Validation of the PathFinder neurosurgical robot using a phantom

M. S. Eljamel

    Research output: Contribution to journalArticlepeer-review

    52 Citations (Scopus)


    Background: Minimally invasive surgery was born out of recent advances in neuro-imaging and stereotactic technology. As a result, the scale of neurosurgical procedures will soon be so small that it will not be within the ability of the most gifted and skilled neurosurgeons of today. Hence, neurosurgical robotics is the natural evolution in this field. The aim of this study was to evaluate the performance of a new robotic system in a neurosurgical phantom, comparing it to standard frame-based and frameless technology of today. Methods: In total, 19 different targets were approached by two standard stereotactic frames, the Stealth Station frameless system and the robot. The CRW and the ZD stereotactic frames were used. The frameless system was the Stealth Station image guidance system. The phantom used was a replica of the human skull fitted with 10 surface and nine deep targets. Results: The robotic system outperformed both frame-based and frameless systems in all experiments in this study. The application accuracies were: robot, 0.5 mm; stereotactic frames, 0.98 mm; and frameless system, 1.96 mm. Conclusions: The robotic system was as accurate as the stereotactic frame, but without technical restrictions and cumbersome manual adjustments. Furthermore, the robotic system had near-absolute geometric accuracy, was reliable to perform the same procedure over and over without tiresomeness, variation or boredom, and would be impervious to biohazards and hostile environments. Copyright © 2007 John Wiley & Sons, Ltd
    Original languageEnglish
    Pages (from-to)372-377
    Number of pages6
    JournalInternational Journal of Medical Robotics and Computer Assisted Surgery
    Issue number4
    Publication statusPublished - Dec 2007


    • Equipment Design
    • Equipment Failure Analysis
    • Humans
    • Neurosurgical Procedures
    • Phantoms, Imaging
    • Reproducibility of Results
    • Robotics
    • Sensitivity and Specificity
    • Surgery, Computer-Assisted


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