Image-Based 3-D Spinal Navigation Using Intra-Operative Fluoroscopic Registration R. Grzeszczuk, S. Chin, M. Murphy, R. Fahrig, H. Abbasi, D. Kim, J.R. Adler, Jr. R. Shahidi, Stanford University School of Medicine

System Overview A fluoroscopic navigation system that uses pre-operative diagnostic scans (e.g., CT, MRI) to track surgical tools in the context of a 3D patient-specific anatomical model. 3D FluoroNav Picture goes here

Clinical Motivation Targeted procedures Endoscopic lumbar diskectomy Thorasic diskectomy, tumor resection, instrumentation Complex spinal reconstruction Percutaneous pedical screw fixation Laproscopic lumbar inter-body fusion Motivating factors High failure rates (as high as 40% reported) Pursuit of more intuitive guidance methods Pursuit of minimal invasiveness

3D vs. Planar Navigation Pro: 3D provides a more intuitive visualization of spatially complex structures Con: 3D is more challenging technically: requires registration 3D NavigationPlanar Navigation

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System Components C-Arm camera tracking Relative camera positions Imaging system modeling Intrinsic camera calibration Coarse registration Extrinsic camera calibration High accuracy registration Radiographic method

Intrinsic Camera Calibration Critical imaging parameters: Estimate focal length Estimate image center Eliminate pin-cushion distortion All imaging parameters are sensitive to the orientation within the gravitational field as well as Earth and external magnetic fields, thus requiring per-frame calibration

Extrinsic Camera Calibration The positions and orientations of the camera that produced the stereo pair can be estimated using conventional photogrammetric techniques The estimate is inherently inaccurate due to parallax errors and it cannot be used for the purposes of high accuracy tracking in 3D The estimate is sufficient as a starting point for a registration method

High Accuracy Radiographic Registration Start with an initial guess of the CT position and orientation with respect to the camera positions Compute a pair of simulated fluoroscopic images by projecting the CT volume If both simulated images are exactly the same as the actual fluoroscopic images, the solution was found Otherwise, translate/rotate CT and repeat till convergence is reached

Radiographic Registration Camera A Camera B ComputedFluoroDifference

Advantages of Radiographic Registration High theoretical accuracy: Translational +/- 0.2 mm Rotational +/- 0.5 deg Does not require the structure of interest to be exposed: suitable for minimally invasive approaches Can be made automatic Can be made to work on fiducials as well as feature-less anatomical structures Can be made to work on deformable structures

Conventional 3D Methodology Multi-stage registration Manual digitization of anatomical landmarks and/or surfaces Requires full exposure of the structure Cumbersome, time consuming, limited accuracy Optical tracking for navigation Limited to open surgery or “deep” tracking of rigid effectors

Conventional 2D Methodology Unassisted free-hand fluoroscopy labor intensive and tedious relatively high radiation exposure counter-intuitive visualization for guidance Computer-assisted fluoroscopy streamlines workflow shows several views simultaneously can track tools on pre-acquired projections counter-intuitive visualization for guidance

Differentiating Technology Robust and rapid registration technique Percutaneously implanted fiducials Skeletal anatomy Adaptable to articulated structures Fluoroscopic tracking Can track internal structures and flexible tools More effective use of C-Arm for free hand navigation Less radiation to patient and staff Computation of new virtual views (including axial) Better visualization of spatially complex structures

Summary We proposed a computer-assisted tool that should: facilitate better decision making improve the accuracy reduce risk minimize the invasiveness shorten surgery time for a broad range of neurosurgical and orthopaedic procedures of the spine