Share Email Print
cover

Proceedings Paper

Modeling the surgical exposure of anatomy in robot-assisted laparoscopic partial nephrectomy
Author(s): Michael A. Kokko; John D. Seigne; Douglas W. Van Citters; Ryan J. Halter
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Although robotic instrumentation has revolutionized manipulation in oncologic laparoscopy, there remains a significant need for image guidance during the exposure portion of certain abdominal procedures. The high degree of mobility and potential for deformation associated with abdominal organs and related structures poses a significant challenge to implementing image-based navigation for the initial phase of robot-assisted laparoscopic partial nephrectomy (RALPN). This work introduces two key elements of a RALPN exposure simulation framework: a model for laparoscopic exposure and a compact representation of anatomical geometry suitable for integration into a statistical estimation framework. Data to drive the exposure simulation were collected during a clinical RALPN case in which the robotic endoscope was tracked in six dimensions. An initial rigid registration was performed between a preoperative CT scan and the frame of the optical tracker, allowing the endoscope trajectory to be replayed over tomography to simulate anatomical observations with realistic kinematics. CT data from five study subjects were combined with four publicly available datasets to produce a mean kidney shape. This template kidney was fit back to each of the input models by optimally tuning a set of eight parameters, achieving an average RMSE of 2.18mm. These developments represent important steps toward a full, clinically-relevant framework for simulating organ exposure and testing navigation algorithms. In future work, a particle filter estimation scheme will be integrated into the simulation to incrementally optimize correspondences between parametric anatomical models and simulated or reconstructed endoscopic observations.

Paper Details

Date Published: 16 March 2020
PDF: 7 pages
Proc. SPIE 11315, Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling, 113151H (16 March 2020); doi: 10.1117/12.2550605
Show Author Affiliations
Michael A. Kokko, Thayer School of Engineering, Dartmouth College (United States)
John D. Seigne, Geisel School of Medicine, Dartmouth College (United States)
Dartmouth-Hitchcock Medical Ctr. (United States)
Douglas W. Van Citters, Thayer School of Engineering, Dartmouth College (United States)
Ryan J. Halter, Thayer School of Engineering, Dartmouth College (United States)
Geisel School of Medicine, Dartmouth College (United States)


Published in SPIE Proceedings Vol. 11315:
Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling
Baowei Fei; Cristian A. Linte, Editor(s)

© SPIE. Terms of Use
Back to Top
PREMIUM CONTENT
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?
close_icon_gray