Dong Chen1, Weisheng Chen2, Lipeng Huang2, Xuegang Feng2, Terry Peters3, Lixu Gu4. 1. School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China. 2. Department of Cardiothoracic Surgery, Affiliated East Hospital of Xiamen University, Fuzhou, China. 3. Robarts Research Institute, Western University, London, Canada. 4. School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China. gulixu@sjtu.edu.cn.
Abstract
PURPOSE: Accurate and real-time prediction of the lung and lung tumor deformation during respiration are important considerations when performing a peripheral biopsy procedure. However, most existing work focused on offline whole lung simulation using 4D image data, which is not applicable in real-time image-guided biopsy with limited image resources. In this paper, we propose a patient-specific biomechanical model based on the boundary element method (BEM) computed from CT images to estimate the respiration motion of local target lesion region, vessel tree and lung surface for the real-time biopsy guidance. METHODS: This approach applies pre-computation of various BEM parameters to facilitate the requirement for real-time lung motion simulation. The resulting boundary condition at end inspiratory phase is obtained using a nonparametric discrete registration with convex optimization, and the simulation of the internal tissue is achieved by applying a tetrahedron-based interpolation method depend on expert-determined feature points on the vessel tree model. A reference needle is tracked to update the simulated lung motion during biopsy guidance. RESULTS: We evaluate the model by applying it for respiratory motion estimations of ten patients. The average symmetric surface distance (ASSD) and the mean target registration error (TRE) are employed to evaluate the proposed model. Results reveal that it is possible to predict the lung motion with ASSD of [Formula: see text] mm and a mean TRE of [Formula: see text] mm at largest over the entire respiratory cycle. In the CT-/electromagnetic-guided biopsy experiment, the whole process was assisted by our BEM model and final puncture errors in two studies were 3.1 and 2.0 mm, respectively. CONCLUSION: The experiment results reveal that both the accuracy of simulation and real-time performance meet the demands of clinical biopsy guidance.
PURPOSE: Accurate and real-time prediction of the lung and lung tumor deformation during respiration are important considerations when performing a peripheral biopsy procedure. However, most existing work focused on offline whole lung simulation using 4D image data, which is not applicable in real-time image-guided biopsy with limited image resources. In this paper, we propose a patient-specific biomechanical model based on the boundary element method (BEM) computed from CT images to estimate the respiration motion of local target lesion region, vessel tree and lung surface for the real-time biopsy guidance. METHODS: This approach applies pre-computation of various BEM parameters to facilitate the requirement for real-time lung motion simulation. The resulting boundary condition at end inspiratory phase is obtained using a nonparametric discrete registration with convex optimization, and the simulation of the internal tissue is achieved by applying a tetrahedron-based interpolation method depend on expert-determined feature points on the vessel tree model. A reference needle is tracked to update the simulated lung motion during biopsy guidance. RESULTS: We evaluate the model by applying it for respiratory motion estimations of ten patients. The average symmetric surface distance (ASSD) and the mean target registration error (TRE) are employed to evaluate the proposed model. Results reveal that it is possible to predict the lung motion with ASSD of [Formula: see text] mm and a mean TRE of [Formula: see text] mm at largest over the entire respiratory cycle. In the CT-/electromagnetic-guided biopsy experiment, the whole process was assisted by our BEM model and final puncture errors in two studies were 3.1 and 2.0 mm, respectively. CONCLUSION: The experiment results reveal that both the accuracy of simulation and real-time performance meet the demands of clinical biopsy guidance.
Entities:
Keywords:
Biomechanical model; Biopsy; Boundary element method; Lung motion prediction
Authors: Keelin Murphy; Bram van Ginneken; Joseph M Reinhardt; Sven Kabus; Kai Ding; Xiang Deng; Kunlin Cao; Kaifang Du; Gary E Christensen; Vincent Garcia; Tom Vercauteren; Nicholas Ayache; Olivier Commowick; Grégoire Malandain; Ben Glocker; Nikos Paragios; Nassir Navab; Vladlena Gorbunova; Jon Sporring; Marleen de Bruijne; Xiao Han; Mattias P Heinrich; Julia A Schnabel; Mark Jenkinson; Cristian Lorenz; Marc Modat; Jamie R McClelland; Sébastien Ourselin; Sascha E A Muenzing; Max A Viergever; Dante De Nigris; D Louis Collins; Tal Arbel; Marta Peroni; Rui Li; Gregory C Sharp; Alexander Schmidt-Richberg; Jan Ehrhardt; René Werner; Dirk Smeets; Dirk Loeckx; Gang Song; Nicholas Tustison; Brian Avants; James C Gee; Marius Staring; Stefan Klein; Berend C Stoel; Martin Urschler; Manuel Werlberger; Jef Vandemeulebroucke; Simon Rit; David Sarrut; Josien P W Pluim Journal: IEEE Trans Med Imaging Date: 2011-05-31 Impact factor: 10.048
Authors: Frank C Detterbeck; Sandra Zelman Lewis; Rebecca Diekemper; Doreen Addrizzo-Harris; W Michael Alberts Journal: Chest Date: 2013-05 Impact factor: 9.410
Authors: Paul J Keall; Gig S Mageras; James M Balter; Richard S Emery; Kenneth M Forster; Steve B Jiang; Jeffrey M Kapatoes; Daniel A Low; Martin J Murphy; Brad R Murray; Chester R Ramsey; Marcel B Van Herk; S Sastry Vedam; John W Wong; Ellen Yorke Journal: Med Phys Date: 2006-10 Impact factor: 4.071
Authors: Daniel A Low; Michelle Nystrom; Eugene Kalinin; Parag Parikh; James F Dempsey; Jeffrey D Bradley; Sasa Mutic; Sasha H Wahab; Tareque Islam; Gary Christensen; David G Politte; Bruce R Whiting Journal: Med Phys Date: 2003-06 Impact factor: 4.071