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Jiao Y, Zhang T, Fan C, Cao H, Chao M, Han L, Zhang W, Mao L, Liu R, Xu C, Wang L. Real-time imaging of traumatic brain injury using magnetic induction tomography. Physiol Meas 2023; 44. [PMID: 36827707 DOI: 10.1088/1361-6579/acbeff] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 02/24/2023] [Indexed: 02/26/2023]
Abstract
Objective. Early diagnosis of traumatic brain injury (TBI) is crucial for its prognosis; however, traditional computed tomography diagnostic methods rely on large medical devices with an associated lag time to receive results. Therefore, an imaging modality is needed that provides real-time monitoring, can easily be carried out to assess the extent of TBI damage, and thus guides treatment.Approach. In the present study, an improved magnetic induction tomography (MIT) data acquisition system was used to monitor TBI in an animal model and distinguish the injury level. A pneumatically controlled cortical impactor was used to strike the parietal lobe of anesthetized rabbits two or three times under the same parameter mode to establish two different rabbit models of TBI. The MIT data acquisition system was used to record data and continuously monitor the brain for one hour without intervention.Main results. A target with increased conductivity was clearly observed in the reconstructed image. The position was relatively fixed and accurate, and the average positioning error of the image was 0.013 72 m. The normalized mean reconstruction value of all images increased with time. The slope of the regression line of the normalized mean reconstruction value differed significantly between the two models (p< 0.0001).Significance. This indicates that in the animal model, the unique features of MIT may facilitate the early monitoring of TBI and distinguish different degrees of injuries, thereby reducing the risk and mortality of associated complications.
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Affiliation(s)
- Yang Jiao
- Department of Neurosurgery, Tangdu Hospital of the Fourth Military Medical University, 569 Xinsi Road, Xi'an, 710038, People's Republic of China
| | - Tao Zhang
- Department of Biomedical Engineering, the Fourth Military Medical University, Xi'an 710032, People's Republic of China
| | - Chao Fan
- Department of Neurosurgery, Tangdu Hospital of the Fourth Military Medical University, 569 Xinsi Road, Xi'an, 710038, People's Republic of China
| | - Haiyan Cao
- Department of Neurosurgery, Tangdu Hospital of the Fourth Military Medical University, 569 Xinsi Road, Xi'an, 710038, People's Republic of China
| | - Min Chao
- Department of Neurosurgery, Tangdu Hospital of the Fourth Military Medical University, 569 Xinsi Road, Xi'an, 710038, People's Republic of China
| | - Liying Han
- Department of Neurosurgery, Tangdu Hospital of the Fourth Military Medical University, 569 Xinsi Road, Xi'an, 710038, People's Republic of China
| | - Weirui Zhang
- Department of Biomedical Engineering, the Fourth Military Medical University, Xi'an 710032, People's Republic of China
| | - Lei Mao
- HangZhou UTRON Technology Co., Ltd, Hang Zhou, People's Republic of China
| | - Ruigang Liu
- Department of Biomedical Engineering, the Fourth Military Medical University, Xi'an 710032, People's Republic of China
| | - Canhua Xu
- Department of Biomedical Engineering, the Fourth Military Medical University, Xi'an 710032, People's Republic of China
| | - Liang Wang
- Department of Neurosurgery, Tangdu Hospital of the Fourth Military Medical University, 569 Xinsi Road, Xi'an, 710038, People's Republic of China
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Wang L, Zhu W, Wang R, Li W, Liang G, Ji Z, Dong X, Shi X. Suppressing interferences of EIT on synchronous recording EEG based on comb filter for seizure detection. Front Neurol 2022; 13:1070124. [DOI: 10.3389/fneur.2022.1070124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 11/18/2022] [Indexed: 12/03/2022] Open
Abstract
Background and objectiveThe purpose of this study was to eliminate the interferences of electrical impedance tomography (EIT) on synchronous recording electroencephalography (EEG) for seizure detection.MethodsThe simulated EIT signal generated by COMSOL Multiphysics was superimposed on the clinical EEG signal obtained from the CHB-MIT Scalp EEG Database, and then the spectrum features of superimposed mixed signals were analyzed. According to the spectrum analysis, in addition to high-frequency interference at 51.2 kHz related to the drive current, there was also low-frequency interference caused by switching of electrode pairs, which were used to inject drive current. A low pass filter and a comb filter were used to suppress the high-frequency interference and low-frequency interference, respectively. Simulation results suggested the low-pass filter and comb filter working together effectively filtered out the interference of EIT on EEG in the process of synchronous monitoring.ResultsAs a result, the normal EEG and epileptic EEG could be recognized effectively. Pearson correlation analysis further confirmed the interference of EIT on EEG was effectively suppressed.ConclusionsThis study provides a simple and effective interference suppression method for the synchronous monitoring of EIT and EEG, which could be served as a reference for the synchronous monitoring of EEG and other medical electromagnetic devices.
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Koh RGL, Zariffa J, Jabban L, Yen SC, Donaldson N, Metcalfe BW. Tutorial: A guide to techniques for analysing recordings from the peripheral nervous system. J Neural Eng 2022; 19. [PMID: 35772397 DOI: 10.1088/1741-2552/ac7d74] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 06/30/2022] [Indexed: 11/11/2022]
Abstract
The nervous system, through a combination of conscious and automatic processes, enables the regulation of the body and its interactions with the environment. The peripheral nervous system is an excellent target for technologies that seek to modulate, restore or enhance these abilities as it carries sensory and motor information that most directly relates to a target organ or function. However, many applications require a combination of both an effective peripheral nerve interface and effective signal processing techniques to provide selective and stable recordings. While there are many reviews on the design of peripheral nerve interfaces, reviews of data analysis techniques and translational considerations are limited. Thus, this tutorial aims to support new and existing researchers in the understanding of the general guiding principles, and introduces a taxonomy for electrode configurations, techniques and translational models to consider.
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Affiliation(s)
- Ryan G L Koh
- IBBME, University of Toronto, Rosebrugh Bldg, 164 College St Room 407, Toronto, Ontario, M5S 3G9, CANADA
| | - Jose Zariffa
- Research, Toronto Rehabilitation Institute - University Health Network, 550 University Ave, #12-102, Toronto, Ontario, M5G 2A2, CANADA
| | - Leen Jabban
- Electronic and Electrical Engineering, University of Bath, Electronic and Electrical Engineering, Claverton Down, Bath, Bath, BA2 7AY, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Shih-Cheng Yen
- Engineering Design and Innovation Centre, National University of Singapore, 21 Lower Kent Ridge Road, Singapore, 119077, SINGAPORE
| | - Nick Donaldson
- Medical Physics and Bioengineering, University College London, Gower Street, London, WC1E 6BT, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Benjamin W Metcalfe
- Electronics & Electrical Engineering, University of Bath, Claverton Down, Bath, Somerset, BA2 7JY, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
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Paldanius A, Dekdouk B, Toivanen J, Kolehmainen V, Hyttinen J. Sensitivity Analysis Highlights the Importance of Accurate Head Models for Electrical Impedance Tomography Monitoring of Intracerebral Hemorrhagic Stroke. IEEE Trans Biomed Eng 2022; 69:1491-1501. [PMID: 34665718 DOI: 10.1109/tbme.2021.3120929] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
OBJECTIVE Electrical impedance tomography (EIT) has been proposed as a novel tool for diagnosing stroke. However, so far, the clinical feasibility is unresolved. In this study, we aim to investigate the need for accurate head modeling in EIT and how the inhomogeneities of the head contribute to the EIT measurement and affect its feasibility in monitoring the progression of a hemorrhagic stroke. METHODS We compared anatomically detailed six- and three-layer finite element models of a human head and computed the resulting scalp electrode potentials and the lead fields of selected electrode configurations. We visualized the resulting EIT measurement sensitivity distributions, computed the scalp electrode potentials, and examined the inverse imaging with selected cases. The effect of accurate tissue geometry and conductivity values on the EIT measurement is assessed with multiple different hemorrhagic perturbation locations and sizes. RESULTS Our results show that accurate tissue geometries and conductivity values inside the cranial cavity, especially the highly conductive cerebrospinal fluid, significantly affect EIT measurement sensitivity distribution and measured potentials. CONCLUSIONS We can conclude that the three-layer head models commonly used in EIT literature cannot depict the current paths correctly in the head. Thus, our study highlights the need to consider the detailed geometry of the cerebrospinal fluid (CSF) in EIT. SIGNIFICANCE The results clearly show that the CSF should be considered in the head EIT calculations.
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Ke XY, Hou W, Huang Q, Hou X, Bao XY, Kong WX, Li CX, Qiu YQ, Hu SY, Dong LH. Advances in electrical impedance tomography-based brain imaging. Mil Med Res 2022; 9:10. [PMID: 35227324 PMCID: PMC8883715 DOI: 10.1186/s40779-022-00370-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Accepted: 02/08/2022] [Indexed: 11/10/2022] Open
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.
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Affiliation(s)
- Xi-Yang Ke
- Department of Radiation Oncology and Therapy, The First Hospital of Jilin University, 130021, Changchun, China.,Jilin Provincial Key Laboratory of Radiation Oncology and Therapy, The First Hospital of Jilin University, Changchun, 130021, China.,NHC Key Laboratory of Radiobiology, School of Public Health, Jilin University, Changchun, 130021, China
| | - Wei Hou
- Department of Radiation Oncology and Therapy, The First Hospital of Jilin University, 130021, Changchun, China.,Jilin Provincial Key Laboratory of Radiation Oncology and Therapy, The First Hospital of Jilin University, Changchun, 130021, China.,NHC Key Laboratory of Radiobiology, School of Public Health, Jilin University, Changchun, 130021, China
| | - Qi Huang
- CAS Key Laboratory of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, Jiangsu, China
| | - Xue Hou
- Department of Radiation Oncology and Therapy, The First Hospital of Jilin University, 130021, Changchun, China.,Jilin Provincial Key Laboratory of Radiation Oncology and Therapy, The First Hospital of Jilin University, Changchun, 130021, China.,NHC Key Laboratory of Radiobiology, School of Public Health, Jilin University, Changchun, 130021, China
| | - Xue-Ying Bao
- Department of Radiation Oncology and Therapy, The First Hospital of Jilin University, 130021, Changchun, China.,Jilin Provincial Key Laboratory of Radiation Oncology and Therapy, The First Hospital of Jilin University, Changchun, 130021, China.,NHC Key Laboratory of Radiobiology, School of Public Health, Jilin University, Changchun, 130021, China
| | - Wei-Xuan Kong
- Department of Radiation Oncology and Therapy, The First Hospital of Jilin University, 130021, Changchun, China.,Jilin Provincial Key Laboratory of Radiation Oncology and Therapy, The First Hospital of Jilin University, Changchun, 130021, China
| | - Cheng-Xiang Li
- Department of Radiation Oncology and Therapy, The First Hospital of Jilin University, 130021, Changchun, China.,Jilin Provincial Key Laboratory of Radiation Oncology and Therapy, The First Hospital of Jilin University, Changchun, 130021, China.,NHC Key Laboratory of Radiobiology, School of Public Health, Jilin University, Changchun, 130021, China
| | - Yu-Qi Qiu
- Department of Radiation Oncology and Therapy, The First Hospital of Jilin University, 130021, Changchun, China.,Jilin Provincial Key Laboratory of Radiation Oncology and Therapy, The First Hospital of Jilin University, Changchun, 130021, China.,NHC Key Laboratory of Radiobiology, School of Public Health, Jilin University, Changchun, 130021, China
| | - Si-Yi Hu
- CAS Key Laboratory of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, Jiangsu, China.
| | - Li-Hua Dong
- Department of Radiation Oncology and Therapy, The First Hospital of Jilin University, 130021, Changchun, China. .,Jilin Provincial Key Laboratory of Radiation Oncology and Therapy, The First Hospital of Jilin University, Changchun, 130021, China. .,NHC Key Laboratory of Radiobiology, School of Public Health, Jilin University, Changchun, 130021, China.
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Abboud T, Mielke D, Rohde V. Mini Review: Impedance Measurement in Neuroscience and Its Prospective Application in the Field of Surgical Neurooncology. Front Neurol 2022; 12:825012. [PMID: 35111132 PMCID: PMC8801870 DOI: 10.3389/fneur.2021.825012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 12/27/2021] [Indexed: 11/13/2022] Open
Abstract
Impedance measurement of human tissue can be performed either in vivo or ex vivo. The majority of the in-vivo approaches are non-invasive, and few are invasive. To date, there is no gold standard for impedance measurement of intracranial tissue. In addition, most of the techniques addressing this topic are still experimental and have not found their way into clinical practice. This review covers available impedance measurement approaches in the neuroscience in general and specifically addresses recent advances made in the application of impedance measurement in the field of surgical neurooncology. It will provide an understandable picture on impedance measurement and give an overview of limitations that currently hinders clinical application and require future technical and conceptual solutions.
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Witkowska-Wrobel A, Aristovich K, Crawford A, Perkins JD, Holder D. Imaging of focal seizures with Electrical Impedance Tomography and depth electrodes in real time. Neuroimage 2021; 234:117972. [PMID: 33757909 PMCID: PMC8204270 DOI: 10.1016/j.neuroimage.2021.117972] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2020] [Revised: 01/31/2021] [Accepted: 03/12/2021] [Indexed: 11/26/2022] Open
Abstract
Intracranial EEG is the current gold standard technique for localizing seizures for surgery, but it can be insensitive to tangential dipole or distant sources. Electrical Impedance Tomography (EIT) offers a novel method to improve coverage and seizure onset localization. The feasibility of EIT has been previously assessed in a computer simulation, which revealed an improved accuracy of seizure detection with EIT compared to intracranial EEG. In this study, slow impedance changes, evoked by cell swelling occurring over seconds, were reconstructed in real time by frequency division multiplexing EIT using depth and subdural electrodes in a swine model of epilepsy. EIT allowed to generate repetitive images of ictal events at similar time course to fMRI but without its significant limitations. EIT was recorded with a system consisting of 32 parallel current sources and 64 voltage recorders. Seizures triggered with intracranial injection of benzylpenicillin (BPN) in five pigs caused a repetitive peak impedance increase of 3.4 ± 1.5 mV and 9.5 ± 3% (N =205 seizures); the impedance signal change was seen already after a single, first seizure. EIT enabled reconstruction of the seizure onset 9 ± 1.5 mm from the BPN cannula and 7.5 ± 1.1 mm from the closest SEEG contact (p<0.05, n =37 focal seizures in three pigs) and it could address problems with sampling error in intracranial EEG. The amplitude of the impedance change correlated with the spread of the seizure on the SEEG (p <<0.001, n =37). The results presented here suggest that combining a parallel EIT system with intracranial EEG monitoring has a potential to improve the diagnostic yield in epileptic patients and become a vital tool in improving our understanding of epilepsy.
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Affiliation(s)
| | - Kirill Aristovich
- Medical Physics and Biomedical Engineering, University College London, UK
| | - Abbe Crawford
- Royal Veterinary College, Hawkshead Lane, North Mymms, Hatfield, Hertfordshire AL9 7TA, UK
| | - Justin D Perkins
- Royal Veterinary College, Hawkshead Lane, North Mymms, Hatfield, Hertfordshire AL9 7TA, UK
| | - David Holder
- Medical Physics and Biomedical Engineering, University College London, UK
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Groenendaal W, Lee S, van Hoof C. Wearable Bioimpedance Monitoring: Viewpoint for Application in Chronic Conditions. JMIR BIOMEDICAL ENGINEERING 2021; 6:e22911. [PMID: 38907374 PMCID: PMC11041432 DOI: 10.2196/22911] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 03/01/2021] [Accepted: 04/06/2021] [Indexed: 01/20/2023] Open
Abstract
Currently, nearly 6 in 10 US adults are suffering from at least one chronic condition. Wearable technology could help in controlling the health care costs by remote monitoring and early detection of disease worsening. However, in recent years, there have been disappointments in wearable technology with respect to reliability, lack of feedback, or lack of user comfort. One of the promising sensor techniques for wearable monitoring of chronic disease is bioimpedance, which is a noninvasive, versatile sensing method that can be applied in different ways to extract a wide range of health care parameters. Due to the changes in impedance caused by either breathing or blood flow, time-varying signals such as respiration and cardiac output can be obtained with bioimpedance. A second application area is related to body composition and fluid status (eg, pulmonary congestion monitoring in patients with heart failure). Finally, bioimpedance can be used for continuous and real-time imaging (eg, during mechanical ventilation). In this viewpoint, we evaluate the use of wearable bioimpedance monitoring for application in chronic conditions, focusing on the current status, recent improvements, and challenges that still need to be tackled.
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Affiliation(s)
| | - Seulki Lee
- Imec the Netherlands / Holst Centre, Eindhoven, Netherlands
| | - Chris van Hoof
- Imec, Leuven, Belgium
- One Planet Research Center, Wageningen, Netherlands
- Department of Engineering Science, KU Leuven, Leuven, Belgium
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Hannan S, Aristovich K, Faulkner M, Avery J, Walker MC, Holder DS. Imaging slow brain activity during neocortical and hippocampal epileptiform events with electrical impedance tomography. Physiol Meas 2021; 42:014001. [PMID: 33361567 DOI: 10.1088/1361-6579/abd67a] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
OBJECTIVE Electrical impedance tomography (EIT) is an imaging technique that produces tomographic images of internal impedance changes within an object using surface electrodes. It can be used to image the slow increase in cerebral tissue impedance that occurs over seconds during epileptic seizures, which is attributed to cell swelling due to disturbances in ion homeostasis following hypersynchronous neuronal firing and its associated metabolic demands. In this study, we characterised and imaged this slow impedance response during neocortical and hippocampal epileptiform events in the rat brain and evaluated its relationship to the underlying neural activity. APPROACH Neocortical or hippocampal seizures, comprising repeatable series of high-amplitude ictal spikes, were induced by electrically stimulating the sensorimotor cortex or perforant path of rats anaesthetised with fentanyl-isoflurane. Transfer impedances were measured during ≥30 consecutive seizures, by applying a sinusoidal current through independent electrode pairs on an epicortical array, and combined to generate an EIT image of slow activity. MAIN RESULTS The slow impedance responses were consistently time-matched to the end of seizures and EIT images of this activity were reconstructed reproducibly in all animals (p < 0.03125, N = 5). These displayed foci of activity that were spatially confined to the facial somatosensory cortex and dentate gyrus for neocortical and hippocampal seizures, respectively, and encompassed a larger volume as the seizure progressed. Centre-of-mass analysis of reconstructions revealed that this activity corresponded to the true location of the epileptogenic zone, as determined by EEG recordings and fast neural EIT measurements which were obtained simultaneously. SIGNIFICANCE These findings suggest that the slow impedance response presents a reliable marker of hypersynchronous neuronal activity during epileptic seizures and can thus be utilised for investigating the mechanisms of epileptogenesis in vivo and for aiding localisation of the epileptogenic zone during presurgical evaluation of patients with refractory epilepsies.
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Affiliation(s)
- Sana Hannan
- Department of Medical Physics and Biomedical Engineering, University College London, United Kingdom
| | - Kirill Aristovich
- Department of Medical Physics and Biomedical Engineering, University College London, United Kingdom
| | - Mayo Faulkner
- Wolfson Institute for Biomedical Research, University College London, United Kingdom
| | - James Avery
- Department of Surgery and Cancer, Imperial College London, United Kingdom
| | - Matthew C Walker
- UCL Queen Square Institute of Neurology, University College London, United Kingdom
| | - David S Holder
- Department of Medical Physics and Biomedical Engineering, University College London, United Kingdom
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Mansouri S, Alharbi Y, Haddad F, Chabcoub S, Alshrouf A, Abd-Elghany AA. Electrical Impedance Tomography - Recent Applications and Developments. JOURNAL OF ELECTRICAL BIOIMPEDANCE 2021; 12:50-62. [PMID: 35069942 PMCID: PMC8667811 DOI: 10.2478/joeb-2021-0007] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Indexed: 06/12/2023]
Abstract
Electrical impedance tomography (EIT) is a low-cost noninvasive imaging method. The main purpose of this paper is to highlight the main aspects of the EIT method and to review the recent advances and developments. The advances in instrumentation and in the different image reconstruction methods and systems are demonstrated in this review. The main applications of the EIT are presented and a special attention made to the papers published during the last years (from 2015 until 2020). The advantages and limitations of EIT are also presented. In conclusion, EIT is a promising imaging approach with a strong potential that has a large margin of progression before reaching the maturity phase.
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Affiliation(s)
- Sofiene Mansouri
- Department of Biomedical Technology, College of Applied Medical Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj, Saudi Arabia
- Laboratory of Biophysics and Medical Technologies, Higher Institute of Medical Technologies of Tunis, University of Tunis El Manar, TunisTunisia
| | - Yousef Alharbi
- Department of Biomedical Technology, College of Applied Medical Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj, Saudi Arabia
| | - Fatma Haddad
- Laboratory of Biophysics and Medical Technologies, Higher Institute of Medical Technologies of Tunis, University of Tunis El Manar, TunisTunisia
| | - Souhir Chabcoub
- Laboratory of Biophysics and Medical Technologies, Higher Institute of Medical Technologies of Tunis, University of Tunis El Manar, TunisTunisia
| | - Anwar Alshrouf
- Department of Biomedical Technology, College of Applied Medical Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj, Saudi Arabia
| | - Amr A. Abd-Elghany
- Department of Biomedical Technology, College of Applied Medical Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj, Saudi Arabia
- Biophysics Department, Faculty of Science, Cairo University, CairoEgypt
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Ravagli E, Mastitskaya S, Thompson N, Iacoviello F, Shearing PR, Perkins J, Gourine AV, Aristovich K, Holder D. Imaging fascicular organization of rat sciatic nerves with fast neural electrical impedance tomography. Nat Commun 2020; 11:6241. [PMID: 33288760 PMCID: PMC7721735 DOI: 10.1038/s41467-020-20127-x] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Accepted: 11/13/2020] [Indexed: 02/06/2023] Open
Abstract
Imaging compound action potentials (CAPs) in peripheral nerves could help avoid side effects in neuromodulation by selective stimulation of identified fascicles. Existing methods have low resolution, limited imaging depth, or are invasive. Fast neural electrical impedance tomography (EIT) allows fascicular CAP imaging with a resolution of <200 µm, <1 ms using a non-penetrating flexible nerve cuff electrode array. Here, we validate EIT imaging in rat sciatic nerve by comparison to micro-computed tomography (microCT) and histology with fluorescent dextran tracers. With EIT, there are reproducible localized changes in tissue impedance in response to stimulation of individual fascicles (tibial, peroneal and sural). The reconstructed EIT images correspond to microCT scans and histology, with significant separation between the fascicles (p < 0.01). The mean fascicle position is identified with an accuracy of 6% of nerve diameter. This suggests fast neural EIT can reliably image the functional fascicular anatomy of the nerves and so aid selective neuromodulation.
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Affiliation(s)
- Enrico Ravagli
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Svetlana Mastitskaya
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK.
| | - Nicole Thompson
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Francesco Iacoviello
- Electrochemical Innovation Laboratory, Department of Chemical Engineering, University College London, London, UK
| | - Paul R Shearing
- Electrochemical Innovation Laboratory, Department of Chemical Engineering, University College London, London, UK
| | - Justin Perkins
- Clinical Science and Services, Royal Veterinary College, Hawkshead Lane, Hatfield, UK
| | - Alexander V Gourine
- Centre for Cardiovascular and Metabolic Neuroscience, Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Kirill Aristovich
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - David Holder
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
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Hannan S, Faulkner M, Aristovich K, Avery J, Walker MC, Holder DS. In vivo imaging of deep neural activity from the cortical surface during hippocampal epileptiform events in the rat brain using electrical impedance tomography. Neuroimage 2020; 209:116525. [DOI: 10.1016/j.neuroimage.2020.116525] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Revised: 12/12/2019] [Accepted: 01/06/2020] [Indexed: 02/07/2023] Open
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Abstract
Candidates for epilepsy surgery must undergo presurgical evaluation to establish whether and how surgical treatment can stop seizures without causing neurological deficits. Various techniques, including MRI, PET, single-photon emission CT, video-EEG, magnetoencephalography and invasive EEG, aim to identify the diseased brain tissue and the involved network. Recent technical and methodological developments, encompassing both advances in existing techniques and new combinations of technologies, are enhancing the ability to define the optimal resection strategy. Multimodal interpretation and predictive computer models are expected to aid surgical planning and patient counselling, and multimodal intraoperative guidance is likely to increase surgical precision. In this Review, we discuss how the knowledge derived from these new approaches is challenging our way of thinking about surgery to stop focal seizures. In particular, we highlight the importance of looking beyond the EEG seizure onset zone and considering focal epilepsy as a brain network disease in which long-range connections need to be taken into account. We also explore how new diagnostic techniques are revealing essential information in the brain that was previously hidden from view.
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Zhu D, McEwan A, Eiber C. Microelectrode array electrical impedance tomography for fast functional imaging in the thalamus. Neuroimage 2019; 198:44-52. [PMID: 31108212 DOI: 10.1016/j.neuroimage.2019.05.023] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2019] [Revised: 04/26/2019] [Accepted: 05/09/2019] [Indexed: 10/26/2022] Open
Abstract
Electrical Impedance Tomography (EIT) has the potential to be able to observe functional tomographic images of neural activity in the brain at millisecond time-scales. Prior modelling and experimental work has shown that EIT is capable of imaging impedance changes from neural depolarisation in rat somatosensory cortex. Here, we investigate the feasibility of EIT for imaging impedance changes using a stereotaxically implanted microelectrode array in the thalamus. Microelectrode array EIT was simulated using an anatomically accurate marmoset brain model. Impedance imaging was validated and detectability estimated using physiological noise recorded from the marmoset visual thalamus. The results suggest that visual-input-driven impedance changes in visual subcortical bodies within 300 μm of the implanted array could be reliably reconstructed and localised, comparable to local field potential measurements. Furthermore, we demonstrated that microelectrode array EIT could reconstruct concurrent activity in multiple subcortical bodies simultaneously.
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Affiliation(s)
- Danyi Zhu
- School of Electrical and Information Engineering, The University of Sydney, Camperdown, NSW, Australia
| | - Alistair McEwan
- School of Electrical and Information Engineering, The University of Sydney, Camperdown, NSW, Australia
| | - Calvin Eiber
- Save Sight Institute, The University of Sydney, 8 Macquarie St, Sydney, NSW, Australia; School of Medical Sciences, University of Sydney, Sydney, NSW, Australia; Australian Research Council Centre of Excellence for Integrative Brain Function, Australia.
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15
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Zhang G, Li W, Ma H, Liu X, Dai M, Xu C, Li H, Dong X, Sun X, Fu F. An on-line processing strategy for head movement interferences removal of dynamic brain electrical impedance tomography based on wavelet decomposition. Biomed Eng Online 2019; 18:55. [PMID: 31072348 PMCID: PMC6509801 DOI: 10.1186/s12938-019-0668-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2018] [Accepted: 04/04/2019] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Head movement interferences are a common problem during prolonged dynamic brain electrical impedance tomography (EIT) clinical monitoring. Head movement interferences mainly originate from body movements of patients and nursing procedures performed by medical staff, etc. These body movements will lead to variation in boundary voltage signals, which affects image reconstruction. METHODS This study employed a data preprocessing method based on wavelet decomposition to inhibit head movement interferences in brain EIT data. Mixed Gaussian models were applied to describe the distribution characteristics of brain EIT data. We identified head movement signal through the differences in distribution characteristics of corresponding wavelet decomposition coefficients between head movement artifacts and normal signals, and then managed the contaminated data with improved on-line wavelet processing methods. RESULTS To validate the efficacy of the method, simulated signal experiments and human data experiments were performed. In the simulation experiment, the simulated movement artifact was significantly reduced and data quality was improved with indicators' increase in PRD and correlation coefficient. Human data experiments demonstrated that this method effectively suppressed head movement in signals and reduce artifacts resulting from head movement artifacts in images. CONCLUSION In this paper, we proposed an on-line strategy to manage the head movement interferences from the brain EIT data based on the distribution characteristics of wavelet coefficients. Our strategy is capable of reducing the movement interference in the data and improving the reconstructed images. This work would improve the clinical practicability of brain EIT and contribute to its further promotion.
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Affiliation(s)
- Ge Zhang
- Department of Radiology, Bethune International Peace Hospital, Shijiazhuang, China.,Department of Biomedical Engineering, Fourth Military Medical University, Xi'an, China
| | - Weichen Li
- Department of Biomedical Engineering, Fourth Military Medical University, Xi'an, China
| | - Hang Ma
- Department of Biomedical Engineering, Fourth Military Medical University, Xi'an, China
| | - Xuechao Liu
- Department of Biomedical Engineering, Fourth Military Medical University, Xi'an, China
| | - Meng Dai
- Department of Biomedical Engineering, Fourth Military Medical University, Xi'an, China
| | - Canhua Xu
- Department of Biomedical Engineering, Fourth Military Medical University, Xi'an, China
| | - Haoting Li
- Department of Biomedical Engineering, Fourth Military Medical University, Xi'an, China
| | - Xiuzhen Dong
- Department of Biomedical Engineering, Fourth Military Medical University, Xi'an, China
| | - Xingwang Sun
- Department of Radiology, Bethune International Peace Hospital, Shijiazhuang, China.
| | - Feng Fu
- Department of Biomedical Engineering, Fourth Military Medical University, Xi'an, China.
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16
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Avery J, Dowrick T, Witkowska-Wrobel A, Faulkner M, Aristovich K, Holder D. Simultaneous EIT and EEG using frequency division multiplexing. Physiol Meas 2019; 40:034007. [DOI: 10.1088/1361-6579/ab0bbc] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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17
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Hannan S, Faulkner M, Aristovich K, Avery J, Walker M, Holder D. Imaging fast electrical activity in the brain during ictal epileptiform discharges with electrical impedance tomography. NEUROIMAGE-CLINICAL 2018; 20:674-684. [PMID: 30218899 PMCID: PMC6140294 DOI: 10.1016/j.nicl.2018.09.004] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/27/2018] [Revised: 07/27/2018] [Accepted: 09/02/2018] [Indexed: 12/19/2022]
Abstract
Electrical Impedance Tomography (EIT) is an emerging medical imaging technique which can produce tomographic images of internal impedance changes within an object using non-penetrating surface electrodes. It has previously been used to image impedance changes due to neuronal depolarisation during evoked potentials in the rat somatosensory cortex with a resolution of 2 ms and <200 μm, using an epicortical electrode array. The purpose of this work was to use this technique to elucidate the intracortical spatiotemporal trajectory of ictal spike-and-wave discharges (SWDs), induced by electrical stimulation in an acute rat model of epilepsy, throughout the cerebral cortex. Seizures lasting 16.5 ± 5.3 s with repetitive 2-5 Hz SWDs were induced in five rats anaesthetised with fentanyl-isoflurane. Transfer impedance measurements were obtained during each seizure with a 57-electrode epicortical array by applying 50 μA current at 1.7 kHz to two electrodes and recording voltages from all remaining electrodes. Images were reconstructed from averaged SWD-related impedance traces obtained from EIT measurements in successive seizures. We report the occurrence of reproducible impedance changes during the initial spike phase, which had an early onset in the whisker barrel cortex and spread posteriorly, laterally and ventrally over 20 ms (p < 0.03125, N = 5). These findings, which confirm and extend knowledge of SWD initiation and expression, suggest that EIT is a valuable neuroimaging tool for improving understanding of neural circuits implicated in epileptic phenomena.
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Affiliation(s)
- Sana Hannan
- Department of Medical Physics and Biomedical Engineering, University College London, UK.
| | - Mayo Faulkner
- Department of Medical Physics and Biomedical Engineering, University College London, UK
| | - Kirill Aristovich
- Department of Medical Physics and Biomedical Engineering, University College London, UK
| | - James Avery
- Department of Medical Physics and Biomedical Engineering, University College London, UK
| | | | - David Holder
- Department of Medical Physics and Biomedical Engineering, University College London, UK
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Faulkner M, Hannan S, Aristovich K, Avery J, Holder D. Feasibility of imaging evoked activity throughout the rat brain using electrical impedance tomography. Neuroimage 2018; 178:1-10. [DOI: 10.1016/j.neuroimage.2018.05.022] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2018] [Revised: 04/26/2018] [Accepted: 05/08/2018] [Indexed: 10/16/2022] Open
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Aristovich K, Donegá M, Blochet C, Avery J, Hannan S, Chew DJ, Holder D. Imaging fast neural traffic at fascicular level with electrical impedance tomography: proof of principle in rat sciatic nerve. J Neural Eng 2018; 15:056025. [DOI: 10.1088/1741-2552/aad78e] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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