High-Fidelity MicroCT Reconstructions of Cardiac Devices Enable Patient-Specific Simulation for Structural Heart Interventions.

Background/

Objective

Precise preprocedural planning is essential for the safety and efficacy of structural heart interventions. Conventional imaging modalities, while informative, do not allow for direct and accurate visualization, limiting procedural predictability. We aimed to develop and validate a high-resolution micro-computed tomography (microCT)-based reverse modeling workflow that integrates digital reconstructions of metallic cardiac devices into patient imaging datasets, enabling accurate, patient-specific virtual simulation for procedural planning.

Methods

Clinical-grade transcatheter heart valves, septal defect occluders, patent ductus arteriosus occluders, left atrial appendage closure devices, and coronary stents were scanned using microCT (36.9 μm resolution). Agreement was assessed by intra-class correlation coefficients (ICC) and Bland-Altman analyses. Device geometries were reconstructed into 3D stereolithography files and virtually implanted within multislice CT datasets using dedicated software.

Results

Devices were successfully reverse-modeled with high geometric fidelity, showing negligible dimensional deviations from manufacturer specifications (mean ΔDistance range: -0.20 to +0.20 mm). Simulated measurements demonstrated excellent concordance with postprocedural imaging (ICC 0.90-0.96). The workflow accurately predicted clinically relevant parameters such as valve-to-coronary distances and implantation depths. Notably, preprocedural simulation identified a case at high risk of coronary obstruction, confirmed clinically and managed successfully.

Conclusions

The microCT-based reverse modeling workflow offers a rapid, reproducible, and clinically relevant method for patient-specific simulation in structural heart interventions. By preserving anatomical fidelity and providing detailed device-tissue spatial visualization, this approach enhances preprocedural planning accuracy, risk stratification, and procedural safety. Its resource-efficient digital nature facilitates broad adoption and iterative simulation.