Reduced risk trajectory planning in image-guided keyhole neurosurgery

Reuben R. Shamir*, Leo Joskowicz, Idit Tamir, Elad Dabool, Lihi Pertman, Adam Ben-Ami, Yigal Shoshan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

43 Scopus citations


Purpose: The authors present and evaluate a new preoperative planning method and computer software designed to reduce the risk of candidate trajectories for straight rigid tool insertion in image-guided keyhole neurosurgery. Methods: Trajectories are computed based on the surgeon-defined target and a candidate entry point area on the outer head surface on preoperative CT/MRI scans. A multiparameter risk card provides an estimate of the risk of each trajectory according to its proximity to critical brain structures. Candidate entry points in the outer head surface areas are then color-coded and displayed in 3D to facilitate selection of the most adequate point. The surgeon then defines and/or revised the insertion trajectory using an interactive 3D visualization of surrounding structures. A safety zone around the selected trajectory is also computed to visualize the expected worst-case deviation from the planned insertion trajectory based on tool placement errors in previous surgeries. Results: A retrospective comparative study for ten selected targets on MRI head scans for eight patients showed a significant reduction in insertion trajectory risk. Using the authors' method, trajectories longer than 30 mm were an average of 2.6 mm further from blood vessels compared to the conventional manual method. Average planning times were 8.4 and 5.9 min for the conventional technique and the authors' method, respectively. Neurosurgeons reported improved understanding of possible risks and spatial relations for the trajectory and patient anatomy. Conclusions: The suggested method may result in safer trajectories, shorter preoperative planning time, and improved understanding of risks and possible complications in keyhole neurosurgery.

Original languageAmerican English
Pages (from-to)2885-2895
Number of pages11
JournalMedical Physics
Issue number5
StatePublished - May 2012

Bibliographical note

Funding Information:
This work was support in part by FP7 ERC ROBOCAST Grant No. 21590. The authors thank Ms. Judith Frank for her assistance with MRI head scan segmentation. The authors thank Ms. Shifra Fraifeld for her assistance with the preparation of the manuscript.


  • neurosurgery
  • therapy planning


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