Advances in electrical impedance tomography-based brain imaging

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.

Emerging trends and hot spots on electrical impedance tomography extrapulmonary applications

“…EIT biological applications involved multiple tissue and organ such as the brain [ 23 ], breast [ 24 ], prostate [ 25 ], bladder [ 26 ], stomach [ 27 ], and blood vessels [ 28 ], etc., consistent with our result that keywords were clustered into 18 topics. The cluster intensity and the specific topic analysis showed that applications in brain anatomical structure, breast cancer, and hemodynamics were hot topics over time.…”

Electrical Impedance Tomography: From the Traditional Design to the Novel Frontier of Wearables

“…As the blood is characterized by lower impedance compared to the brain, brain imaging exploits the impedance changes in the cerebral cortex induced by a change in the cerebral blood volume during functional activity or in the case of stroke and ischemia [ 83 ]. EIT has broad possibilities in diagnosis and real-time monitoring in patients with brain diseases, with recent research focusing on epilepsy, stroke, brain injury and edema [ 83 ].…”

“…As the blood is characterized by lower impedance compared to the brain, brain imaging exploits the impedance changes in the cerebral cortex induced by a change in the cerebral blood volume during functional activity or in the case of stroke and ischemia [ 83 ]. EIT has broad possibilities in diagnosis and real-time monitoring in patients with brain diseases, with recent research focusing on epilepsy, stroke, brain injury and edema [ 83 ]. Studies on conductive changes in the rat cerebral cortex during physiological evoked activity [ 84 ] and epileptic discharges [ 84 ] using epicortical electrodes have reported temporal and spatial resolutions of 2 ms and 200 μm, respectively.…”

Cerebral edema after ischemic stroke: Pathophysiology and underlying mechanisms

“…However, these MRI techniques are expensive, time-consuming, and cannot monitor cerebral edema in real-time. Electrical impedance tomography (EIT) is a real-time functional imaging technique that allows imaging of electrical impedance changes in the volume of interest ( Ke et al, 2022 ). Because the electrical impedance between cerebral edema tissue and normal cortical tissue is different, EIT could recognize different types of cerebral edema ( Yang et al, 2019 ).…”

“…Because the electrical impedance between cerebral edema tissue and normal cortical tissue is different, EIT could recognize different types of cerebral edema ( Yang et al, 2019 ). However, the application of EIT is limited by factors such as the modeling accuracy and reconstruction algorithms ( Ke et al, 2022 ). The emergence of artificial intelligence points to a new direction for evaluating cerebral edema, but minimal efforts have been made to detect cerebral edema ( Obenaus and Badaut, 2022 ).…”