Volume 13, Issue 5 (September & October 2022)
BCN 2022, 13(5): 595-608 |
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Mirhoseini M, Rezanejad Gatabi Z, Das S, Joveini S, Rezanezhad Gatabi I. Applications of Electrical Impedance Tomography in Neurology. BCN 2022; 13 (5) :595-608
URL: http://bcn.iums.ac.ir/article-1-2010-en.html
URL: http://bcn.iums.ac.ir/article-1-2010-en.html
Mehri Mirhoseini1 
, Zahra Rezanejad Gatabi2 , Sayantan Das3 , Sepideh Joveini2 , Iman Rezanezhad Gatabi * 4
, Zahra Rezanejad Gatabi2 , Sayantan Das3 , Sepideh Joveini2 , Iman Rezanezhad Gatabi * 4
1- Amol Faculty of Paramedical Sciences, Mazandaran University of Medical Sciences, Sari, Iran.
2- Department of Pharmaceutics, Faculty of Pharmacy, Mazandaran University of Medical Sciences, Sari, Iran.
3- Faculty/College of Science and Mathematics, Texas A&M University, San Antonio, United States.
4- Department of Electrical and Computer Engineering, Texas A&M University, College Station, United States.
2- Department of Pharmaceutics, Faculty of Pharmacy, Mazandaran University of Medical Sciences, Sari, Iran.
3- Faculty/College of Science and Mathematics, Texas A&M University, San Antonio, United States.
4- Department of Electrical and Computer Engineering, Texas A&M University, College Station, United States.
Abstract:
Introduction: Electrical impedance tomography (EIT) is a non-invasive technique utilized in various medical applications, including brain imaging and other neurological diseases. Recognizing the physiological and anatomical characteristics of organs based on their electrical properties is one of the main applications of EIT, as each variety of tissue structure has its own electrical characteristics. The high potential of brain EIT is established in real-time supervision and early recognition of cerebral brain infarction, hemorrhage, and other diseases. In this paper, we review the studies on the neurological applications of EIT.
Methods: EIT calculates the internal electrical conductivity distribution of an organ by measuring its surface impedance. A series of electrodes are placed on the surface of the target tissue, and small alternating currents are injected. The related voltages are then observed and analyzed. The electrical permittivity and conductivity distributions inside the tissue are reconstructed by measuring the electrode voltages.
Results: The electrical characteristic of biological tissues is remarkably dependent on their structures. Some tissues are better electrical conductors than the others since they have more ions that can carry the electrical charges. This difference is attributed to changes in cellular water content, membrane properties, and destruction of tight junctions within cell membranes.
Conclusion: EIT is an extremely practical device for brain imaging, capturing fast electrical activities in the brain, imaging epileptic seizures, detecting intracranial bleeding, detecting cerebral edema, and diagnosing stroke.
Methods: EIT calculates the internal electrical conductivity distribution of an organ by measuring its surface impedance. A series of electrodes are placed on the surface of the target tissue, and small alternating currents are injected. The related voltages are then observed and analyzed. The electrical permittivity and conductivity distributions inside the tissue are reconstructed by measuring the electrode voltages.
Results: The electrical characteristic of biological tissues is remarkably dependent on their structures. Some tissues are better electrical conductors than the others since they have more ions that can carry the electrical charges. This difference is attributed to changes in cellular water content, membrane properties, and destruction of tight junctions within cell membranes.
Conclusion: EIT is an extremely practical device for brain imaging, capturing fast electrical activities in the brain, imaging epileptic seizures, detecting intracranial bleeding, detecting cerebral edema, and diagnosing stroke.
Type of Study: Review |
Subject:
Computational Neuroscience
Received: 2020/11/30 | Accepted: 2021/04/14 | Published: 2022/09/11
Received: 2020/11/30 | Accepted: 2021/04/14 | Published: 2022/09/11
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