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Optical Society of Korea (한국광학회)
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Cerebral Oxygenation Monitoring during a Variation of Isoflurane Concentration in a Minimally Invasive Rat Model

  • Choi, Dong-Hyuk (Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology) ;
  • Kim, Sungchul (Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology) ;
  • Shin, Teo Jeon (Department of Pediatric Dentistry, School of Dentistry, Seoul National University) ;
  • Kim, Seonghyun (Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology) ;
  • Kim, Jae Gwan (Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology)
  • Received : 2022.05.18
  • Accepted : 2022.08.30
  • Published : 2022.10.25
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Abstract

Our previous study on monitoring cerebral oxygenation with a variation of isoflurane concentration in a rat model showed that near-infrared spectroscopy (NIRS) signals have potential as a new depth of anesthesia (DOA) index. However, that study obtained results from the brain in a completely invasive way, which is inappropriate for clinical application. Therefore, in this follow-up study, it was investigated whether the NIRS signals measured in a minimally invasive model including the skull and cerebrospinal fluid layer (CSFL) are similar to the previous study used as a gold standard. The experimental method was the same as the previous study, and only the subject model was different. We continuously collected NIRS signals before, during, and after isoflurane anesthesia. The isoflurane concentration started at 2.5% (v/v) and decreased to 1.0% by 0.5% every 5 min. The results showed a positive linear correlation between isoflurane concentration and ratio of reflectance intensity (RRI) increase, which is based on NIRS signals. This indicates that the quality of NIRS signals passed through the skull and CSFL in the minimally invasive model is as good as the signal obtained directly from the brain. Therefore, we believe that the results of this study can be easily applied to clinics as a potential indicator to monitor DOA.

Keywords

Acknowledgement

SGER grant through the National Research Foundation of Korea (NRF-2015R1D1A1A02062382); Healthcare AI Convergence Research & Development Program through the National IT Industry Promotion Agency of Korea (NIPA) funded by the Ministry of Science and ICT (No. S1601-20-1016); and GIST Research Institute (GRI) IIBR grant funded by the GIST in 2022.

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