3D navigation and monitoring for spinal milling operation based on registration between multiplanar fluoroscopy and CT images

Milling operations in spinal surgery demand much experience and skill for the surgeon to perform the procedure safely. A 3D navigation method is introduced aiming at providing a monitoring system with enhanced safety and minimal intraoperative interaction. An automatic registration method is presented to establish the 3D-3D transformation between the preoperative CT images and a common reference system in the surgical space, and an intensity-based similarity metric adapted for the multi-planar configuration is introduced in the registration procedure. A critical region is defined for real-time monitoring in order to prevent penetration of the lamina and avoid violation of nerve structures. The contour of the spinal canal is reconstructed as the critical region, and different levels of warning limits are defined. During the milling procedure, the position of the surgical instrument relative to the critical region is provided with augmented display and audio warnings. Timely alarm is provided for surgeons to prevent surgical failure when the mill approaches the critical region. Our validation experiment shows that real-time 3D navigation and monitoring is advantageous for improving the safety of the milling operation.

[1]  Jaydev P. Desai,et al.  A biplanar fluoroscopic approach for the measurement, modeling, and simulation of needle and soft-tissue interaction , 2007, Medical Image Anal..

[2]  T. Lund,et al.  A new approach to computer-aided spine surgery: fluoroscopy-based surgical navigation , 2000, European Spine Journal.

[3]  Naoki Ishiguro,et al.  The simultaneous registration with CT-fluoro matching for spinal navigation surgery , 2004 .

[4]  Lik-Kwan Shark,et al.  A computationally efficient method for automatic registration of orthogonal x-ray images with volumetric CT data , 2008, Physics in medicine and biology.

[5]  田村 裕一 Surface-based registration accuracy of CT-based image-guided spine surgery , 2005 .

[6]  Jürgen Weese,et al.  An approach to 2D/3D registration of a vertebra in 2D X-ray fluoroscopies with 3D CT images , 1997, CVRMed.

[7]  Graeme P. Penney,et al.  Standardized evaluation methodology for 2-D-3-D registration , 2005, IEEE Transactions on Medical Imaging.

[8]  Tomaz Slivnik,et al.  3-D/2-D registration of CT and MR to X-ray images , 2003, IEEE Transactions on Medical Imaging.

[9]  L. Holly Image‐guided spinal surgery , 2006, The international journal of medical robotics + computer assisted surgery : MRCAS.

[10]  T. Lund,et al.  Computer-assisted spine surgery , 2000, European Spine Journal.

[11]  Tianmiao Wang,et al.  Force‐based control of a compact spinal milling robot , 2010, The international journal of medical robotics + computer assisted surgery : MRCAS.

[12]  D. Simon,et al.  Virtual Fluoroscopy: Computer-Assisted Fluoroscopic Navigation , 2001, Spine.

[13]  Rebecca Fahrig,et al.  A Flouroscopic X-Ray Registration Process for Three-Dimensional Surgical Navigation , 2000, MICCAI.

[14]  Jürgen Weese,et al.  A comparison of similarity measures for use in 2-D-3-D medical image registration , 1998, IEEE Transactions on Medical Imaging.

[15]  Rafael C. González,et al.  Local Determination of a Moving Contrast Edge , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[16]  Randy E. Ellis,et al.  Robust registration for computer-integrated orthopedic surgery: Laboratory validation and clinical experience , 2003, Medical Image Anal..

[17]  Kevin T. Foley,et al.  Image-guided spinal surgery , 2000 .

[18]  Andreas Hein,et al.  Concept and clinical evaluation of navigated control in spine surgery , 2003, Proceedings 2003 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM 2003).

[19]  David J. Hawkes,et al.  A Comparison of 2D-3D Intensity-Based Registration and Feature-Based Registration for Neurointerventions , 2002, MICCAI.

[20]  Leo Joskowicz,et al.  Effective Intensity-Based 2D/3D Rigid Registration between Fluoroscopic X-Ray and CT , 2003, MICCAI.

[21]  M. Shoham,et al.  BONE‐MOUNTED MINIATURE ROBOTIC GUIDANCE FOR PEDICLE SCREW AND TRANSLAMINAR FACET SCREW PLACEMENT: PART 2—EVALUATION OF SYSTEM ACCURACY , 2007, Neurosurgery.

[22]  Daniel Rueckert,et al.  Fast generation of digitally reconstructed radiographs using attenuation fields with application to 2D-3D image registration , 2005, IEEE Transactions on Medical Imaging.

[23]  Naoki Ishiguro,et al.  Simultaneous registration with ct-fluoro matching for spinal navigation surgery. A case report. , 2006, Nagoya journal of medical science.