Abstract
Purpose
The interplay between geometry and hemodynamics is a significant factor in the development of cardiovascular diseases. This is particularly true for stented coronary arteries. To elucidate this factor, an accurate patient-specific analysis requires the reconstruction of the geometry following the stent deployment for a computational fluid dynamics (CFD) investigation. The image-based reconstruction is troublesome for the different possible positions of the stent struts in the lumen and the coronary wall. However, the accurate inclusion of the stent footprint in the hemodynamic analysis is critical for detecting abnormal stress conditions and flow disturbances, particularly for thick struts like in bioresorbable scaffolds. Here, we present a novel reconstruction methodology that relies on Data Assimilation and Computer Aided Design.
Methods
The combination of the geometrical model of the undeployed stent and image-based data assimilated by a variational approach allows the highly automated reconstruction of the skeleton of the stent. A novel approach based on computational mechanics defines the map between the intravascular frame of reference (called L-view) and the 3D geometry retrieved from angiographies. Finally, the volumetric expansion of the stent skeleton needs to be self-intersection free for the successive CFD studies; this is obtained by using implicit representations based on the definition of Nef-polyhedra.
Results
We assessed our approach on a vessel phantom, with less than 10% difference (properly measured) vs. a customized manual (and longer) procedure previously published, yet with a significant higher level of automation and a shorter turnaround time. Computational hemodynamics results were even closer. We tested the approach on two patient-specific cases as well.
Conclusions
The method presented here has a high level of automation and excellent accuracy performances, so it can be used for larger studies involving patient-specific geometries.
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Availability of Data and Material
The codes developed specifically for this paper are under GPL Licence and will be available upon request to the corresponding author. Specifically: 1. Registration: The point-cloud-to-polyline registration was developed under the Matlab FAIR package obtained under permission of the authors. The availability of our solver is subject to the availability of FAIR. 2. Mapping: the FENICS code is available upon request 3. Volume Meshing: the code developed with OpenCASCADE (LGPL) and CGAL (GPL) are available upon request. The de-identified data used for benchmarking can be requested as well, consistently with the restrictions of the Clinical Trial NCT01751906.
Notes
Deviations from rectilinear are induced by the catheter floating.
To the best of the authors’ knowledge, the terminology that follows has not been used elsewhere.
Here, we have no reason for introducing different parameters for the in-plane Cartesian coordinates x and y. A different coordinate system (e.g., polar) may require different parameters.
When the stent does not have a circular cross-section, we intend here the diameter of the smallest pipe enclosing the stent.
Notice that Nef-polyhedron are not restricted to convex polytopes.6
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Acknowledgments
The contribution of Boyi Yang and Gaetano Esposito (Emory University Hospital) to the early stages of this work is gratefully acknowledged. S. B. thanks the Department of Mathematics at Emory University for the hospitality. A.V., H.S., D.M. and A.L. thank Don Giddens for many fruitful discussions on the topics of the paper and suggestions when preparing the manuscripts. Habib Samady and David Molony are now with the Northeast Georgia Medical Center, 743 Spring Street Gainesville, GA 30501, USA.
Funding
Some of the computation were performed on XSEDE facilities (Stampede 2) under the NSF-XSEDE TG-ASC160069 Grant. H. S. acknowledges the support to his research from Medtronic, Abbott Vascular, Philips, Gilead.
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AL: method design, development, advising, code implementation, paper writing. SB: method design, development, code implementation, paper writing. MP: code development, paper writing. DM: data collection, image segmentation, proofreading. HS: clinical direction, data collection, supervision and handling of the clinical data, proofreading. CC, FM: method design, advising, results analysis, proofreading. AV: method design, advising, results analysis, paper writing.
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The authors A.L., S.B., D.M., M.P., C.C., and F.M. declare that they have no conflict of interest. H.S. and A.V. are co-founders, former CMO/consultant and CSO respectively and equity holders of COVANOS Inc. A.L. is a consultant and equity holder of COVANOS Inc. No conflict of interest to be disclosed for this activity. H.S. received grants from Medtronic, Abbott Vascular, Philips, and Gilead. H.S. is also part of the Trial steering committee, consultant for Philips, Abbott Vascular.
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Lefieux, A., Bridio, S., Molony, D. et al. Semi-Automatic Reconstruction of Patient-Specific Stented Coronaries based on Data Assimilation and Computer Aided Design. Cardiovasc Eng Tech 13, 517–534 (2022). https://doi.org/10.1007/s13239-021-00570-7
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DOI: https://doi.org/10.1007/s13239-021-00570-7