Intraoperative post-annuloplasty three-dimensional valve analysis does not predict recurrent ischemic mitral regurgitation

A Computational Pipeline for Patient-Specific Prediction of the Postoperative Mitral Valve Functional State

While mitral valve (MV) repair remains the preferred clinical option for mitral regurgitation (MR) treatment, long-term outcomes remain suboptimal and difficult to predict. Furthermore, pre-operative optimization is complicated by the heterogeneity of MR presentations and the multiplicity of potential repair configurations. In the present work, we established a patient-specific MV computational pipeline based strictly on standard-of-care pre-operative imaging data to quantitatively predict the post-repair MV functional state. First, we established human mitral valve chordae tendinae (MVCT) geometric characteristics obtained from five CT-imaged excised human hearts. From these data, we developed a finite-element model of the full patient-specific MV apparatus that included MVCT papillary muscle origins obtained from both the in vitro study and the pre-operative three-dimensional echocardiography images. To functionally tune the patient-specific MV mechanical behavior, we simulated pre-operative MV closure and iteratively updated the leaflet and MVCT prestrains to minimize the mismatch between the simulated and target end-systolic geometries. Using the resultant fully calibrated MV model, we simulated undersized ring annuloplasty (URA) by defining the annular geometry directly from the ring geometry. In three human cases, the postoperative geometries were predicted to 1 mm of the target, and the MV leaflet strain fields demonstrated close agreement with noninvasive strain estimation technique targets. Interestingly, our model predicted increased posterior leaflet tethering after URA in two recurrent patients, which is the likely driver of long-term MV repair failure. In summary, the present pipeline was able to predict postoperative outcomes from pre-operative clinical data alone. This approach can thus lay the foundation for optimal tailored surgical planning for more durable repair, as well as development of mitral valve digital twins.

Pre-surgical Prediction of Ischemic Mitral Regurgitation Recurrence Using In Vivo Mitral Valve Leaflet Strains

Ischemic mitral regurgitation (IMR) is a prevalent cardiac disease associated with substantial morbidity and mortality. Contemporary surgical treatments continue to have limited long-term success, in part due to the complex and multi-factorial nature of IMR. There is thus a need to better understand IMR etiology to guide optimal patient specific treatments. Herein, we applied our finite element-based shape-matching technique to non-invasively estimate peak systolic leaflet strains in human mitral valves (MVs) from in-vivo 3D echocardiographic images taken immediately prior to and post-annuloplasty repair. From a total of 21 MVs, we found statistically significant differences in pre-surgical MV size, shape, and deformation patterns between the with and without IMR recurrence patient groups at 6 months post-surgery. Recurrent MVs had significantly less compressive circumferential strains in the anterior commissure region compared to the recurrent MVs (p = 0.0223) and were significantly larger. A logistic regression analysis revealed that average pre-surgical circumferential leaflet strain in the Carpentier A1 region independently predicted 6-month recurrence of IMR (optimal cutoff value - 18%, p = 0.0362). Collectively, these results suggest greater disease progression in the recurrent group and underscore the highly patient-specific nature of IMR. Importantly, the ability to identify such factors pre-surgically could be used to guide optimal treatment methods to reduce post-surgical IMR recurrence.

Ex Vivo Model of Ischemic Mitral Regurgitation and Analysis of Adjunctive Papillary Muscle Repair

Ischemic mitral regurgitation (IMR) is particularly challenging to repair with lasting durability due to the complex valvular and subvalvular pathologies resulting from left ventricular dysfunction. Ex vivo simulation is uniquely suited to quantitatively analyze the repair biomechanics, but advancements are needed to model the nuanced IMR disease state. Here we present a novel IMR model featuring a dilation device with precise dilatation control that preserves annular elasticity to enable accurate ex vivo analysis of surgical repair. Coupled with augmented papillary muscle head positioning, the enhanced heart simulator system successfully modeled IMR pre- and post-surgical intervention and enabled the analysis of adjunctive subvalvular papillary muscle repair to alleviate regurgitation recurrence. The model resulted in an increase in regurgitant fraction: 11.6 ± 1.7% to 36.1 ± 4.4% (p < 0.001). Adjunctive papillary muscle head fusion was analyzed relative to a simple restrictive ring annuloplasty repair and, while both repairs successfully eliminated regurgitation initially, the addition of the adjunctive subvalvular repair reduced regurgitation recurrence: 30.4 ± 5.7% vs. 12.5 ± 2.6% (p = 0.002). Ultimately, this system demonstrates the success of adjunctive papillary muscle head fusion in repairing IMR as well as provides a platform to optimize surgical techniques for increased repair durability.

Heart Valve Biomechanics: The Frontiers of Modeling Modalities and the Expansive Capabilities of Ex Vivo Heart Simulation

The field of heart valve biomechanics is a rapidly expanding, highly clinically relevant area of research. While most valvular pathologies are rooted in biomechanical changes, the technologies for studying these pathologies and identifying treatments have largely been limited. 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. 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. 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. 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.