AUA 2017: Development of Software to Overlay Imaging Data in Real Time onto the Intraoperative View During Robotic Surgery

Boston, MA ( Lim et al. presented a novel method for intraoperative superimposition of preoperative patient imaging data for use in robotic surgery. The goal of their present in vitro study was to define the spatial accuracy of the software developed by their team. They developed three dimensional pelvic skeletal and prostate models with small markers printed into their surfaces. These models were then imaged via CT allowing for the automatic segmentation of these markers. This interesting approach made it possible to identify the same marker locations on laparoscopic imaging. Upon the identification of these markers, the software is designed to correlate the markers from the CT segmentation with the laparoscopic display output. In essence, the registration markers make image superimposition possible.

Regarding accuracy related to the markers between the laparoscopic image, the 3D-printed models, and the CT segmentation, the image overlay accuracy was 4.21mm. However, the presenting author pointed out that the laparoscope was far more accurate (within 1mm), and that with further fine-tuning of the software, the accuracy is expect to improve. They anticipate testing the accuracy in clinical, in vivo experiments in the near future.

Presented By: Sunghwan Lim

Authors: Sunghwan Lim, Changhan Jun, Doru Petrisor, Pan Li, Steven P. Rowe, Mohamad E. Allaf, Dan Stoianovici, Michael A. Gorin

Affiliation: Robotics Laboratory, Department of Urology, Johns Hopkins University School of Medicine

Written By: Shoaib Safiullah, MS4 for

at the 2017 AUA Annual Meeting - May 12 - 16, 2017 – Boston, Massachusetts, USA