gms | German Medical Science

60th Annual Meeting of the German Society of Neurosurgery (DGNC)
Joint Meeting with the Benelux countries and Bulgaria

German Society of Neurosurgery (DGNC)

24 - 27 May 2009, Münster

Automated databasing of tissue consistency parameters using a new tactile sensor technology

Meeting Abstract

  • R. Stroop - Klinik für Neurochirurgie, Universitätsklinikum Essen
  • D. Oliva Uribe - Institut für Dynamik und Schwingungen, Universität Hannover
  • J. Wallaschek - Institut für Dynamik und Schwingungen, Universität Hannover
  • U. Sure - Klinik für Neurochirurgie, Universitätsklinikum Essen

Deutsche Gesellschaft für Neurochirurgie. 60. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC), Joint Meeting mit den Benelux-Ländern und Bulgarien. Münster, 24.-27.05.2009. Düsseldorf: German Medical Science GMS Publishing House; 2009. DocP10-08

doi: 10.3205/09dgnc360, urn:nbn:de:0183-09dgnc3604

Published: May 20, 2009

© 2009 Stroop et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( You are free: to Share – to copy, distribute and transmit the work, provided the original author and source are credited.



Objective: The neurosurgeon's tactile perception in addition to his visual sense is a crucial criterion for intraoperative tissue differentiation. Precise demarcation of brain tumor borders is as essential for patient outcome as it is important for minimizing tumor relapse.

Although human tactile perception is a highly sensitive function it is not able to quantify absolute tissue consistency parameters. Furthermore, tactile perception will be completely lost during tissue manipulation in endoscopic surgery techniques. Tissue consistency can be described by the use of mechanical parameters such as ‘stiffness’ and ‘damping’, however, a good interpretation requires an appropriate knowledge of these variables and their variance. A piezoelectric bimorph based sensing technology for high resolution determination of tissue consistency parameters was developed.

A measuring station was implemented for automated gauging of phantoms and porcine ex-vivo brain for databasing tissue elasticity parameters.

Methods: A resonant vibrating piezoelectric bimorph sensor was mounted to a 2-axis linear stage driven by stepper motors. The linear stage is fully automated and controlled by a computer using Labview. The bimorph support holder is attached to a load cell to measure the contact force between the tactile sensor and the probe.

Electrical frequency, amplitude and phase of the signals of the bimorph are recorded. A USB-Webcam is mounted for the registration of images with each measurement.

Results: The automated linear stage guided resonant vibrating piezoelectric bimorph sensor allowed to precisely characterize the tissue phantoms with respect to static elasticity parameters, ‘stiffness’ and ‘damping’, as well as to record dynamic strain-gauge curves. Thus highly reproducible measurements of porcine ex-vivo tissue were possible being used for databasing of tissue elasticity parameters.

Conclusions: These measurements are the basic precondition for the evaluation of still different tactile sensor elements and the assessment of their clinical application in intraoperative tissue differentiation. Whereas measurements have been performed at fresh porcine ex-vivo tissues therefore being deprived of a hemodynamic tissue perfusion and showing altered tissue tonicity, the experimental setup will serve as a measurement station for tissue elasticity in the investigation of tissue characteristics.