Key result
Computational predictive modeling is linked to fewer leaflet modifications in high-risk ViV TAVR.
Why the study?
Traditional CTA-based risk stratification for coronary obstruction in ViV TAVR and redo-TAVR relies on static parameters that may overestimate risk and lead to burdensome leaflet modification procedures. The impact of augmenting preprocedural planning with patient-specific computational predictive modeling on leaflet modification rates needed evaluation.
Does computational predictive modeling (CPM) preprocedural planning augmentation reduce leaflet modification rates in patients undergoing valve-in-valve or redo TAVR deemed high-risk for coronary obstruction by conventional CTA?
Observational (n=157)
Does computational predictive modeling (CPM) preprocedural planning augmentation reduce leaflet modification rates in patients undergoing valve-in-valve or redo TAVR deemed high-risk for coronary obstruction by conventional CTA?
Augmenting conventional CTA planning with computational predictive modeling significantly reduces the need for leaflet modification procedures in high-risk valve-in-valve and redo-TAVR patients without increasing coronary obstruction events.
AI simulation was associated with fewer leaflet modifications; leaves open whether it improves safety in prospective multicenter validation.
BACKGROUND: Coronary obstruction (CO) complicates valve-in-valve (ViV) and redo transcatheter aortic valve replacement (TAVR) at higher rates than native TAVR. Leaflet modification mitigates this risk but increases procedural burden. Traditional computed tomography angiography (CTA)-based risk stratification relies on static parameters that may overestimate risk; computational predictive modeling (CPM) uses patient-specific data to refine risk assessment. OBJECTIVES: The study aims to characterize leaflet modification rates in conventional ViV TAVR and redo-TAVR and evaluate the impact of CPM preprocedural planning augmentation on leaflet modification rates. METHODS: A total of 157 consecutive ViV TAVR or redo-TAVR patients treated from 2022 to 2025 were retrospectively analyzed. CO risk status was derived from traditional CTA parameters. Leaflet modification rates among CTA high-risk subgroups (non-CPM, n = 62; and CPM, n = 29) were compared using Boschloo's one-sided exact test. CPM risk-reclassification patterns were studied using counterfactual binomial analysis. RESULTS: Leaflet modification occurred in 26.3% of ViV TAVR and 24.1% of redo-TAVR procedures that used only conventional CTA-based planning methods. Among patients deemed high risk for CO by conventional methods, leaflet modification was significantly lower in the CPM-augmented subgroup vs that in the non-CPM subgroup (24.1% vs 46.8%; OR: 2.76; 95% CI: 1.03-7.40; P = 0.021). CPM-augmented planning reclassified 82.8% of patients to low-risk status, and 79.2% of reclassified patients were managed without leaflet modification. No COs occurred during the study period. CONCLUSIONS: Among ViV TAVR and redo-TAVR patients at high risk of CO based on conventional CTA-based planning, the use of CPM to augment standard risk assessment was associated with a significant reduction in leaflet modification procedures.
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Valle et al. (2026) conducted an observational in Valve-in-valve (ViV) or redo transcatheter aortic valve replacement (TAVR) at risk for coronary obstruction (n=157). Computational predictive modeling (CPM)-augmented preprocedural planning vs. Conventional CTA-based planning alone (non-CPM) was evaluated on Leaflet modification rate among CTA high-risk patients (OR 2.76, 95% CI 1.03-7.40, p=0.021). Computational predictive modeling reduced leaflet modification vs conventional CTA alone in high-risk ViV/redo-TAVR (24.1% vs 46.8%; OR 2.76, 95% CI 1.03-7.40; P=0.021).
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