Geometry Factor Determination for Tetrapolar Impedance Sensor Probes

Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov:2021:6800-6805. doi: 10.1109/EMBC46164.2021.9629757.

Abstract

Even after successful tumor resection, cancer recurrence remains an important issue for bladder tumors. Intra-operative tissue differentiation can help for diagnostic purposes as well as for ensuring that all cancerous cells are completely removed, therefore, decreasing the risk of recurrence. It has been shown that the electrical properties of tumors differ from healthy tissue due to an altered physiology. This work investigates three sensor configurations to measure the impedance of tissue. Each relies on a four terminal measurement and has a distinct electrode arrangement either inline or as a square. Analytical expressions to calculate the geometry factor of each sensor based on Laplace's equation are derived. The results are verified experimentally and in a finite element simulation. Furthermore, several measurements on pig bladders, both fresh and from frozen storage, are carried out with each sensor.It is shown that the calculated and simulated geometry factors yield the same results and are suitable and uncomplicated methods to determine the geometry factor without an experimental setup. These methods also allow for sensor optimization by knowing the measured potentials before the actual fabrication of the sensor. Moreover, conductivity values close to listed data are obtained for pig bladders, which validates the sensors. Ultimately, the square electrode configuration turns out to be a valid option for minimally invasive sensors, which are necessary for the envisaged application of transurethral bladder cancer diagnostics and surgery. This arrangement both assures reliable data and allows for easier miniaturization than the inline electrode placement.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Computer Simulation
  • Electric Impedance
  • Electrodes
  • Neoplasm Recurrence, Local*
  • Swine