BioMedical Engineering OnLine (Mar 2022)

Early assessment of acute ischemic stroke in rabbits based on multi-parameter near-field coupling sensing

  • Gen Li,
  • Shengtong Yin,
  • Man Jian,
  • Jingbo Chen,
  • Lingxi Zeng,
  • Zelin Bai,
  • Wei Zhuang,
  • Bingxin Xu,
  • Shengjie He,
  • Jian Sun,
  • Yujie Chen

DOI
https://doi.org/10.1186/s12938-022-00991-y
Journal volume & issue
Vol. 21, no. 1
pp. 1 – 19

Abstract

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Abstract Background Early diagnosis and continuous monitoring are the key to emergency treatment and intensive care of patients with acute ischemic stroke (AIS). Nevertheless, there has not been a fully accepted method targeting continuous assessment of AIS in clinical. Methods Near-field coupling (NFC) sensing can obtain the conductivity related to the volume of intracranial components with advantages of non-invasiveness, strong penetrability and real-time monitoring. In this work, we built a multi-parameter monitoring system that is able to measure changes of phase and amplitude in the process of electromagnetic wave (EW) reflection and transmission. For investigating its feasibility in AIS detection, 16 rabbits were chosen to establish AIS models by bilateral common carotid artery ligation and then were enrolled for monitoring experiments. Results During the 6 h after AIS, the reflection amplitude (RA) shows a decline trend with a range of 0.69 dB and reflection phase (RP) has an increased variation of 6.48° . Meanwhile, transmission amplitude (TA) and transmission phase (TP) decrease 2.14 dB and 24.29° , respectively. The statistical analysis illustrates that before ligation, 3 h after ligation and 6 h after ligation can be effectively distinguished by the four parameters individually. When all those parameters are regarded as recognition features in back propagation (BP) network, the classification accuracy of the three different periods reaches almost 100%. Conclusion These results prove the feasibility of multi-parameter NFC sensing to assess AIS, which is promised to become an outstanding point-of-care testing method in the future.

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