Advances in electrical impedance tomography-based brain imaging

Military Medical Research

Qi Huang¹  Si-Yi Hu¹  Xue-Ying Bao²  Wei Hou²  Cheng-Xiang Li²  Yu-Qi Qiu²  Wei-Xuan Kong²  Li-Hua Dong²  Xi-Yang Ke²  Xue Hou² 

[1] CAS Key Laboratory of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences;Department of Radiation Oncology and Therapy, The First Hospital of Jilin University;

关键词: Electrical impedance tomography (EIT);    Brain diseases;    Tissue impedance;    Microelectrode array;   

DOI  :  10.1186/s40779-022-00370-7

来源: DOAJ

【 摘 要 】

Abstract Novel advances in the field of brain imaging have enabled the unprecedented clinical application of various imaging modalities to facilitate disease diagnosis and treatment. Electrical impedance tomography (EIT) is a functional imaging technique that measures the transfer impedances between electrodes on the body surface to estimate the spatial distribution of electrical properties of tissues. EIT offers many advantages over other neuroimaging technologies, which has led to its potential clinical use. This qualitative review provides an overview of the basic principles, algorithms, and system composition of EIT. Recent advances in the field of EIT are discussed in the context of epilepsy, stroke, brain injuries and edema, and other brain diseases. Further, we summarize factors limiting the development of brain EIT and highlight prospects for the field. In epilepsy imaging, there have been advances in EIT imaging depth, from cortical to subcortical regions. In stroke research, a bedside EIT stroke monitoring system has been developed for clinical practice, and data support the role of EIT in multi-modal imaging for diagnosing stroke. Additionally, EIT has been applied to monitor the changes in brain water content associated with cerebral edema, enabling the early identification of brain edema and the evaluation of mannitol dehydration. However, anatomically realistic geometry, inhomogeneity, cranium completeness, anisotropy and skull type, etc., must be considered to improve the accuracy of EIT modeling. Thus, the further establishment of EIT as a mature and routine diagnostic technique will necessitate the accumulation of more supporting evidence.

【 授权许可】

Unknown