Modeling of the dynamics of vascular embolization by using porous media for the design of injection robots of embolic agents.

Journal: Medical engineering & physics
PMID:

Abstract

Embolization is the prevailing therapy for tumor-targeting, anti-organ hyperfunction, and hemostasis. However, the injection of embolic agents largely depends on the experiences of doctors as assisted by X-ray, which will negate the health of the doctor. To avail embolization therapy feasible even in hospitals without experienced doctors and to prevent the doctors from exposion to X-ray, robotization is a promising alternative. To these ends, building the relationship between physiological parameters and hemodynamic parameters during embolization is crucial. This study takes the renal artery-kidney system of rabbits as the model case to investigate the dynamics of vascular embolization by numerical simulation using porous media for injection of embolic agents. The capillaries at the embolic site inside the kidney are modeled as porous media. The flow from the artery to the vein through the porous media is assumed as a viscous resistance fluid. The resistance, which increases with the increasing degree of embolization, is approached by CFD simulations. According to simulation results, a prediction model of flow resistance is established, enabling building the control law of an embolic agents injection robot. Experimental tests provide physical geometries and relevant parameters for the simulations as well as caliber to verify the simulation results. It is demonstrated that the currently proposed prediction model reflects the relationship between embolic agent injection and hemodynamic parameters reliably, enabling quantitative assessment of the degree of embolization with local blood pressure in the artery of the organ.

Authors

  • Dongcheng Ren
    Academy for Engineering and Technology, Fudan University, 220 Handan Rd., Shanghai,China; Shanghai Engineering Research Center of AI & Robotics, 539 Handan Rd., Shanghai,China; Engineering Research Center of AI & Robotics, Ministry of Education, 539 Handan Rd., Shanghai,China.
  • Jiasheng Li
    State Key Laboratory on Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, 130012 Changchun, China. Electronic address: jali17@mails.jlu.edu.cn.
  • Bo Zhou
    Department of Neurology, The Third People's Hospital of Yibin, Yibin, China.
  • Shijie Guo
  • Baolei Guo
    Department of Vascular Surgery, Fudan University Zhongshan Hospital, 180 Fenglin Rd., Shanghai,China; National Clinical Research Center for Intervenional Medicine, 180 Fenglin Rd., Shanghai,China. Electronic address: guo.baolei@zs-hospital.sh.cn.