1. Minimally-Invasive Approach to Pelvic Osteolysis Srinivas Prasad, Ming Li, Nicholas Ramey Final Presentation May 10, 2001

2. Project Overview

4. Project Components Project 1 Pre-Operative Modeling Trajectory Planning Intra-Operative Registration Robotically Controlled Cannula Placement Project 2 Lesion Evacuation Cavity Filling

5. Deliverables Minimal: 1.Pre-Op Pelvic Modeling and Trajectory Planning Software 2.Intra-Operative Pelvis Registration and Tracking Software/Hardware 3.Robotically Controlled Drill Guide with Trackable Drill 4.1.0 – 1.5 cm diameter manually introduced cannula with retractable spear-tip 5.Passive cannula holder Expected: 3a.Robotically Inserted Cannula with Robot-Cannula Interface Maximal: 1b.Pre-Op GUI-Based Trajectory Planning Software 6.Methods and Instruments for lesion visualization, excavation and filling. 7.Real-Time pelvic motion tracking and compensatory cannula position control. Completed Tasks Pending TasksDeferred/Deleted Tasks

6. Revised Schedule 2/22 Project Proposal Submission 2/23Meet with Andy, Jianhua, Rajesh for Reg. Strategy 2/25Completion of Pelvis Preparation and Mounting 2/26-2/30CT-scan of pelvis 4/2Completion of Image Processing 4/22Completion of 2D-3D Registration Software, F 4/22Completion of Robot Registration Software, F 4/29Completion of Cannula Design and Implementation 4/29Completion of Robot Control Software 4/29-5/11System Integration and Testing 5/11Final Presentation Completed before Checkpoint Completed after Checkpoint Pending Tasks Robot Fluoro Robot CT

7. Final Presentation Outline Developed Technologies –2D-3D Registration –Robot Registration –Robot Control Component Simulations –Slicer Interface –Image Processing and Registration Conclusions –Remaining Tasks –Obstacles/Dependencies –What We’ve Learned –Potential Future Evolution

8. 2D-3D Registration Input: Fiducial positions in 2D image (Fluoro) and 3D space (CT) Pick a 2D triangle abc and find all 3D triangles a’b’c’ that might match Compute the frames mapping a’b’c’ to abc Compute errors associated with each mapping Choose frame with minimal error and iterate to reduce error

9. Robot Registration Purpose: –To relate the CT Coordinate Space to the Robot Coordinate System. –This is represented by the transformation General Principles: –We use Fluoro Space as the common coordinate system. –We use two Fluoro poses to decrease registration error –We directly compute the best rigid transformation between points in robot space and their corresponding points in CT space.

10. Robot Registration

11. line 1 1 n 1 Pose 1 Robot CT p 1 p n p 1 p n

12. Robot Registration line 1 2 n 2 Pose 2 Robot CT line 1 1 n 1 Pose 1 Robot CT p 1 p n p 1 p n p 1 p n

13. Robot Registration For any given 1 ≤ i ≤ n : [ p i ] Robot = (x i, y i, z i ) Robot [ p i ] CT = intersect(, ) p i line i 2 i 1 i 1 i 2 = CBRT [ p 1 ] Robot [ p 2 ] Robot [ p 3 ] Robot... [ p 1 ] CT [ p 2 ] CT [ p 3 ] CT..., CBRT( ) = ComputeBestRigidTransformation( )

14. Robot Control Instrument holder Can be attached to the fifth joint of the Neuromate MRC Server and Neuromate Server provide kinematics class which can control the robot on Frame level * Goal: Move the robot to let the tip of the holder to the specific position and the holder itself in the orientation which meets the planned trajectory in robot coor. Keep the gesture of the holder

15. Robot Control What we know: T: the target position T in CT coor. A: a point A on the planned trajectory line in CT coor. d: distance of T to P (the target position of the tip of the holder in CT coor.) T A d P 1.Transfer all the coordinate in robot coor. We got 2. Position

16. Robot Control 3. Rotation The orientation of the holder as z axis in our target frame (1) (2) (3) (4) (5) Rotation: Target Frame: F(R,P) x z 0 T P y

17. Slicer Simulation Pre-Operative CT Volume Processing: –Pelvis Segmentation: (Thresholding Method) –Lesion Characterization –Trajectory Definition: Target and Origin Coordinates in CT coordinates, mm units. –Fiducial Finding: All fiducial coordinates in CT Coordinate system, mm units Output Saved to text files for intra-op use: –Fiducial Coordinates –Trajectory Coordinates

18. Intra-Operative Image Processing Simulation GUI for 2D Image Processing, built from Jianhua Yao’s Sample Interface Added Functionality –Bzostek Transformation –Fiducial Finding –2D-3D Registration file setup –2D-3D Registration

20. Remaining Tasks Human Pelvis Preparation –Create artificial osteolytic defects –Place multiple widely distributed pelvic fiducials –Obtain high quality CT and Fluoro Studies System Integration –Consolidate various software components into a single Workspace/Application System Testing –Evaluate System performance experimentally

21. Pelvis Preparation – Dr. Frassica Orthopaedic Instrumentation – Dr. Frassica CT and High-Resolution Fluoro Access – Neuroradiology JHH Experimental Apparatus – ERC Fluoroscopy Access – ERC Neuromate Robot – ERC Dependencies and Obstacles

22. What We’ve Learned Academically –Code writing and integration (Slicer, MFC, MRC, CIS, etc.) –Proper development technique (code maintenance, etc.) –A little Linear Algebra, a lot of CIS Project Management –Communication –Do your part, follow up –Stay involved with other components of the project –Be persistent –Use resources wisely and appreciatively

23. Potential Future Evolution True 2D-3D Registration Incorporation of fiducial-free 2D-3D registration algorithms would obviate the need for pre-imaging fiducial placement Component Tracking Incorporation of intra-operative optical or magnetic tracking systems would allow real-time component tracking, making the experimental apparatus more realistic Robotic Cannula Insertion Employment of Active Robots capable of inserting the cannula might increase consistency and accuracy of cannula placement