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Related Experiment Videos

Smart bioimpedance-controlled craniotomy: Concept and first experiments.

Annegret Niesche1, Meiko Müller1, Fritz Ehreiser1

  • 11 Chair of Medical Engineering, RWTH Aachen University, Aachen, Germany.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of Engineering in Medicine
|April 8, 2017
PubMed
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This study introduces real-time cutting depth control for craniotomy using bioimpedance measurements. This innovative approach enhances neurosurgical safety by preventing damage to delicate intracranial structures during bone cutting.

Area of Science:

  • Neurosurgery
  • Biomedical Engineering
  • Surgical Instrumentation

Background:

  • Craniotomy, essential for accessing intracranial structures, carries risks of dural tears and soft tissue damage.
  • Existing methods for controlling bone cutting depth lack robustness and often complicate surgical workflows.
  • A novel instrument combining a soft tissue preserving saw with automatic depth control has been developed.

Purpose of the Study:

  • To present novel concepts for real-time cutting depth control during craniotomy.
  • To explore the use of in-process bioimpedance measurements for surgical depth control.
  • To demonstrate and evaluate sensor integration into a synergistic surgical device.

Main Methods:

  • Development of real-time cutting depth control algorithms based on bioimpedance.
Keywords:
Bioimpedancebone cuttingcomputer-assisted surgerycraniotomyimpedance-controlled surgical instrumentationrobot-assisted surgeryskull trepanation

Related Experiment Videos

  • Integration of bioimpedance sensors into a bidirectional oscillating saw system.
  • Feasibility testing on fresh bovine bone specimens using bipolar measurements.

    • Main Results:

    • Characteristic impedance patterns were observed during transitions between bicortical bone layers.
    • Bone breakthrough was identified through distinct changes in impedance.
    • These impedance patterns show potential for effective process control during craniotomy.

    Conclusions:

    • In-process bioimpedance measurements offer a robust method for real-time cutting depth control in craniotomy.
    • Sensor integration into synergistic surgical devices is feasible and effective.
    • This technology has the potential to significantly improve neurosurgical safety and precision.