1. Rigid Needles, Steerable Needles, and Optimal Beam Algorithms Ovidiu Daescu Bio-Medical Computing Laboratory Department of Computer Science University of Texas at Dallas (Joint work with Yam Ki Cheung and Anastasia Kurdia)

2.  Rigid needle: cannot bend  Steerable needle: can bend State of needle described by tip position, orientation, and bevel direction φ

3.  Composed of a highly flexible material, with a bevel tip  Offers greater mobility compared to rigid needles for minimally invasive medical procedures.  Needle traces out a curve path inside the tissue.  Rotating the base, the needle can be steered to avoid vital organs. φ The state of the needle is described by tip position, tip orientation, bevel direction

5. Rigid Needle: Optimal Directions

6. Optimal Directions

7. Optimal Direction in Radiation Therapy

8. Weighted subdivisions

9. Weighted Distance Metric a b s t p ||p||=∑|p∩R i |w i ||ab||=|ab|w i

10. Cases  Optimal directions in weighted regions  Optimal link in weighted regions  k-link minimum cost paths  Steerable needle paths  Most results in 2D, some extend to 3D

11. L T The line L “probes” R L The line L “penetrates” R T Optimal Direction

12. L T S An optimal link problem between a source S and a target T. Optimal Link

13. L T The line L “probes” R L The line L “penetrates” R T Optimal Direction/Link  -width 

14. L T Optimal Direction – Strip Cover

15. T Optimal Direction – Cone Cover

16. K-Link Minimum Cost Path A 9-link path. A 4-link path.

17. The LinkSolver Software

18. 2D: Optimal link goes through a vertex Property T

19. 2D: Optimal link goes through a vertex Property T 

20.  In ray space  Much faster to solve than 2D optimization problems 1D Problems T v

21.  1D optimization  The objective function is “not nice”  Can approximate optimal solution do this for all subproblems at v prune-and-search: fast in practice  Can model it as a 2D linear objective function problem use SOLF algorithm A subproblem at v T v

22.  Optimal ray Goes through vertex Goes through two edges  2D optimization problems! Extend to 3D v

23.  Get many 2D slices Automatically As suggested by expert

24.  Minimally invasive surgical techniques have been highly successful in improving patient care, reducing risk of infection, and decreasing recovery times and treatment costs.  A thin flexible needle, inserted into the human body and steered them from outside.  Can reach targets inaccessible to traditional stiff needles  One of the ways to reduce invasiveness of radiotherapy, biopsy collection, other procedures.

25.  The position of the needle depends on Original insertion angle Ability of the needle to bend The number of rotations performed and angle of each rotation  Bending of the needle depends on physical properties of the needle and the environment  A treatment plan would consist of initial insertion point and orientation and a sequence of rotations

26.  Rotation at the base does not directly correspond to the rotation at the needle tip  More rotations result in larger deviation of the actual position of the needle tip from the predicted position  The tissue experiences deformation Implications:  A desired treatment plan should minimize the number of rotation to minimize the error  It should also avoid or minimize damage to vital organs

27.  Design algorithms to compute optimal treatment plans  Create computer simulations and visualization of the interaction between the needle and the human tissue to aid the surgeons in planning the procedures.

28.  Can characterize the number of rotations and compute treatment plan in absence of obstacles in 2D and 3D  Given a target, the minimum number of rotations required to reach the target can be found fast

29. Work in progress  Compute the optimal path in the presence of polygonal obstacles

30.  Laboratory for Computational Sensing and Robotics at Johns Hopkins University  “Steering Flexible Needles in Soft Tissue“  Funding: NSF  Focus on probabilistic methods of computing trajectory.

31.  Medical Robotics Technology Center at Carnegie Mellon University  “Needle Steering for Brain Surgery”  Funding: The Pittsburgh Foundation, NSF  Searching for optimal physical properties of the needle  Showed that constantly spinning the needle during insertion makes the needle move in straight line

32.  Laboratory for Biomedical Computing at UTD and UTSW research groups? Preliminary work started with Lech Papiez’s group  Funding: ?  Focus on deterministic methods.

33.  Want real time solutions  Use multiple 2D slices (hundreds) Independent problems in each slice Solve in parallel on a cluster of computers  Business model: outsource computation Data at UTSW Computing cluster at UTD Transfer anonimous data (random ID)