SDFStent: Real-time interactive virtual stenting via SDF deformation fields

2026-05-21

AI Summary

This study addresses the challenge of efficiently generating post-stent implantation vascular geometries, a key bottleneck limiting the clinical adoption of patient-specific hemodynamic simulations. The authors propose a real-time virtual stenting method based on signed distance fields (SDFs), which constructs stent geometry via capsule assembly and smooth minimum operators, then deforms the vessel mesh by displacing vertices along SDF gradients. This approach achieves rapid, conformal, and topologically consistent mesh deformation—marking the first application of SDF-based deformation fields to virtual stent modeling. It enables real-time interaction, automatic angle preservation, self-intersection-free results, and clinically accurate dimensions. Experiments demonstrate watertight meshes with mean diameters of 5.92 ± 0.08 mm (target: 6.0 mm) generated in under 1.5 seconds—over 100× faster than existing methods—and computational fluid dynamics (CFD) predictions of pressure drop within 2 mmHg of clinical measurements (maximum error: 4 mmHg). The implementation is publicly available in the 3D Slicer platform.

Abstract

Stenting is among the most common transcatheter interventions for congenital heart disease (CHD). Patient-specific computational fluid dynamics (CFD) simulations can predict hemodynamic outcomes of intervention scenarios but require post-operative vascular geometries that reflect stent-induced shape changes, which existing tools either model inadequately or require extensive time or manual effort to generate. We present SDFStent, a signed distance function (SDF) based mesh deformation method for virtual stenting that operates in real time, maintains mesh integrity, and preserves junction geometry. The stent is modeled as a pipe surface composed of piecewise-capsule SDFs joined by a smooth-minimum operator. Mesh vertices near the expanding SDF surface are displaced along the SDF gradient with a compactly supported fall-off function and an alpha blending mask. SDFStent was benchmarked against three existing approaches and validated on three tetralogy of Fallot (ToF) patients and three coarctation of the aorta (CoA) patients using rigid-wall steady-state CFD simulations against clinical catheterization measurements. Against a prescribed diameter of 6.0 mm, the method produced a mean stented diameter of 5.92 $\pm$ 0.08 mm in 1.5 s, over 100$\times$ faster than the best stenting-specific comparator. All output meshes were watertight and self-intersection-free. CFD-simulated post-operative pressure drops agreed with clinical measurements within 4 mmHg (mean error 2 mmHg). SDFStent produces simulation-ready post-stent models that match prescribed stent dimensions at interactive speeds, from pre-operative anatomy and catheterization data alone. The implementation is open-source and available in 3D Slicer. Its scriptable architecture enables automated generation of large synthetic cohorts for data-driven surrogate modeling.

Problem

• virtual stenting
• congenital heart disease
• computational fluid dynamics
• patient-specific modeling
• mesh deformation

Innovation

• SDF deformation
• virtual stenting
• real-time mesh deformation
• computational fluid dynamics
• signed distance function