A Computational Image-Based Guidance System for Precision Laparoscopy
|Tsekos, Nikolaos V.
|Pavlidis, Ioannis T.
|Nguyen, Toan B. 1984-
|This dissertation presents our progress toward the goal of building a computational image-based guidance system for precision laparoscopy; in particular, laparoscopic liver resection. As we aim to keep our working goal as simple as possible, we have focused on the most important questions of laparoscopy - predicting the new location of tumors and resection plane after a liver maneuver during surgery. Our approach was to build a mechanical model of the organ based on pre-operative images and register it to intra-operative data. We proposed several practical and cost-effective methods to obtain the intra-operative data 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 of the liver. We were able to confirm that our model has decent accuracy for 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. For further corrections to 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 a 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 an effort to transit our research from porcine livers to human livers, in-vivo experiments had been conducted on cadavers. From those studies, we found 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.
|Computer Science, Department of
|Portions of this document appear in: Nguyen, Toan B., Albert Y. Huang, Vid Fikfak, Brian J. Dunkin, and Marc Garbey. "Image-guided simulation of tissue deformation using a mechanical model on a surgical application." Computer methods in biomechanics and biomedical engineering 20, no. 2 (2017): 206-214.
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|Soft tissue mechanics
|A Computational Image-Based Guidance System for Precision Laparoscopy
|College of Natural Sciences and Mathematics
|University of Houston
|Doctor of Philosophy