Caracterización de tejido cerebral artificial utilizando Inverse-FEM para simular indentación y comprensión
Main Article Content
Keywords
inverse-FEM, Ensayo a Compresión, Indentación, Calibración de tejidos, Simuladores Quirúrgicos.
Resumen
Una simulación realista de la interacción tejido-herramienta es necesaria para desarrollar simuldores quirúrgicos, y la presición en modelos biomecánicos de tejidos es determinante para cumplir tal fin. Los trabajos previos han caracterizado las propiedades de tejidos blandos; sin embargo, ha faltado una validación apropiada de los resultados. En este trabajo se determinaron las propiedades mecánicas de un tejido blando minimizando la diferencia entre las mediciones experimentales y la solución analítica o simulada del problema. Luego, fueron seleccionados los parámetros que mejor se ajustaron a los datos experimentales para simular una compresión con fricción y la indentación de una aguja con punta plana. Se concluye que el inverse-FEM permite la precisa estimación de las propiedades del material. Además, estos resultados fueron validados con varias interacciones tejido-herramienta sobre el mismo espécimen.
MSC: 74S05
Descargas
Referencias
[2] S. Misra, K. J. Macura, K. T. Ramesh, A. M. Okamura, “The Importance of Organ Geometry and Boundary Constraints for Planning of Medical Interventions”, Med Eng Phys, vol. 31, n.o 2, pp. 195-206, mar. 2009. Referenced in 11
[3] N. Abolhassani, R. Patel, M. Moallem, “Needle insertion into soft tissue: A survey”, Medical Engineering & Physics, vol. 29, n.o 4, pp. 413-431, may 2007. Referenced in 11, 26
[4] I. Brouwer, J. Ustin, L. Bentley, A. Sherman, N. Dhruv, F. Tendick, “Measuring In Vivo Animal Soft Tissue Properties for Haptic Modeling in Surgical Simulation”, in Stud Health Technol Inform, 2001, pp. 69-74. Referenced in 11, 12
[5] M. Kauer, V. Vuskovic, J. Dual, G. Szekely, y M. Bajka, “Inverse finite element characterization of soft tissues”, Medical Image Analysis, vol. 6, n.o 3, pp. 275-287, sep. 2002. Referenced in 11, 12
[6] S. P. DiMaio y S. E. Salcudean, “Needle insertion modelling and simulation”, in Robotics and Automation, 2002. Proceedings. ICRA ’02. IEEE International Conference on, 2002, vol. 2, pp. 2098 - 2105 vol.2. Referenced in 11, 12
[7] J. Kim y M. Srinivasan, “Characterization of Viscoelastic Soft Tissue Properties from In Vivo Animal Experiments and Inverse FE Parameter Estimation”, in Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005, vol. 3750, J. Duncan y G. Gerig, Eds. Springer Berlin / Heidelberg, 2005, pp.599-606. Referenced in 11, 12
[8] C. Dechwayukul y W. Thongruang, “Compressive modulus of adhesive bonded rubber block”, Songklanakarin Journal of Science and Technology, vol. 30, n.o 2, pp. 221-225, 2008. Referenced in 12, 21
[9] M. Kaneko, C. Toya, y M. Okajima, “Active Strobe Imager for Visualizing Dynamic Behavior of Tumors”, in Robotics and Automation, 2007 IEEE International Conference on, 2007, pp. 3009 -3014. Referenced in 12
[10] A. M. Okamura, C. Simone, y M. D. O’Leary, “Force modeling for needle insertion into soft tissue”, Biomedical Engineering, IEEE Transactions on, vol. 51, n.o 10, pp. 1707 -1716, oct. 2004. Referenced in 12, 26
[11] K. Miller, A. Wittek, G. Joldes, A. Horton, T. Dutta-Roy, J. Berger, y L. Morriss, “Modelling brain deformations for computer-integrated neurosurgery”, International Journal for Numerical Methods in Biomedical Engineering, vol. 26, n.o 1, pp. 117-138, 2010. Referenced in 12
[12] M. Kohandel, S. Sivaloganathan, G. Tenti, y J. M. Drake, “The constitutive properties of the brain parenchyma: Part 1. Strain energy approach”, Medical Engineering & Physics, vol. 28, n.o 5, pp. 449-454, jun. 2006. Referenced in 12, 16
[13] K. Sangpradit, H. Liu, L. D. Seneviratne, y K. Althoefer, “Tissue identification using inverse Finite Element analysis of rolling indentation”, in Robotics and Automation, 2009. ICRA ’09. IEEE International Conference on, 2009, pp. 1250-1255. Referenced in 12
[14] Y. C. Fung, Biomechanics: Mechanical Properties of Living Tissues, Second Edition, 2nd ed. Springer, 1993. Referenced in 12
[15] Y. C. Fung, Foundations of Solid Mechanics, 2nd Printing. Prentice Hall, 1965. Referenced in 12
[16] A. F. Bower, Applied Mechanics of Solids, 1.a ed. CRC Press, 2009. Referenced in 12, 14, 17
[17] N. Famaey y J. V. Sloten, “Soft tissue modelling for applications in virtual surgery and surgical robotics”, Computer Methods in Biomechanics and Biomedical Engineering, vol. 11, n.o 4, pp. 351-366, 2008. Referenced in 13
[18] G. Franceschini, D. Bigoni, P. Regitnig, y G. A. Holzapfel, “Brain tissue deforms similarly to filled elastomers and follows consolidation theory”, Journal of the Mechanics and Physics of Solids, vol. 54, n.o 12, pp. 2592-2620, dic. 2006. Referenced in 15, 16
[19] H. Girnary, “BRAIN PHANTOM PROJECT”, dic. 2007. Referenced in 15
[20] H. O. Altamar, R. E. Ong, C. L. Glisson, D. P. Viprakasit, M. I. Miga, S. D. Herrell, y R. L. Galloway, “Kidney Deformation and Intraprocedural Registration: A Study of Elements of Image-Guided Kidney Surgery”, Journal of Endourology, vol. 25, n.o 3, pp. 511-517, mar. 2011. Referenced in 15
[21] A. Deram, V. Luboz, E. Promayon, y Y. Payan, “Using a 3D biomechanical model to improve a light aspiration device for in vivo soft tissue characterisation”, Computer Methods in Biomechanics and Biomedical Engineering, vol. 15, n.o sup1, pp. 41-43, 2012. Referenced in 15
[22] E. Promayon, V. Luboz, G. Chagnon, T. Alonso, D. Favier, C. Barthod, y Y. Payan, “Comparison of LASTIC (Light Aspiration device for in vivo Soft TIssue Characterization) with classic Tensile Tests.”, in Proceedings of the EU-ROMECH534 Colloquium., France, 2012, pp. 75-76. Referenced in 15
[23] D. Hendrickson y F. Bellezo, “Surgical Simulator, Simulated Organs andMethod of Making Same”, . Referenced in 15
[24] K. Miller y K. Chinzei, “Constitutive modelling of brain tissue: Experiment and theory”, Journal of Biomechanics, vol. 30, n.o 11-12, pp. 1115-1121, nov. 1997. Referenced in 16
[25] K. Miller, “Constitutive model of brain tissue suitable for finite element analysis of surgical procedures”, Journal of Biomechanics, vol. 32, n.o 5, pp. 531-537, may 1999. Referenced in 16
[26] K. Miller, K. Chinzei, G. Orssengo, y P. Bednarz, “Mechanical properties of brain tissue in-vivo: experiment and computer simulation”, Journal of Biomechanics, vol. 33, n.o 11, pp. 1369-1376, nov. 2000. Referenced in 16
[27] K. I. Romanov, “The drucker stability of a material”, Journal of Applied Mathematics and Mechanics, vol. 65, n.o 1, pp. 155-162, feb. 2001. Referenced in 17
[28] A. N. Gent y E. A. Meinecke, “Compression, bending, and shear of bonded rubber blocks”, Polymer Engineering & Science, vol. 10, n.o 1, pp. 48-53, 1970. Referenced in 21
[29] J. G. Williams y C. Gamonpilas, “Using the simple compression test to determine Young’s modulus, Poisson’s ratio and the Coulomb friction coefficient”, International Journal of Solids and Structures, vol. 45, n.o 16, pp. 4448-4459, ago. 2008. Referenced in 21
[30] “Friction - DiracDelta Science & Engineering Encyclopedia”. [Online]. Available:
www.diracdelta.co.uk/science/source/f/r/ .
Referenced in 21
[31] “Coefficients of Friction for Steel”. [Online]. Available: hypertextbook.com/facts/2005/steel.shtml [Accessed: mar-2011].
Referenced in 21
[32] “Coefficient of Friction”. [Online]. Available: http://buildingcriteria2.tpub.com/ufc 4 152 01/ufc 4 152 010141.htm [Accessed: mar-2011]. Referenced in 21