Current Directions in Biomedical Engineering (Sep 2015)

Intraoperative identification of somato-sensory brain areas using optical imaging and standard RGB camera equipment – a feasibility study

  • Oelschlägel M.,
  • Meyer T.,
  • Sobottka S. B.,
  • Kirsch M.,
  • Schackert G.,
  • Morgenstern U.

DOI
https://doi.org/10.1515/cdbme-2015-0066
Journal volume & issue
Vol. 1, no. 1
pp. 265 – 269

Abstract

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Intraoperative Optical Imaging (IOI) is a neuro-imaging technique that allows the visualization of changes in optical properties of the brain cortex. Recent developments enhanced the method regarding the robustness under intraoperative conditions. However, the necessity of additional hardware still limits the use in the operating room (OR). Since modern surgical microscopes are potentially equipped with all required hardware for imaging, we investigated the possible use of such standard RGB camera for IOI. Measurements were performed on eight patients. Changes in optical properties of the cortical surface were acquired with a monochrome CCD camera (AxioCam MRm) and simultaneously with a standard RGB camera (Trio 610). Maps of cortical activity were calculated from the image data and the quality of these maps was assessed with a spatial signal-to-noise ratio. Activity maps calculated from AxioCam MRm data showed highest SNR in six out of eight patients. In two patients the activity map calculated from Trio 610 red channel performed best overall. The Trio 610 maps calculated from red channel data performed best in three out of eight cases like the activity maps calculated from green channel data, whereas the activity map calculated from blue channel data performed best in only two cases. If the color channel with the highest SNR is chosen in each patient for comparison to AxioCam MRm, the median of the SNR (SNRAxioCam/SNRBestColorChannel) is 84 % (Quartile 1 (Q1): 78 %, Quartile 3 (Q3): 99%). Results reveal that the integration of the Intraoperative Optical Imaging method into the OR and surgical workflow can be further improved by using RGB camera equipment. A robust identification of somato-sensory areas seems possible. Due to the gain of information from different wavelength bands the need for intelligent evaluation algorithms is increased and should therefore be topic of future research.

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