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Improving accuracy for finite element modeling of endovascular coiling of intracranial aneurysm

BACKGROUND: Computer modeling of endovascular coiling intervention for intracranial aneurysm could enable a priori patient-specific treatment evaluation. To that end, we previously developed a finite element method (FEM) coiling technique, which incorporated simplified assumptions. To improve accura...

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Autores principales: Damiano, Robert J., Tutino, Vincent M., Lamooki, Saeb R., Paliwal, Nikhil, Dargush, Gary F., Davies, Jason M., Siddiqui, Adnan H., Meng, Hui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6934293/
https://www.ncbi.nlm.nih.gov/pubmed/31881029
http://dx.doi.org/10.1371/journal.pone.0226421
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author Damiano, Robert J.
Tutino, Vincent M.
Lamooki, Saeb R.
Paliwal, Nikhil
Dargush, Gary F.
Davies, Jason M.
Siddiqui, Adnan H.
Meng, Hui
author_facet Damiano, Robert J.
Tutino, Vincent M.
Lamooki, Saeb R.
Paliwal, Nikhil
Dargush, Gary F.
Davies, Jason M.
Siddiqui, Adnan H.
Meng, Hui
author_sort Damiano, Robert J.
collection PubMed
description BACKGROUND: Computer modeling of endovascular coiling intervention for intracranial aneurysm could enable a priori patient-specific treatment evaluation. To that end, we previously developed a finite element method (FEM) coiling technique, which incorporated simplified assumptions. To improve accuracy in capturing real-life coiling, we aimed to enhance the modeling strategies and experimentally test whether improvements lead to more accurate coiling simulations. METHODS: We previously modeled coils using a pre-shape based on mathematical curves and mechanical properties based on those of platinum wires. In the improved version, to better represent the physical properties of coils, we model coil pre-shapes based on how they are manufactured, and their mechanical properties based on their spring-like geometric structures. To enhance the deployment mechanics, we include coil advancement to the aneurysm in FEM simulations. To test if these new strategies produce more accurate coil deployments, we fabricated silicone phantoms of 2 patient-specific aneurysms in duplicate, deployed coils in each, and quantified coil distributions from intra-aneurysmal cross-sections using coil density (CD) and lacunarity (L). These deployments were simulated 9 times each using the original and improved techniques, and CD and L were calculated for cross-sections matching those in the experiments. To compare the 2 simulation techniques, Euclidean distances (d(Min), d(Max), and d(Avg)) between experimental and simulation points in standardized CD-L space were evaluated. Univariate tests were performed to determine if these distances were significantly different between the 2 simulations. RESULTS: Coil deployments using the improved technique agreed better with experiments than the original technique. All d(Min), d(Max), and d(Avg) values were smaller for the improved technique, and the average values across all simulations for the improved technique were significantly smaller than those from the original technique (d(Min): p = 0.014, d(Max): p = 0.013, d(Avg): p = 0.045). CONCLUSION: Incorporating coil-specific physical properties and mechanics improves accuracy of FEM simulations of endovascular intracranial aneurysm coiling.
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spelling pubmed-69342932020-01-07 Improving accuracy for finite element modeling of endovascular coiling of intracranial aneurysm Damiano, Robert J. Tutino, Vincent M. Lamooki, Saeb R. Paliwal, Nikhil Dargush, Gary F. Davies, Jason M. Siddiqui, Adnan H. Meng, Hui PLoS One Research Article BACKGROUND: Computer modeling of endovascular coiling intervention for intracranial aneurysm could enable a priori patient-specific treatment evaluation. To that end, we previously developed a finite element method (FEM) coiling technique, which incorporated simplified assumptions. To improve accuracy in capturing real-life coiling, we aimed to enhance the modeling strategies and experimentally test whether improvements lead to more accurate coiling simulations. METHODS: We previously modeled coils using a pre-shape based on mathematical curves and mechanical properties based on those of platinum wires. In the improved version, to better represent the physical properties of coils, we model coil pre-shapes based on how they are manufactured, and their mechanical properties based on their spring-like geometric structures. To enhance the deployment mechanics, we include coil advancement to the aneurysm in FEM simulations. To test if these new strategies produce more accurate coil deployments, we fabricated silicone phantoms of 2 patient-specific aneurysms in duplicate, deployed coils in each, and quantified coil distributions from intra-aneurysmal cross-sections using coil density (CD) and lacunarity (L). These deployments were simulated 9 times each using the original and improved techniques, and CD and L were calculated for cross-sections matching those in the experiments. To compare the 2 simulation techniques, Euclidean distances (d(Min), d(Max), and d(Avg)) between experimental and simulation points in standardized CD-L space were evaluated. Univariate tests were performed to determine if these distances were significantly different between the 2 simulations. RESULTS: Coil deployments using the improved technique agreed better with experiments than the original technique. All d(Min), d(Max), and d(Avg) values were smaller for the improved technique, and the average values across all simulations for the improved technique were significantly smaller than those from the original technique (d(Min): p = 0.014, d(Max): p = 0.013, d(Avg): p = 0.045). CONCLUSION: Incorporating coil-specific physical properties and mechanics improves accuracy of FEM simulations of endovascular intracranial aneurysm coiling. Public Library of Science 2019-12-27 /pmc/articles/PMC6934293/ /pubmed/31881029 http://dx.doi.org/10.1371/journal.pone.0226421 Text en © 2019 Damiano et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Damiano, Robert J.
Tutino, Vincent M.
Lamooki, Saeb R.
Paliwal, Nikhil
Dargush, Gary F.
Davies, Jason M.
Siddiqui, Adnan H.
Meng, Hui
Improving accuracy for finite element modeling of endovascular coiling of intracranial aneurysm
title Improving accuracy for finite element modeling of endovascular coiling of intracranial aneurysm
title_full Improving accuracy for finite element modeling of endovascular coiling of intracranial aneurysm
title_fullStr Improving accuracy for finite element modeling of endovascular coiling of intracranial aneurysm
title_full_unstemmed Improving accuracy for finite element modeling of endovascular coiling of intracranial aneurysm
title_short Improving accuracy for finite element modeling of endovascular coiling of intracranial aneurysm
title_sort improving accuracy for finite element modeling of endovascular coiling of intracranial aneurysm
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6934293/
https://www.ncbi.nlm.nih.gov/pubmed/31881029
http://dx.doi.org/10.1371/journal.pone.0226421
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