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Measurement of Extracellular Electrical Properties with Tracer-Based MRI

  • Heng Zhang
  • , Yu Fu
  • , Hongbin Han*
  • , Jiangtao Sun*
  • , Lide Xie*
  • , Xiaokang Ren
  • , Yi Yuan
  • , Wanyi Fu
  • , Xin Mao
  • , Huipo Liu
  • , Jiangfeng Cao
  • , Yun Peng
  • , Xin Jia
  • , Meng Xu
  • , Hanbo Tan
  • , Shaoyi Su
  • *此作品的通讯作者
  • Chengde Medical University
  • Peking University
  • Beijing Key Lab of MRI Device and Technique
  • Yanshan University
  • Tsinghua University
  • IAPCM
  • CAS - Institute of Information Engineering
  • Capital Medical University

科研成果: 期刊稿件文章同行评审

摘要

To design and develop an electrical properties measurement strategy with Tracer-based MRI system to comprehensively and simultaneously detect the structure parameters, diffusion coefficients and electrical characteristics of brain extracellular space (ECS). A Tracer-based MRI system, integrated with Electrical Impedance Tomography (EIT), was developed to simultaneously measurement brain ECS structural parameters, diffusion coefficients, and electrical characteristics. Twelve adult Sprague–Dawley rats were randomly divided into two groups: the first group was assessed using traditional Tracer-based MRI alone (n = 6), and the second group with the integration of EIT compatible with impedance measurements (n = 6). The diffusion coefficient, volume fraction, and electrical performance parameters were analysed. The study demonstrated the feasibility of obtaining electrical properties of the ECS, including conductivity (2.006 S/m), dielectric constant (84.77), diffusion rate (3.54*10–4 mm2/s), and volume fraction(17.43%). Additionally, the group assessed with the integration of EIT exhibited a significant decrease in both the diffusion coefficient of ECS molecules (t = 4.748, P < 0.01) and ECS volume fraction (t = 7.77, P < 0.01), compared to using Tracer-based MRI alone. Tracer-based MRI integrated with EIT system enables comprehensive and simultaneous assessment of ECS including structure parameters, diffusion coefficients and electrical characteristics. This approach shows promise as a new method for neuromodulation through the ECS pathway.

源语言英语
期刊论文编号34
期刊Sensing and Imaging
25
1
DOI
出版状态已出版 - 12月 2024

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