A BrainRetraction Correction Framework Applying Extended Finite Element Method and Validation
1 Digital Medical Research Centre, Fudan University, Shanghai 200032, China
2 Shanghai Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention (MICCAI), Shanghai 200032, China
Abstract：Brain retraction severely decreases the accuracy and reliability of Image Guided Navigation Systems (IGNS). In this paper, we proposed a linear elastic framework in which extended finite element method (XFEM) was used for the correction of the brain retraction. We performed a quantitative assessment of brain retraction framework by the displacement of implanted metal makers in one brain phantom. The average correction error of our XFEM framework varied between 0.3mm and 0.5mm (mean 0.4mm). And the average correction accuracy varied between 83.1% and 87.5% (mean 85.9%). The results of the experiments indicated this framework had a great potential to correct brain retraction.
［1］Zhang C, Wang M, Song Z. A braindeformation framework based on a linear elastic model and evaluation using clinical data［J］. IEEE Trans Biomed Eng,2011,58(1):191-199.
［2］Vigneron LM, Duflot MP, Robe PA, et al. 2D XFEMbased modeling of retraction and successive resections for preoperative image update［J］. Comput Aided Surg,2009,14(1-3):1-20.
［3］Ferrant M, Nabavi A, Macq B, et al. Registration of 3D intraoperative MR images of the brain using a finiteelement biomechanical model［J］. IEEE Trans Med Imaging,2001,20(12):1384-1397.
［4］Miga MI, Roberts DW, Kennedy FE, et al. Modeling of retraction and resection for intraoperative updating of images［J］. Neurosurgery, 2001,49(1):75-84, 84-85.
［5］Lamprich BK, Miga MI. Analysis of modelupdated MR images to correct for brain deformation due to tissue retraction［C］ // Medical Imaging 2003: Visualization, ImageGuided Procedures, and Display. San Diego: SPIE, 2003:552-560.
［6］Sun H, Kennedy F, Carlson E, et al. Modeling of Brain Tissue Retraction Using Intraoperative Data［C］ //Barillot C, Haynor D, Hellier P,eds. Medical Image Computing and ComputerAssisted Intervention–MICCAI 2004. Berlin Heidelberg: Springer,2004: 3217,225-233.
［7］Duflot M, NguyenDang H. A meshless method with enriched weight functions for fatigue crack growth［J］. International Journal for Numerical Methods in Engineering, 2004,59(14):1945-1961.
［8］Mos N. Dolbow J, Belytschko T. A finite element method for crack growth without remeshing［J］. International Journal for Numerical Methods in Engineering,1999,46(1):131-150.
［9］Vigneron LM, Noels L, Warfield SK, et al. Serial FEM/XFEMbased update of preoperative brain Images using intraoperative MRI［J］. Int J Biomed Imaging,2012,2012:872783.
［10］Vigneron LM, Warfield SK, Robe PA, et al. 3D XFEMbased modeling of retraction for preoperative image update ［J］. Comput Aided Surg, 2011,16(3):121-134.
［11］Wittek A, Hawkins T, Miller K. On the unimportance of constitutive models in computing brain deformation for imageguided surgery［J］. Biomech Model Mechanobiol,2009,8(1):77-84.
［12］Liu Y, Song Z. A robust brain deformation framework based on a finite element model in IGNS［J］. Int J Med Robot, 2008,4(2):146-157.
［13］Platenik LA, Miga MI, Roberts DW, et al. In vivo quantification of retraction deformation modeling for updated imageguidance during neurosurgery［J］. IEEE Trans Biomed Eng, 2002,49(8):823-835.
