Istrazivanja i projektovanja za privreduJournal of Applied Engineering Science

IMPROVED NUMERICAL MODEL OF THE ARTERIAL WALL APPLIED FOR SIMULATIONS OF STENT DEPLOYMENT WITHIN PATIENT-SPECIFIC CORONARY ARTERIES


DOI: 10.5937/jaes0-27805 
This is an open access article distributed under the CC BY 4.0
Creative Commons License

Tijana Djukic*
Bioengineering Research and Development Center, BioIRC, Kragujevac, Serbia

University of Kragujevac, Institute for Information Technologies, Kragujevac, Serbia

Igor Saveljic
Bioengineering Research and Development Center, BioIRC, Kragujevac, Serbia

University of Kragujevac, Institute for Information Technologies, Kragujevac, Serbia

Gualtiero Pelosi
Institute of Clinical Physiology, National Research Council, Pisa, Italy

Oberdan Parodi
Institute of Clinical Physiology, National Research Council, Pisa, Italy

Nenad Filipovic
Bioengineering Research and Development Center, BioIRC, Kragujevac, Serbia

University of Kragujevac, Faculty of Engineering, Department of Applied Mechanics and Automatic Control, Kragujevac, Serbia

Arterial stenosis is the obstruction of normal blood flow that is caused by atherosclerosis. One of the endovascular treatment procedures in this case is the implantation of a stent to restore the blood flow. This study presented an improved numerical model that can precisely simulate the deformation of human arterial wall in coronary arteries, during the stent deployment process. The new model considered the arterial wall as an incompressible, isotropic and hyperelastic material. The material coefficients were defined according to experimental values presented in literature. The accuracy of the numerical model was investigated by comparing the results with follow up data obtained in clinical examination. The small relative and standard deviation error prove that this numerical model can be used to assist clinicians in decision making and treatment planning with reliable predictions of the outcome of the stent deployment procedure.

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The research presented in this study was part of the project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 689068 - SMARTool. This article reflects only the author's view. The Commission is not responsible for any use that may be made of the information it contains. This work was also supported by the Ministry of Education, Science and Technological Development of the Republic of Serbia [ID 451-03-68/2020- 14/200378].

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