Human Blood Pressure Simulation for Stress Analysis in Model of Vasculature Using Photoelastic Effect
Carlos Tercero*1, 2, Seiichi Ikeda*1, Erick Tijerino*3, 2,
Motoki Matsushima*1, Toshio Fukuda*1, Makoto Negoro*4,
and Ikuo Takahashi*5
*1Micro-Nano Systems Engineering Department, Nagoya University, Furo-cho 1, Chikusa-ku, Nagoya 464-8603, Japan
*2Electronics Engineering Department, Del Valle de Guatemala University, 18 avenida 11-95 Zona 15, Guatemala City, Guatemala
*3Mechanical, Materials and Aerospace Engineering, University of Central Florida, 4000 Central Florida Blvd. Orlando, Florida 32816-2450, USA
*4Department of Neurosurgery, Fujita Health University, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Aichi 470-1192, Japan
*5Department of Neurosurgery, Anjo Kosei Hospital, 28 Higashi Hirokute, Anjo-cho, Anjo, Aichi 446-8602, Japan
Numerical criteria for evaluating stress on vasculature models have applications in evaluating medical tools and surgical skills enabling better endovascular surgery training and the development of better medical techniques and tools. We propose using the stress produced by blood pressure simulation in the vasculature model wall for this criterion and use photoelastic effect for measuring the principal stress magnitude component. We simulated human blood pressure with 5.6% average error and developed shielded urethane model of vasculature enabling water circulation and avoiding plastic deformation at pressures below 182 mmHg. We developed software to calculate model wall stress. We quantitatively compared in four ranges stress produced on the model wall by blood pressure simulation and a guide wire.
-  C. Murray and A. Lopez, “Alternative projections of mortality and disability by cause 1990-2020: Global Burden of Disease Study,” The Lancet, Vol.349, pp. 1498-1504, 1997.
-  K. Kunkler, “The role of Medical simulation: an overview,” Int. it Journal of Medical Robotics and Computer Assisted Surgery, Vol.2, pp. 203-210, 2006.
-  Y. Kawanabe, A. Sadato, W. Taki, and N. Hashimoto. “Endovascular Occlusion of Intracranial Aneurysms with Guglielmi Detachable Coils: Correlation Between Coil Packing Density and Coil Compaction,” Acta Neurochir, Vol.143, pp. 451-455, 2001.
-  S. Ikeda, C. Tercero, T. Fukuda, Y. Okada, F. Arai, M. Negoro, M. Hayakawa, and I. Takahashi, “Patient-Specific IVR Endovascular Simulator with Augmented Reality for Medical Training and Robot Evaluation,” Journal of Robotics and Mechatronics, Vol.20, No.3, pp. 441-448, 2008.
-  P. Serruys, P. de Jaegere, F. Kiemeneij, C. Macaya, W. Rutsch, G. Heyndrickx, H. Emanuelsson, J. Marco, V. Legrand, P. Materne, J. Belardi, U. Sigwart, A. Colombo, J. Goy, P. van den Heuvel, J. Delcan, and M. Morel, “A Comparison of Balloon-Expandable-Stent Implantation with Balloon Angioplasty in Patients with Coronary Artery Disease,” The New England Journal of Medicine, Vol.331, No.8, pp. 489-495, 1994.
-  S. Ikeda, F. Arai, T. Fukuda, M. Negoro, and K. Irie, “An in vitro patientspecific biological model of the cerebral artery reproduced with a membranous configuration for simulating endovascular intervention,” J. of Robotics and Mechatronics, Vol.17, No.3, pp. 327-333, 2005.
-  S. Ikeda, T. Fukuda, F. Arai, et al., “Patient-specific neurovascular simulator for evaluating the performance of medical robots and instruments,” in Proc. of the IEEE-ICRA, pp. 625-630, 2006.
-  C. Tercero, Y. Okada, S. Ikeda, T. Fukuda, K. Sekiyama, M. Negoro, and I. Takahashi. “Numerical evaluation method for catheter prototypes using photo-elastic stress analysis on patient-specific vascular model,” Int. Journal of Medical Robotics and Computer Assisted Surgery, Vol.3:4 pp. 349-354, 2007.
-  J. Panza, “High-Normal Blood Pressure more “High” than “Normal”,” N Engl J Med, Vol.345, No.18, pp. 1337-1340, 2001.
-  B. De Bruyne, J. Bartunek, S. K. Sys, et al., “Simultaneous coronary pressure and flow velocity measurements in humans,” Circulation, Vol.94, pp. 1842-1849, 1996.
-  A. J. Ebenal, S. Vasana, C. Clinton, D. Cox, and T. Shine, “Arterial Blood Pressure System Modeling and Signal Analysis,” in Proc. IEEE-CIRA, pp. 386-391, 2007.
-  S. Tong and D. Yang, “Rotor Profiles Synthesis for Lobe Pumps With Given Flow Rate Functions,” Journal of Mechanical Design, Vol.127, pp. 287-294, 2005.
-  A. Kuske and G. Robertson, “Photoelastic Stress Analysis,” A Wiley-Interscience Publication, pp. 87-109, 263-274, 1974.
-  Y. Okada, S. Ikeda, T. Fukuda, F. Arai, M. Negoro, and I. Takahashi, “Photoelastic Stress Analysis on Patient-Specific Anatomical Model of Cerebral Artery,” in Proc. of the Int. Symposium on Micro-NanoMechatronics and Human Science, pp. 538-543, 2007.
-  M. Tanimoto, F. Arai, T. Fukuda, H. Iwata, K. Gotoh, M. Hashimoto, and M. Negoro, “Study on Micro Force Sensor for Minimum Invasive Surgery,” Trans. of the Japan Soc. of Mech. Eng., C 64-620, JSME, pp. 150-155, 1998.
-  C. Tercero, S. Ikeda, T. Fukuda, K. Sekiyama, Y. Okada, T. Uchiyama, M. Negoro, and I. Takahashi, “Robot Manipulation and Guidance Using Magnetic Motion Capture Sensor and a Rule-Based Controller,” Journal of Robotics and Mechatronics, Vol.20, No.1, pp. 151-158, 2008.
-  C. Tercero, S. Ikeda, T. Uchiyama, T. Fukuda, F. Arai, Y. Okada, Y. Ono, R. Hattori, T. Yamamoto, M. Negoro, and I. Takahashi, “Autonomous Catheter Insertion System using Magnetic Motion Capture Sensor for endovascular surgery,” Int. Journal of Medical Robotics and Computer Assisted Surgery, Vol.3:1, pp. 52-58, 2007.
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