PhD Thesis Defense: Michael Kokko

For Info on how to attend this videoconference, please email Michael Kokko at michael.a.kokko.TH@dartmouth.edu

"Toward Autonomous Navigation in the Abdominal Cavity: A Framework for Navigated Organ Exposure in Robotic Laparoscopy"

Abstract

The field of surgical robotics has demonstrated marked success over the past two decades in augmenting the dexterity and reach of the minimally invasive surgeon, while maintaining (or improving upon) patient outcomes associated with traditional laparoscopic and open approaches. Barriers to wider adoption of robotics include high capital and operating expenses, the potential for increased operative time relative to open surgery, and attenuation of the visual and tactile sensory information that has guided the hands of surgeons for centuries. Sensory cues are of particular importance during the exposure phase of abdominal surgery, when surgeons navigate with limited visibility through webs of fascia and adipose tissue by incrementally exposing anatomical landmarks, consulting preoperative imaging, and drawing from their own surgical experience. While the image-guided surgery community has developed a number of navigational solutions for visualizing tumors within exposed organs, relatively little attention has been paid to assisting surgeons during the process of gaining initial exposure. A successful guidance system for abdominal exposure will reduce operating time (lower cost), surgeon cognitive load (higher quality output), and anesthesia time (quicker recovery) without increasing the risk of iatrogenic damage.

This thesis introduces methods for bridging the gap between the autonomous navigation strategies of the mobile robotics community and the largely manual methods currently employed in robotic surgery, using Robot-Assisted Laparoscopic Partial Nephrectomy (RALPN) as an illustrative test case. Building on a newly-acquired clinical dataset, primary contributions are made toward flexible geometric modeling of relevant anatomical structures, iterative assimilation of intraoperative observations into prior anatomical pose estimates, as well as strategies for pre-clinical validation of exposure guidance.

Thesis Committee

• Ryan Halter, PhD (chair)
• Douglas Van Citters, PhD
• Keith Paulsen, PhD
• John Seigne, MB
• Stamatia Giannarou, PhD (external)

Contact

For more information, contact Theresa Fuller at theresa.d.fuller@dartmouth.edu.