-term durability ( 12, 13). Using these models, publications have revealed pathological dynamics and generated useful quantifications based on valvular geometry. Pioneering the clinical application of new computational technologies, researchers have used real-time 3D echocardiography to generate patient-specific computational models of the MV ( 6– 11). A particular area of study that has seen major advancements from in silico, image-based modeling is that of MV dynamics. As imaging modalities and mechanical characterization of biological systems have improved, so have the relevance and realism of these models to better predict physiologic outcomes. In Silico ModelingĬomputational simulations have been a major driving force for generating greater intuition of heart valve mechanics. Each of these modalities has unique advantages and disadvantages, and presented is a review of recent, impactful developments in the field, including the key outlooks and limitations of the technologies. In particular, ex vivo modeling represents an especially promising class of translatable research that leverages the advantages from both in silico and in vivo modeling to provide deep quantitative and qualitative understandings of valvular biomechanics. Modeling technologies, which have provided the underlying platforms for generating many new analyses and insights. However, significant advancements have been made to better understand heart valves and have largely been driven by in silico, ex vivo, and in vivo This disconnect is particularly evident in the lack of surgeon consensus regarding debates such as optimal repair techniques and mechanisms behind disease pathologies and operations ( 2– 5). Moreover, many valvular pathologies are rooted in biomechanical changes, yet the technologies for studying these pathologies and identifying treatments have largely been limited. While there are a wide variety of repair operations and devices, most of these strategies have been historically based upon anatomy and subjective visual appearance, and quantitative mechanical foundations have been limited as interventional insights have largely been driven by clinical outcomes. Valvular heart disease is a significant cause of global morbidity and mortality, with a prognosis rivaling many types of cancer ( 1). The frontiers of this work are being discovered by innovative research groups that have used creative, interdisciplinary approaches toward recapitulating in vivo physiology, changing the landscape of clinical understanding and practice for cardiovascular surgery and medicine. In particular, novel ex vivo modeling technologies represent an especially promising class of translatable research that leverages the advantages from both in silico and in vivo modeling to provide deep quantitative and qualitative insights on valvular biomechanics. These modalities represent cutting-edge abilities for generating novel insights regarding native, disease, and repair physiologies, and each has unique advantages and limitations for advancing study in this field. Nonetheless, significant advancements are underway to better understand the biomechanics of heart valves, pathologies, and interventional therapeutics, and these advancements have largely been driven by crucial in silico, ex vivo, and in vivo modeling technologies. While most valvular pathologies are rooted in biomechanical changes, the technologies for studying these pathologies and identifying treatments have largely been limited. The field of heart valve biomechanics is a rapidly expanding, highly clinically relevant area of research. 4University Department of Cardiac Surgery, Leipzig Heart Center, Leipzig, Germany.3Department of Bioengineering, Stanford University, Stanford, CA, United States. 2Department of Mechanical Engineering, Stanford University, Stanford, CA, United States.1Department of Cardiothoracic Surgery, Stanford University, Stanford, CA, United States.Imbrie-Moore 1,2, Hanjay Wang 1, Mateo Marin-Cuartas 1,4, Michael J.
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