Towards clinical translation of augmented orthopedic surgery: from pre-op CT to intra-op x-ray via RGBD sensing

Pre-operative CT data is available for several orthopedic and trauma interventions, and is mainly used to identify injuries and plan the surgical procedure. In this work we propose an intuitive augmented reality environment allowing visualization of pre-operative data during the intervention, with an overlay of the optical information from the surgical site. The pre-operative CT volume is first registered to the patient by acquiring a single C-arm X-ray image and using 3D/2D intensity-based registration. Next, we use an RGBD sensor on the C-arm to fuse the optical information of the surgical site with patient pre-operative medical data and provide an augmented reality environment. The 3D/2D registration of the pre- and intra-operative data allows us to maintain a correct visualization each time the C-arm is repositioned or the patient moves. An overall mean target registration error (mTRE) and standard deviation of 5.24 ± 3.09 mm was measured averaged over 19 C-arm poses. The proposed solution enables the surgeon to visualize pre-operative data overlaid with information from the surgical site (e.g. surgeon’s hands, surgical tools, etc.) for any C-arm pose, and negates issues of line-of-sight and long setup times, which are present in commercially available systems.

[1]  R Fahrig,et al.  Marker-free motion correction in weight-bearing cone-beam CT of the knee joint. , 2016, Medical physics.

[2]  Jos Vander Sloten,et al.  Segmentation accuracy of long bones. , 2014, Medical engineering & physics.

[3]  Leo Joskowicz,et al.  Computer Aided Orthopaedic Surgery: Incremental shift or paradigm change? , 2016, Medical Image Anal..

[4]  Wen Gao,et al.  Image Matching by Normalized Cross-Correlation , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[5]  Gerard A Engh,et al.  Learning curve with minimally invasive unicompartmental knee arthroplasty. , 2008, The Journal of arthroplasty.

[6]  Simon Weidert,et al.  Technical note: on-the-fly augmented reality for orthopaedic surgery using a multi-modal fiducial , 2018, Medical Imaging.

[7]  Nassir Navab,et al.  Can real-time RGBD enhance intraoperative Cone-Beam CT? , 2017, International Journal of Computer Assisted Radiology and Surgery.

[8]  N. Glossop,et al.  Advantages of optical compared with electromagnetic tracking. , 2009, The Journal of bone and joint surgery. American volume.

[9]  Russell H. Taylor,et al.  Tracker-on-C for cone-beam CT-guided surgery: evaluation of geometric accuracy and clinical applications , 2012, Medical Imaging.

[10]  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.

[11]  H. Goitz,et al.  Percutaneous screw fixation of acetabular fractures with CT guidance: preliminary results of a new technique. , 1992, AJR. American journal of roentgenology.

[12]  A. Kimura,et al.  Whole-body computed tomography is associated with decreased mortality in blunt trauma patients with moderate-to-severe consciousness disturbance: A multicenter, retrospective study , 2013, The journal of trauma and acute care surgery.

[13]  M. Powell The BOBYQA algorithm for bound constrained optimization without derivatives , 2009 .

[14]  Simon Weidert,et al.  Preclinical usability study of multiple augmented reality concepts for K-wire placement , 2016, International Journal of Computer Assisted Radiology and Surgery.

[15]  Peter Kazanzides,et al.  Intraoperative Image-based Multiview 2D/3D Registration for Image-Guided Orthopaedic Surgery: Incorporation of Fiducial-Based C-Arm Tracking and GPU-Acceleration , 2012, IEEE Transactions on Medical Imaging.

[16]  Nassir Navab,et al.  Calibration of RGBD camera and cone-beam CT for 3D intra-operative mixed reality visualization , 2016, International Journal of Computer Assisted Radiology and Surgery.

[17]  Nassir Navab,et al.  Camera Augmented Mobile C-Arm (CAMC): Calibration, Accuracy Study, and Clinical Applications , 2010, IEEE Transactions on Medical Imaging.

[18]  Nassir Navab,et al.  Plan in 2-D, execute in 3-D: an augmented reality solution for cup placement in total hip arthroplasty , 2018, Journal of medical imaging.

[19]  D. Schaad,et al.  Minimally invasive total knee arthroplasty compared with traditional total knee arthroplasty. Assessment of the learning curve and the postoperative recuperative period. , 2007, The Journal of bone and joint surgery. American volume.

[20]  Nassir Navab,et al.  Pose-aware C-arm for automatic re-initialization of interventional 2D/3D image registration , 2017, International Journal of Computer Assisted Radiology and Surgery.