Morphological Characteristics Following Self-Expanding Transcatheter Heart Valve Implantation and Implications for Hypoattenuating Leaflet Thickening

Background: Hypoattenuating leaflet thickening (HALT) following transcatheter aortic valve replacement (TAVR) may compromise valve durability, posing a significant barrier to the broader adoption of this technology among younger patients. Self-expanding valves (SEVs) are the most commonly used transcatheter heart valves (THVs) among Chinese patients with aortic stenosis. Understanding the potential mechanisms underlying HALT is, therefore, critical to guide future THV design and development.

Aims: Identify morphological factors associated with HALT Unidentified after SEVs implantation.

Methods: This study included 195 consecutive patients from Fuwai Hospital who underwent TAVR with SEVs. All participants underwent their first postoperative 4D-CT scan within 6 months of the procedure. Key parameters following THV implantation were measured and recorded using 3mensio software. Univariate and multivariable logistic regression models were applied to identify associations between variables and HALT. Discriminatory ability was assessed using receiver operating characteristic (ROC) analysis, followed by bootstrap validation for model robustness.

Results: HALT was observed in 36.4% of patients (71 out of 195 patients). New sinus height (NSH) and leaflet outflow area were identified as independent risk factors for HALT. The areas under the curve (AUC) for NSH and leaflet outflow area were 0.689 (95% CI: 0.612-0.767) and 0.602 (95% CI: 0.521-0.683), respectively, with no significant difference between them (p = 0.082). Bootstrap validation confirmed the robustness of both NSH and leaflet outflow area, showing performance comparable to the initial stepwise model.

Conclusion: NSH and leaflet outflow area were identified as critical post-THV implantation parameters associated with HALT in TAVR patients treated with SEVs. These findings provide valuable insights that could inform the future design and optimization of SEVs.