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

Autoři: Robert J. Damiano aff001;  Vincent M. Tutino aff002;  Saeb R. Lamooki aff001;  Nikhil Paliwal aff001;  Gary F. Dargush aff001;  Jason M. Davies aff003;  Adnan H. Siddiqui aff002;  Hui Meng aff001
Působiště autorů: Department of Mechanical and Aerospace Engineering, University at Buffalo, State University of New York, Buffalo, New York, United States of America aff001;  Canon Stroke & Vascular Research Center, University at Buffalo, State University of New York, Buffalo, New York, United States of America aff002;  Department of Neurosurgery, University at Buffalo, State University of New York, Buffalo, New York, United States of America aff003;  Department of Pathology and Anatomical Sciences, University at Buffalo, State University of New York, Buffalo, New York, United States of America aff004;  Department of Biomedical Engineering, University at Buffalo, State University of New York, Buffalo, New York, United States of America aff005
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
doi: 10.1371/journal.pone.0226421



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.


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 (dMin, dMax, and dAvg) 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.


Coil deployments using the improved technique agreed better with experiments than the original technique. All dMin, dMax, and dAvg 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 (dMin: p = 0.014, dMax: p = 0.013, dAvg: p = 0.045).


Incorporating coil-specific physical properties and mechanics improves accuracy of FEM simulations of endovascular intracranial aneurysm coiling.

Klíčová slova:

Aneurysms – Arteries – Catheters – Finite element analysis – Mechanical properties – Physical properties – Platinum – Simulation and modeling


1. Ferns SP, Sprengers ME, van Rooij WJ, Rinkel GJ, van Rijn JC, Bipat S, et al. Coiling of intracranial aneurysms: a systematic review on initial occlusion and reopening and retreatment rates. Stroke; a journal of cerebral circulation. 2009;40(8):e523–9. doi: 10.1161/STROKEAHA.109.553099 19520984.

2. Molyneux AJ, Kerr RS, Yu LM, Clarke M, Sneade M, Yarnold JA, et al. International subarachnoid aneurysm trial (ISAT) of neurosurgical clipping versus endovascular coiling in 2143 patients with ruptured intracranial aneurysms: a randomised comparison of effects on survival, dependency, seizures, rebleeding, subgroups, and aneurysm occlusion. Lancet. 2005;366(9488):809–17. doi: 10.1016/S0140-6736(05)67214-5 16139655.

3. Damiano RJ, Ma D, Xiang J, Siddiqui AH, Snyder KV, Meng H. Finite element modeling of endovascular coiling and flow diversion enables hemodynamic prediction of complex treatment strategies for intracranial aneurysm. Journal of biomechanics. 2015;48(12):3332–40. doi: 10.1016/j.jbiomech.2015.06.018 26169778.

4. Babiker MH, Chong B, Gonzalez LF, Cheema S, Frakes DH. Finite element modeling of embolic coil deployment: multifactor characterization of treatment effects on cerebral aneurysm hemodynamics. Journal of biomechanics. 2013;46(16):2809–16. doi: 10.1016/j.jbiomech.2013.08.021 24119679.

5. Otani T, Ii S, Shigematsu T, Fujinaka T, Hirata M, Ozaki T, et al. Computational model of coil placement in cerebral aneurysm with using realistic coil properties. Journal of Biomechanical Science and Engineering. 2015;10(4):15-00555-15-. doi: 10.1299/jbse.15-00555

6. Fujimura S, Takao H, Suzuki T, Dahmani C, Ishibashi T, Mamori H, et al. Hemodynamics and coil distribution with changing coil stiffness and length in intracranial aneurysms. Journal of neurointerventional surgery. 2017. Epub 2017/12/21. doi: 10.1136/neurintsurg-2017-013457 29259122.

7. Dequidt J, Marchal M, Duriez C, Kerien E, Cotin S. Interactive simulation of embolization coils: modeling and experimental validation. Medical image computing and computer-assisted intervention: MICCAI International Conference on Medical Image Computing and Computer-Assisted Intervention. 2008;11(Pt 1):695–702. doi: 10.1007/978-3-540-85988-8_83 18979807.

8. Wallace MP, Levine, Marc-alan, Hui, Delilah Yin, Chen, Mary M., Ho, Liem, inventor; Target Therapeutics, Inc. (Fremont, CA), assignee. Stable coil designs. United States2001.

9. White JB, Ken CG, Cloft HJ, Kallmes DF. Coils in a nutshell: a review of coil physical properties. AJNR American journal of neuroradiology. 2008;29(7):1242–6. doi: 10.3174/ajnr.A1067 18417605.

10. Eddleman CS, Welch BG, Vance AZ, Rickert KL, White JA, Pride GL, et al. Endovascular coils: properties, technical complications and salvage techniques. Journal of neurointerventional surgery. 2013;5(2):104–9. doi: 10.1136/neurintsurg-2012-010263 22345145.

11. Wahl AM. Mechanical springs: Penton Publishing Company; 1944.

12. Cowper G. The shear coefficient in Timoshenko’s beam theory. Journal of applied mechanics. 1966;33(2):335–40.

13. Antiga L, Piccinelli M, Botti L, Ene-Iordache B, Remuzzi A, Steinman DA. An image-based modeling framework for patient-specific computational hemodynamics. Medical & biological engineering & computing. 2008;46(11):1097–112. doi: 10.1007/s11517-008-0420-1 19002516.

14. Abaqus 2016 Documentation Collection [Internet]. Dassault Systèmes Simulia Corp. 2016.

15. Moret J, Cognard C, Weill A, Castaings L, Rey A. Reconstruction technic in the treatment of wide-neck intracranial aneurysms. Long-term angiographic and clinical results. Apropos of 56 cases. Journal of neuroradiology Journal de neuroradiologie. 1997;24(1):30–44. 9303942

16. Paliwal N, Damiano RJ, Varble NA, Tutino VM, Dou Z, Siddiqui AH, et al. Methodology for Computational Fluid Dynamic Validation for Medical Use: Application to Intracranial Aneurysm. J Biomech Eng. 2017;139(12). Epub 2017/09/01. doi: 10.1115/1.4037792 28857116; PubMed Central PMCID: PMC5686786.

17. Sadasivan C, Brownstein J, Patel B, Dholakia R, Santore J, Al-Mufti F, et al. In Vitro Quantification of the Size Distribution of Intrasaccular Voids Left after Endovascular Coiling of Cerebral Aneurysms. Cardiovasc Eng Technol. 2013;4(1):63–74. Epub 2013/05/21. doi: 10.1007/s13239-012-0113-7 23687520; PubMed Central PMCID: PMC3653595.

18. Ohta M, Handa A, Iwata H, Rüfenacht DA, Tsutsumi S. Poly-vinyl alcohol hydrogel vascular models for in vitro aneurysm simulations: the key to low friction surfaces. Technology and Health Care. 2004;12(3):225–33. 15328451

19. Sadasivan C, Swartwout E, Kappel AD, Woo HH, Fiorella DJ, Lieber BB. In vitro measurement of the permeability of endovascular coils deployed in cerebral aneurysms. Journal of neurointerventional surgery. 2018. Epub 2018/01/05. doi: 10.1136/neurintsurg-2017-013481 29298858.

20. Chueh JY, Vedantham S, Wakhloo AK, Carniato SL, Puri AS, Bzura C, et al. Aneurysm permeability following coil embolization: packing density and coil distribution. Journal of neurointerventional surgery. 2015;7(9):676–81. doi: 10.1136/neurintsurg-2014-011289 25031179; PubMed Central PMCID: PMC4552888.

21. Plotnick RE, Gardner RH, O'Neill RV. Lacunarity indices as measures of landscape texture. Landscape ecology. 1993;8(3):201–11.

22. Leng X, Wang Y, Xu J, Jiang Y, Zhang X, Xiang J. Numerical simulation of patient-specific endovascular stenting and coiling for intracranial aneurysm surgical planning. Journal of translational medicine. 2018;16(1):208. doi: 10.1186/s12967-018-1573-9 30031395

23. Morales HG, Larrabide I, Geers AJ, Dai D, Kallmes DF, Frangi AF. Analysis and quantification of endovascular coil distribution inside saccular aneurysms using histological images. Journal of neurointerventional surgery. 2013;5 Suppl 3:iii33–7. doi: 10.1136/neurintsurg-2012-010456 22914746; PubMed Central PMCID: PMC3910323.

24. Morales HG, Larrabide I, Geers AJ, San Roman L, Blasco J, Macho JM, et al. A virtual coiling technique for image-based aneurysm models by dynamic path planning. IEEE Trans Med Imaging. 2013;32(1):119–29. doi: 10.1109/TMI.2012.2219626 23008248.

25. Sun J, Lee K, Lee H. Comparison of implicit and explicit finite element methods for dynamic problems. Journal of Materials Processing Technology. 2000;105(1–2):110–8.

26. Hoi Y, Woodward SH, Kim M, Taulbee DB, Meng H. Validation of CFD simulations of cerebral aneurysms with implication of geometric variations. J Biomech Eng. 2006;128(6):844–51. doi: 10.1115/1.2354209 17154684; PubMed Central PMCID: PMC2754174.

27. Mitsos AP, Kakalis NM, Ventikos YP, Byrne JV. Haemodynamic simulation of aneurysm coiling in an anatomically accurate computational fluid dynamics model: technical note. Neuroradiology. 2008;50(4):341–7. doi: 10.1007/s00234-007-0334-x 18043912.

28. Levitt MR, Barbour MC, Rolland du Roscoat S, Geindreau C, Chivukula VK, McGah PM, et al. Computational fluid dynamics of cerebral aneurysm coiling using high-resolution and high-energy synchrotron X-ray microtomography: comparison with the homogeneous porous medium approach. Journal of neurointerventional surgery. 2016. doi: 10.1136/neurintsurg-2016-012479 27405312.

29. Cebral JR, Lohner R. Efficient simulation of blood flow past complex endovascular devices using an adaptive embedding technique. IEEE Trans Med Imaging. 2005;24(4):468–76. doi: 10.1109/tmi.2005.844172 15822805.

30. Morales HG, Larrabide I, Kim M, Villa-Uriol MC, Macho JM, Blasco J, et al. Virtual coiling of intracranial aneurysms based on dynamic path planning. Medical image computing and computer-assisted intervention: MICCAI International Conference on Medical Image Computing and Computer-Assisted Intervention. 2011;14(Pt 1):355–62. doi: 10.1007/978-3-642-23623-5_45 22003637.

31. Chen Z, Chen D, Wang X, Damiano RJ, Meng H, Xu J. Novel geometric approach for virtual coiling. Theoretical computer science. 2018;734:3–14. doi: 10.1016/j.tcs.2018.02.013 30250355

32. Sluzewski M, van Rooij WJ, Slob MJ, Bescos JO, Slump CH, Wijnalda D. Relation between aneurysm volume, packing, and compaction in 145 cerebral aneurysms treated with coils. Radiology. 2004;231(3):653–8. doi: 10.1148/radiol.2313030460 15118115.

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