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FE-based risk assessment of coronary artery compression in pulmonary conduit pre-stenting: optimizing the balance
Davide Astori1, Francesco Sturla1,2, Alessandro Caimi3
1Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milano, Italy.
Background And Objective:
Calcific obstruction of the pulmonary conduit is a late complication of surgical implantation of a homograft in congenital patients. Percutaneous pulmonary valve implantation (PPVI) is an effective alternative to surgical repair. However, this procedure is affected by several complications, with coronary artery (CA) compression being one of the most severe. High-fidelity finite element (FE) models can provide accurate predictions but are too computationally expensive for routine use, whereas simplified models sacrifice mechanical fidelity. This study proposes a novel FE-based framework to investigate conduit pre-stenting feasibility, while aiming to balance computational efficiency with predictive accuracy within clinically relevant timelines.
Methods:
A semi-automated pipeline was developed, requiring manual input only for the segmentation of computed tomography (CT), virtual stent positioning, and simulation launch. Patient-specific geometries were meshed and processed through an automated in-house script, generating ready-to-run Abaqus input files. A multifactorial CA compression risk index was introduced, integrating baseline and post-expansion distances between the pulmonary artery and CA, and their changes during the procedure. The FE simulation of the pre-stenting procedure was tested on 10 PPVI candidates, simulating CP-stent implantation. Simulation accuracy was assessed against fluoroscopy-derived stent diameters.
Results:
The full simulation process required less than 10 h per case, with minimal operator workload. FE-predicted stent configuration showed strong agreement with fluoroscopic measurements ( = 0.87), with a mean absolute error of 3.5 4.4%. Accuracy was highest in patients with calcific volumes <0.8 (error <0.5 mm). CA compression index identified 2 high-risk, 2 moderate-risk, and 6 negligible-risk patients. Peri-procedural fluoroscopy was not available for one negligible-risk patient; it excluded CA compression for the remaining negligible-risk patients (true negatives), for all moderate-risk patients, and for one high-risk patient (false positive); it highlighted CA compression for the remaining high-risk patient (true positive).
Conclusions:
The proposed FE simulation framework enables patient-specific prediction of stent configuration and CA compression risk within clinically compatible timelines. The balanced trade-off between mechanical fidelity and computational efficiency supports its potential integration into pre-procedural planning of conduit pre-stenting and PPVI.
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