Search

Aortic, mitral and tricuspid valve regurgitation are commonly encountered in patients with continuous-flow left ventricular assist devices (CF-LVADs). These valvular heart conditions either develop prior to CF-LVAD implantation or are induced by the pump itself. They can all have significant detrimental effects on patients' survival and quality of life. With the improved durability of CF-LVADs and the overall rise in their volume of implants, an increasing number of patients will likely require a valvular heart intervention at some point during CF-LVAD therapy. However, these patients are often considered poor reoperative candidates. In this context, percutaneous approaches have emerged as an attractive “off-label” option for this patient population. Recent data show promising results, with high device success rates and rapid symptomatic improvements. However, the occurrence of distinct complications such as device migration, valve thrombosis or hemolysis remain of concern. In this review, we will present the pathophysiology of valvular heart disease in the setting of CF-LVAD support to help us understand the underlying rationale of these potential complications. We will then outline the current recommendations for the management of valvular heart disease in patients with CF-LVAD and discuss their limitations. Lastly, we will summarize the evidence related to transcatheter heart valve interventions in this patient population.

Background: Transcatheter aortic valve implantation (TAVI) is a less invasive alternative to open-heart surgery for treating severe aortic stenosis. Despite its benefits, the risk of procedural complications necessitates careful preoperative planning. Methods: This study proposes a fully automated deep learning-based method, TAVI-PREP, for pre-TAVI planning, focusing on measurements extracted from computed tomography (CT) scans. The algorithm was trained on the public MM-WHS dataset and a small subset of private data. It uses MeshDeformNet for 3D surface mesh generation and a 3D Residual U-Net for landmark detection. TAVI-PREP is designed to extract 22 different measurements from the aortic valvular complex. A total of 200 CT-scans were analyzed, and automatic measurements were compared to the ones made manually by an expert cardiologist. A second cardiologist analyzed 115 scans to evaluate inter-operator variability. Results: High Pearson correlation coefficients between the expert and the algorithm were obtained for most parameters (0.90–0.97), except for left and right coronary height (0.8 and 0.72, respectively). Similarly, the mean absolute relative error was within 5% for most measurements, except for left and right coronary height (11.6% and 16.5%, respectively). A greater consensus was observed among experts than when compared to the automatic approach, with TAVI-PREP showing no discernable bias towards either the lower or higher ends of the measurement spectrum. Conclusions: TAVI-PREP provides reliable and time-efficient measurements of the aortic valvular complex that could aid clinicians in the preprocedural planning of TAVI procedures.