In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy
will defend his dissertation
A Computational Image-Based Guidance System for Precision Laparoscopy
This dissertation presents our progress toward the goal of building a computational image-based guidance system for precision laparoscopy; in particular, laparoscopic liver resection.
By identifying types of liver resection that can gain benefit from our study, we limited our scope and aimed to solve two practical problems of laparoscopy: to predict the new location of tumors and resection plane after a liver’s maneuver during the surgery. Our approach was to build a mechanical model of the organ based on pre-operative image and register it to intra-operative data. We proposed several practical and cost-effective methods to obtain the intra-operative data the in the real procedure. We integrated all of them into a framework on which we could develop new techniques without redoing everything.
To test the system, we did an experiment with a porcine liver in a controlled setup: a wooden lever was used to elevate a part of the liver to access the posterior aspect of the liver. We had been able to confirm that our model has decent accuracy on the tumor location (approximately 2 mm error) and resection plane (1% difference in remaining liver volume after resection). However, the overall shape of the liver and the fiducial markers still left a lot to be desired.
To make further corrections for the model, we also developed an algorithm to reconstruct the 3D surface of the liver utilizing Smart Trocars, a new surgical instrument recognition system. The algorithm had been verified by an experiment on plastic model using the laparoscopic camera as a mean to obtain surface images. This method had millimetric accuracy provided the angle between two endoscope views is not too small.
In vivo experiments had been conducted on cadavers and had positive preliminary results. From those studies, we found out a new method that used a high-frequency ventilator to eliminate respiratory motion.
The framework showed the potential to work on real organs in clinical settings. Hence, the studies on cadavers needed to be continued to improve those techniques and complete the guidance system.
Date: Wednesday, November 2, 2016
Time: 10:00 AM - 11:00 AM
Place: PGH 550
Advisor: Dr. Nikolaos V. Tsekos
Faculty, students, and the general public are invited.