A Statistical Motion Model Based on Biomechanical Simulations for Data Fusion during Image-Guided Prostate Interventions

A method is described for generating a patient-specific, statistical motion model (SMM) of the prostate gland. Finite element analysis (FEA) is used to simulate the motion of the gland using an ultrasound-based 3D FE model over a range of plausible boundary conditions and soft-tissue properties. By applying principal component analysis to the displacements of the FE mesh node points inside the gland, the simulated deformations are then used as training data to construct the SMM. The SMM is used to both predict the displacement field over the whole gland and constrain a deformable surface registration algorithm, given only a small number of target points on the surface of the deformed gland. Using 3D transrectal ultrasound images of the prostates of five patients, acquired before and after imposing a physical deformation, to evaluate the accuracy of predicted landmark displacements, the mean target registration error was found to be less than 1.9 mm.

[1]  Pierre Hellier,et al.  Level Set Methods in an EM Framework for Shape Classification and Estimation , 2004, International Conference on Medical Image Computing and Computer-Assisted Intervention.

[2]  A. D'Amico,et al.  Evaluation of three-dimensional finite element-based deformable registration of pre- and intraoperative prostate imaging. , 2001, Medical physics.

[3]  Edward L. Chaney,et al.  Automated Finite-Element Analysis for Deformable Registration of Prostate Images , 2007, IEEE Transactions on Medical Imaging.

[4]  Ron Kikinis,et al.  Medical Image Computing and Computer-Assisted Intervention — MICCAI 2002 , 2002, Lecture Notes in Computer Science.

[5]  P. Thomas Fletcher,et al.  Prostate Shape Modeling Based on Principal Geodesic Analysis Bootstrapping , 2004, MICCAI.

[6]  Graeme P. Penney,et al.  Use of a CT statistical deformation model for multi-modal pelvic bone segmentation , 2008, SPIE Medical Imaging.

[7]  Michael G Herman,et al.  Prostate position relative to pelvic bony anatomy based on intraprostatic gold markers and electronic portal imaging. , 2005, International journal of radiation oncology, biology, physics.

[8]  Ken Goldberg,et al.  Registration of MR prostate images with biomechanical modeling and nonlinear parameter estimation. , 2006, Medical physics.

[9]  Russell H. Taylor,et al.  A Combined Statistical and Biomechanical Model for Estimation of Intra-operative Prostate Deformation , 2002, MICCAI.

[10]  Y Chi,et al.  A material sensitivity study on the accuracy of deformable organ registration using linear biomechanical models. , 2006, Medical physics.

[11]  T. Byrne,et al.  A review of prostate motion with considerations for the treatment of prostate cancer. , 2005, Medical dosimetry : official journal of the American Association of Medical Dosimetrists.