Modeling and Control of Robotics-assisted Needle Steering in Soft Tissue

• Author / Creator

  Khadem, Seyed Mohsen

• Percutaneous needle insertion is a common type of minimally invasive surgery used for diagnostic and therapeutic applications such as biopsy, drug delivery, and cancer treatment. Prostate brachytherapy is a needle-based intervention, which is used for cancer treatment. In brachytherapy the surgeon inserts a needle into a patient's body such that radioactive seeds pre-loaded in the needles can be placed in or near the tumor, where radiation released from the seeds kills the cancer cells. Efficiency of needle-based interventions highly depends on accurate control of the needle tip trajectory. For instance, mean targeting accuracy of current techniques used in brachytherapy is 5 mm, which is a relatively large inaccuracy as the average prostate is about 50 mm in diameter. Autonomous or semi-autonomous needle adjustment systems can be used to control the needle tip trajectory and enhance needle insertion accuracy. This dissertation explores the modeling and control of robotics-assisted needle steering with the aim of enhancing the performance of needle-based interventions. This dissertation's main theme is to deploy a medical robot system with minimal modification to clinical settings. Prostate brachytherapy is studied as an example of needle-based interventions. Robotics-assisted needle steering strategies are proposed that can reduce needle targeting error in various clinical scenarios in prostate brachytherapy, which will benefit the individual patient, the surgeon, and the health-care system in the long run. Modeling the needle deflection and its interaction with soft tissue is the first requirement for robotic needle steering. A needle steering model can be used for designing the needle steering controller or estimating the needle/tissue system states that are not observable using 2D imaging modalities. In this research, several needle steering models are proposed that can predict needle deflection in soft tissue as a function of needle steering control inputs such as insertion velocity and needle axial rotation. The models are also capable of estimating needle steering states such as needle shape or needle tip orientation in soft tissue, thus enabling applications in motion planning and real-time control of needle steering. The models are implemented for 2D and 3D needle steering, as well as fully automatic and semi-automated needle steering. In the fully automated needle steering the robot controls all the steering actions. In the semi-automated needle steering the robotic device shares the needle steering control inputs with the surgeon in the interest of ensuring the safety of the operation. Experimental results on synthetic and ex-vivo tissue samples demonstrate that the proposed strategies can significantly reduce needle targeting error in various scenarios in prostate brachytherapy. We also demonstrate that combining the proposed needle steering strategies with a novel flexible needle proposed in this research, provides new methods of reaching challenging targets to reduce number of conditions that are currently considered untreatable or inoperable.

• Subjects / Keywords

  • Tissue Modelling
  • Medical Robotics
  • Needle Steering
  • Motion Planning

• Graduation date

  Fall 2017

• Type of Item

  Thesis

• Degree

  Doctor of Philosophy

• DOI

  https://doi.org/10.7939/R3P55DZ82

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.