Trajectory planning method for reduced patient risk in image-guided neurosurgery: Concept and preliminary results

Reuben R. Shamir, Leo Joskowicz, Luca Antiga, Roberto I. Foroni, Yigal Shoshan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

12 Scopus citations

Abstract

We present a new preoperative planning method to quantify and help reduce the risk associated with needle and tool insertion trajectories in image-guided keyhole neurosurgery. The goal is to quantify the risk of a proposed straight trajectory, and/or to find the trajectory with the lowest risk to nearby brain structures based on pre-operative CT/MRI images. The method automatically computes the risk associated with a given trajectory, or finds the trajectory with the lowest risk to nearby brain structures based on preoperative image segmentation and on a risk volume map. The surgeon can revise the suggested trajectory, add a new one using interactive 3D visualization, and obtain a quantitative risk measure. The trajectory risk is evaluated based on the tool placement uncertainty, on the proximity of critical brain structures, and on a predefined table of quantitative geometric risk measures. Our preliminary results on a clinical dataset with eight targets show a significant reduction in trajectory risk and a shortening of the preoperative planning time as compared to the conventional method.

Original languageAmerican English
Title of host publicationMedical Imaging 2010
Subtitle of host publicationVisualization, Image-Guided Procedures, and Modeling
EditorsKenneth H. Wong, Michael I. Miga
PublisherSPIE
ISBN (Electronic)9780819480262
DOIs
StatePublished - 2010
EventMedical Imaging 2010: Visualization, Image-Guided Procedures, and Modeling - San Diego, United States
Duration: 14 Feb 201016 Feb 2010

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume7625
ISSN (Print)1605-7422

Conference

ConferenceMedical Imaging 2010: Visualization, Image-Guided Procedures, and Modeling
Country/TerritoryUnited States
CitySan Diego
Period14/02/1016/02/10

Bibliographical note

Funding Information:
This study is supported by the ROBOCAST project, EU contract FP7-ICT-215190.

Publisher Copyright:
© 2010 SPIE.

Keywords

  • Image-guided therapy
  • Neuronavigation
  • Neurosurgical procedure
  • Therapy planning

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