Ex-Vivo Characterization of Bioimpedance Spectroscopy of Normal, Ischemic and Hemorrhagic Rabbit Brain Tissue at Frequencies from 10 Hz to 1 MHz

Multi-Path Fusion in SFCF-Net for Enhanced Multi-Frequency Electrical Impedance Tomography

Multi-frequency electrical impedance tomography (mfEIT) offers a nondestructive imaging technology that reconstructs the distribution of electrical characteristics within a subject based on the impedance spectral differences among biological tissues. However, the technology faces challenges in imaging multi-class lesion targets when the conductivity of background tissues is frequency-dependent. To address these issues, we propose a spatial-frequency cross-fusion network (SFCF-Net) imaging algorithm, built on a multi-path fusion structure. This algorithm uses multi-path structures and hyper-dense connections to capture both spatial and frequency correlations between multi-frequency conductivity images, which achieves differential imaging for lesion targets of multiple categories through cross-fusion of information. According to both simulation and physical experiment results, the proposed SFCF-Net algorithm shows an excellent performance in terms of lesion imaging and category discrimination compared to the weighted frequency-difference, U-Net, and MMV-Net algorithms. The proposed algorithm enhances the ability of mfEIT to simultaneously obtain both structural and spectral information from the tissue being examined and improves the accuracy and reliability of mfEIT, opening new avenues for its application in clinical diagnostics and treatment monitoring.

Exploratory study of a multifrequency EIT-based method for detecting intracranial abnormalities

Objective

The purpose of this paper is to compare the differences in the features of multifrequency electrical impedance tomography (MFEIT) images of human heads between healthy subjects and patients with brain diseases and to explore the possibility of applying MFEIT to intracranial abnormality detection.

Methods

Sixteen healthy volunteers and 8 patients with brain diseases were recruited as subjects, and the cerebral MFEIT data of 9 frequencies in the range of 21 kHz - 100 kHz of all subjects were acquired with an MFEIT system. MFEIT image sequences were obtained according to certain imaging algorithms, and the area ratio of the ROI (AR_ROI) and the mean value of the reconstructed resistivity change of the ROI (MVRRC_ROI) on both the left and right sides of these images were extracted. The geometric asymmetry index (GAI) and intensity asymmetry index (IAI) were further proposed to characterize the symmetry of MFEIT images based on the extracted indices and to statistically compare and analyze the differences between the two groups of subjects on MFEIT images.

Results

There were no significant differences in either the AR_ROI or the MVRRC_ROI between the two sides of the brains of healthy volunteers (p > 0.05); some of the MFEIT images mainly in the range of 30 kHz - 60 kHz of patients with brain diseases showed stronger resistivity distributions (larger area or stronger signal) that were approximately symmetric with the location of the lesions. However, statistical analysis showed that the AR_ROI and the MVRRC_ROI on the healthy sides of MFEIT images of patients with unilateral brain disease were not significantly different from those on the affected side (p > 0.05). The GAI and IAI were higher in all patients with brain diseases than in healthy volunteers except for 80 kHz (p < 0.05).

Conclusion

There were significant differences in the geometric symmetry and the signal intensity symmetry of the reconstructed targets in the MFEIT images between healthy volunteers and patients with brain diseases, and the above findings provide a reference for the rapid detection of intracranial abnormalities using MFEIT images and may provide a basis for further exploration of MFEIT for the detection of brain diseases.

Electrical bioimpedance measurement and near-infrared spectroscopy in pediatric postoperative neurocritical care: a prospective observational study

Background

To investigate the clinical significance of the disturbance coefficient (DC) and regional cerebral oxygen saturation (rSO₂) as obtained through the use of electrical bioimpedance and near-infrared spectroscopy (NIRS) in pediatric neurocritical care.

Participants and methods

We enrolled 45 pediatric patients as the injury group and 70 healthy children as the control group. DC was derived from impedance analysis of 0.1 mA-50 kHz current via temporal electrodes. rSO₂ was the percentage of oxyhemoglobin measured from reflected NIR light on the forehead. DC and rSO₂ were obtained at 6, 12, 24, 48 and 72 h after surgery for the injury group and during the health screening clinic visit for the control group. We compared DC and rSO₂ between the groups, their changes over time within the injury group and their correlation with intracranial pressure (ICP), cerebral perfusion pressure (CPP), Glasgow coma scale (GCS) score, Glasgow outcome scale (GOS) score, and their ability to diagnose postoperative cerebral edema and predict poor prognosis.

Results

DC and rSO₂ were significantly lower in the injury group than in the control group. In the injury group, ICP increased over the monitoring period, while DC, CPP and rSO₂ decreased. DC was negatively correlated with ICP and positively correlated with GCS score and GOS score. Additionally, lower DC values were observed in patients with signs of cerebral edema, with a DC value of 86.5 or below suggesting the presence of brain edema in patients aged 6-16 years. On the other hand, rSO₂ was positively correlated with CPP, GCS score, and GOS score, with a value of 64.4% or below indicating a poor prognosis. Decreased CPP is an independent risk factor for decreased rSO₂.

Conclusion

DC and rSO₂ monitoring based on electrical bioimpedance and near-infrared spectroscopy not only reflect the degree of brain edema and oxygenation, but also reflect the severity of the disease and predict the prognosis of the patients. This approach offers a real-time, bedside, and accurate method for assessing brain function and detecting postoperative cerebral edema and poor prognosis.

Case-Specific Focal Sensor Design for Cardiac Electrical Impedance Tomography

Electrical impedance tomography (EIT) is a non-invasive detection technology that uses the electrical response value at the boundary of an observation field to image the conductivity changes in an area. When EIT is applied to the thoracic cavity of the human body, the conductivity change caused by the heartbeat will be concentrated in a sub-region of the thoracic cavity, that is, the heart region. In order to improve the spatial resolution of the target region, two sensor optimization methods based on conformal mapping theory were proposed in this study. The effectiveness of the proposed method was verified by simulation and phantom experiment. The qualitative analysis and quantitative index evaluation of the reconstructed image showed that the optimized model could achieve higher imaging accuracy of the heart region compared with the standard sensor. The reconstruction results could effectively reflect the periodic diastolic and systolic movements of the heart and had a better ability to recognize the position of the heart in the thoracic cavity.

Probe Contact Force Monitoring during Conductivity Measurements of the Left Atrial Appendage to Support the Design of Novel Diagnostic and Therapeutic Procedures

The electrical properties of many biological tissues are freely available from the INRC and the IT'IS databases. However, particularly in lower frequency ranges, few studies have investigated the optimal measurement protocol or the key confounders that need to be controlled, monitored, and reported. However, preliminary work suggests that the contact force of the measurement probe on the tissue sample can affect the measurements. The aim of this paper is to investigate the conductivity change due to the probe contact force in detail. Twenty ex vivo bovine heart samples are used, and conductivity measurements are taken in the Left Atrial Appendage, a common target for medical device developments. The conductivity measurements reported in this work (between 0.14 S/m and 0.24 S/m) align with the literature. The average conductivity is observed to change by -21% as the contact force increases from 2 N to 10 N. In contrast, in conditions where the fluid concentration in the measurement area is expected to be lower, very small changes are observed (less than 2.5%). These results suggest that the LAA conductivity is affected by the contact force due to the fluid concentration in the tissue. This work suggests that contact force should be controlled for in all future experiments.

Applications of Electrical Impedance Tomography in Neurology

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.

Assessment of Low Back Pain in Helicopter Pilots Using Electrical Bio-Impedance Technique: A Feasibility Study

Low back pain (LBP) is known to pose a serious threat to helicopter pilots. This study aimed to explore the potential of electrical bio-impedance (EBI) technique with the advantages of no radiation, non-invasiveness and low cost, which is intended to be used as a daily detection tool to assess LBP in primary aviation medical units. The LBP scales (severity) in 72 helicopter pilots were assessed using a pain questionnaire, while the bilateral impedance measurements of the lumbar muscle were carried out with a high precision EBI measurement system. Results showed that the modulus of lumbar muscle impedance increased with LBP scale whereas the phase angle decreased. For different LBP scales, significant differences were found in the modulus of lumbar muscle impedance sum on both sides (Z_sum), as well as in the modulus and phase angle of lumbar muscle impedance difference between both sides (Z_diff and ϕ_diff), respectively (P < 0.05). Moreover, Spearman’s correlation analysis manifested a strong correlation between Z_sum and LBP scale (R = 0.692, P < 0.01), an excellent correlation between Z_diff and LBP scale (R = 0.86, P < 0.01), and a desirable correlation between ϕ_diff and LBP scale (R = −0.858, P < 0.01). In addition, receiver operator characteristic analysis showed that for LBP prediction, the area under receiver operator characteristic curve of Z_sum, Z_diff, and ϕ_diff were 0.931, 0.992, and 0.965, respectively. These findings demonstrated that EBI could sensitively and accurately detect the state of lumbar muscle associated with LBP, which might be the potential tool for daily detection of LBP in primary aviation medical units.

Stimulation Montage Achieves Balanced Focality and Intensity

Transcranial direct current stimulation (tDCS) is a non-invasive neuromodulation technique to treat brain disorders by using a constant, low current to stimulate targeted cortex regions. Compared to the conventional tDCS that uses two large pad electrodes, multiple electrode tDCS has recently received more attention. It is able to achieve better stimulation performance in terms of stimulation intensity and focality. In this paper, we first establish a computational model of tDCS, and then propose a novel optimization algorithm using a regularization matrix λ to explore the balance between stimulation intensity and focality. The simulation study is designed such that the performance of state-of-the-art algorithms and the proposed algorithm can be compared via quantitative evaluation. The results show that the proposed algorithm not only achieves desired intensity, but also smaller target error and better focality. Robustness analysis indicates that the results are stable within the ranges of scalp and cerebrospinal fluid (CSF) conductivities, while the skull conductivity is most sensitive and should be carefully considered in real clinical applications.

Advances in electrical impedance tomography-based brain imaging

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.

Real-time monitoring hypoxia at high altitudes using electrical bioimpedance technique: an animal experiment

Hypoxia poses a serious threat to pilots. The aim of this study was to examine the efficacy of electrical bioimpedance (EBI) in detecting the onset of hypoxia in real time in a rabbit hypoxia model. Thirty-two New Zealand rabbits were divided equally into four groups (control group and three hypoxia groups, i.e., mild, moderate, and severe). Hypoxia was induced by simulating various altitudes in the hypobaric oxygen chamber (3,000 m, 5,000 m, and 8,000 m). Both cerebral impedance and blood oxygen (Sp_O2) were monitored continuously. Results showed that the cerebral impedance increased immediately during the period of increasing altitude and decreased quickly to the initial baseline at the phase of descending altitude. Moreover, the change of cerebral impedance in the mild hypoxia group (3,000 m) was significantly smaller than those in the other two groups (5,000 m and 8,000 m, P < 0.05). The changes in cerebral impedance and Sp_O2 were significantly correlated based on the total of measurement data (r² = 0.628, P < 0.001). Furthermore, the agreement analysis performed with Bland-Altman and standardized residual plots exhibited high concordance between cerebral impedance and Sp_O2. Receiver operator characteristic analysis manifested that the sensitivity, specificity, and area under the curve using cerebral impedance for changes in Sp_O2 >10% were 0.735, 0.826, and 0.845, respectively. These findings demonstrated that EBI could sensitively and accurately monitor changes of cerebral impedance induced by hypoxia, which might provide a potential tool for the real-time and noninvasive monitoring of hypoxic condition of pilots in flight for early identification of hypoxia.NEW & NOTEWORTHY This study is the first to examine the efficacy of electrical bioimpedance (EBI) in detecting the onset of high-altitude hypoxia in real time. The novelty of this research includes three aspects. First, the cerebral impedance of rabbits increased immediately during the rising of altitude and decreased quickly to the initial baseline at the phase of descending altitude. Second, there was a significant correlation and high concordance between cerebral impedance and Sp_O2. Third, cerebral impedance could determine the change of Sp_O2 resulting from hypoxia.

Dielectric Properties of Human Active Liver, Kidney and Spleen Compared to Those of Respective Inactive Tissues, Porcine Tissues and the Data Provided by a Database in the Frequency Range of 10 Hz to 100 MHz

OBJECTIVE

The purpose of this work is to study whether the active state and species of biological tissues can influence changes in their dielectric properties.

METHODS

In this paper, the dielectric properties of liver, kidney and spleen tissues from human active, human inactive and animal tissues are measured in the frequency range of 10 Hz to 100 MHz. The four- and two-electrode methods are used to measure dielectric properties at different frequencies. Statistical analysis and the pattern recognition method are used to compare the dielectric properties of human active tissues, human inactive tissues, animal tissues and data provided by the IFAC database.

RESULTS

The results show that the dielectric properties of human active tissues are significantly different from those of human inactive tissues and animal tissues, resulting in a great difference between the dielectric properties provided by the IFAC database and those of human active tissues. The dielectric properties of human active tissues can be identified by the pattern recognition method based on principal component analysis, which further proves that the dielectric properties of human active tissues cannot be replaced.

CONCLUSION

The dielectric properties of biological tissues are closely related to the activity and species of tissues. The dielectric properties of human active tissues cannot be replaced by those of human cadaver tissues or animal tissues.

SIGNIFICANCE

The significance of this study is suggesting that the IFAC database should be updated with the dielectric properties of human active tissues to provide accurate data for bioelectromagnetics research.

Electrical Impedance Characterization of in Vivo Porcine Tissue Using Machine Learning

The incorporation of sensors onto the stapling platform has been investigated to overcome the disconnect in our understanding of tissue handling by surgical staplers. The goal of this study was to explore the feasibility of in vivo porcine tissue differentiation using bioimpedance data and machine learning methods. In vivo electrical impedance measurements were obtained in 7 young domestic pigs, using a logarithmic sweep of 50 points over a frequency range of 100 Hz to 1 MHz. Tissues studied included lung, liver, small bowel, colon, and stomach, which was further segmented into fundus, body, and antrum. The data was then parsed through MATLAB's classification learner to identify the best algorithm for tissue type differentiation. The most effective classification scheme was found to be cubic support vector machines with 86.96% accuracy. When fundus, body and antrum were aggregated together as stomach, the accuracy improved to 88.03%. The combination of stomach, small bowel, and colon together as GI tract improved accuracy to 99.79% using fine k nearest neighbors. The results suggest that bioimpedance data can be effectively used to differentiate tissue types in vivo. This study is one of the first that combines in vivo bioimpedance tissue data across multiple tissue types with machine learning methods.

Complex Permittivity Measurement of High-Loss Biological Material with Improved Cavity Perturbation Method in the Range of 26.5–40 GHz

In this paper, we performed and designed a new rectangular cavity to identify and analyze the complex permittivity of two cancer cells (Breast-MDA231, Uveal melanoma) that have a high dielectric constant and dielectric loss. The rectangular cavity device is based on the improved cavity perturbation technology. The sample of the improved cavity perturbation device is placed at the position of a/n close to the wall of the cavity, where a is the wide side of the cavity and n is the positive even number. For high-loss biological materials, the improved cavity perturbation method has higher accuracy than the traditional cavity perturbation method. The results present that the relative dielectric constants of a single cell at Ka-band (26.5–40 GHz) are in the range 8–15, and the relative dielectric loss is 24–31. The information of the cancer cells at Ka-band waves can be helpful for further cancer detection and clinical treatment.

An iterative damped least-squares algorithm for simultaneously monitoring the development of hemorrhagic and secondary ischemic lesions in brain injuries

Electrical impedance tomography (EIT) is a non-invasive and real-time imaging method that has the potential to be used for monitoring intracerebral hemorrhage (ICH). Recent studies have proposed that ischemia secondary to ICH occurs simultaneously in the brain. Real-time monitoring of the development of hemorrhage and risk of secondary ischemia is crucial for clinical intervention. However, few studies have explored the performance of EIT monitoring in cases where hemorrhage and secondary ischemia exist. When these lesions get close to each other, or their conductivity and volume changes differ greatly, it becomes challenging for dynamic EIT algorithms to simultaneously reconstruct subtle injuries. To address this, an iterative damped least-squares (IDLS) algorithm is proposed in this study. The quality of the IDLS algorithm was assessed using blur radius and temporal response during computer simulation and a phantom 3D head-shaped model where bidirectional disturbance targets were simulated. The results showed that the IDLS algorithm enhanced contrast and concurrently reconstructed bidirectional disturbance targets in images. Moreover, it showed superior performance in decreasing the blur radius and was time cost-effective. With further improvement, the IDLS algorithm has the potential to be used for monitoring the development of hemorrhage and risk of ischemia secondary to ICH. Graphical abstract (a) and (b) are simulation images of bidirectional disturbance targets with different change ratios of volume (Vr) and conductivity (σ_r) based on the damped least-squares (DLS) algorithm and iterative damped least-squared (IDLS) algorithm, respectively. (c) shows the performance metrics of blur radius and temporal response with different volume ratio (corresponding to Vr). (d) shows the performance metrics of blur radius and temporal response with different conductivity change percentage (corresponding to σ_r).

EIT Imaging of Intracranial Hemorrhage in Rabbit Models Is Influenced by the Intactness of Cranium

Electrical impedance tomography (EIT) has been shown to be a promising, bedside imaging method to monitor the progression of intracranial hemorrhage (ICH). However, the observed impedance changes within brain related to ICH differed among groups, and we hypothesized that the cranium intactness (open or closed) may be the one of potential reasons leading to the difference. Therefore, the aim of this study was to investigate this effect of open or closed cranium on impedance changes within brain in the rabbit ICH model. In this study, we first established the ICH model in 12 rabbits with the open cranium and in 12 rabbits with the closed cranium. Simultaneously, EIT measurements on the rabbits' heads were performed to record the impedance changes caused by injecting the autologous nonheparinized blood into cerebral parenchyma. Finally, the regional impedance changes on EIT images and the whole impedance changes were analyzed. It was surprisingly found that when the cranium was open, the impedance of the area where the blood was injected, as well as the whole brain impedance, decreased with the amount of blood being injected; when the cranium was closed, while the impedance of the area where blood was not injected continued to increase, the impedance of the area where blood was injected decreased within 20s of the blood being injected and then remained almost unchanged, and the whole brain impedance had a small fall and then notably increased. The results have validated that the cranium completeness (open or closed) has influences on impedance changes within brain when using EIT to monitor ICH. In future study on application of EIT to monitor ICH, the cranium completeness should be taken into account for establishing an ICH model and analyzing the corresponding EIT results.

Optimal combination of electrodes and conductive gels for brain electrical impedance tomography

BACKGROUND

Electrical impedance tomography (EIT) is an emerging imaging technology that has been used to monitor brain injury and detect acute stroke. The time and frequency properties of electrode-skin contact impedance are important for brain EIT because brain EIT measurement is performed over a long period when used to monitor brain injury, and is carried out across a wide range of frequencies when used to detect stroke. To our knowledge, no study has simultaneously investigated the time and frequency properties of both electrode and conductive gel for brain EIT.

METHODS

In this study, the contact impedance of 16 combinations consisting of 4 kinds of clinical electrode and five types of commonly used conductive gel was measured on ten volunteers' scalp for a period of 1 h at frequencies from 100 Hz to 1 MHz using the two-electrode method. And then the performance of each combination was systematically evaluated in terms of the magnitude of contact impedance, and changes in contact impedance with time and frequency.

RESULTS

Results showed that combination of Ag⁺/Ag⁺Cl^- powder electrode and low viscosity conductive gel performed best overall (Ten 20^® in this study); it had a relatively low magnitude of contact impedance and superior performance regarding contact impedance with time (p < 0.05) and frequency (p < 0.05).

CONCLUSIONS

Experimental results indicates that the combination of Ag⁺/Ag⁺Cl^- powder electrode and low viscosity conductive gel may be the best choice for brain EIT.

Electrical Impedance Changes at Different Phases of Cerebral Edema in Rats with Ischemic Brain Injury

Cerebral edema contributes significantly to the morbidity and mortality associated with many common neurologic conditions. Clinically, a diagnostic tool that can be used to monitor cerebral edema in real-time and differentiate between different types of cerebral edema is urgently needed. Because there are differences in electrical impedance between normal cortical tissue and cerebral edema tissue, electrical impedance tomography (EIT) can potentially be used to detect cerebral edema. Accurate recording of the electrical impedance properties of cerebral edema tissue at different time points is important when detecting cerebral edema with EIT. In this study, a rat cerebral edema model was established; then, following the onset of ischemic brain injury, variation in the electrical impedance of cerebral edema was measured at different time points within a 24-hour period and the corresponding morphologic variation was analyzed. After the first six hours, following the onset of ischemic brain injury, the resistivity of brain tissue increased (p < 0.05); during this period, brain cell volume increased (p < 0.05) and the intercellular space decreased (p < 0.05) (behaving like cytotoxic cerebral edema). From 6 to 24 hours, the resistivity of brain tissue decreased; during this time, brain cell volume unchanged (p > 0.05) while intercellular space increased (p < 0.05) (behaving like vasogenic cerebral edema). These findings support the notion that EIT can be used to monitor the development of cerebral edema in real-time and differentiate between different types of brain edema.

Ex vivo tissue imaging for radiology-pathology correlation: a pilot study with a small bore 7-T MRI in a rare pigmented ganglioglioma exhibiting complex MR signal characteristics associated with melanin and hemosiderin

To advance magnetic resonance imaging (MRI) technologies further for in vivo tissue characterization with histopathologic validation, we investigated the feasibility of ex vivo tissue imaging of a surgically removed human brain tumor as a comprehensive approach for radiology–pathology correlation in histoanatomically identical fashion in a rare case of pigmented ganglioglioma with complex paramagnetic properties. Pieces of surgically removed ganglioglioma, containing melanin and hemosiderin pigments, were imaged with a small bore 7-T MRI scanner to obtain T1-, T2-, and T2*-weighted image and diffusion tensor imaging (DTI). Corresponding histopathological slides were prepared for routine hematoxylin and eosin stain and special stains for melanin and iron/hemosiderin to correlate with MRI signal characteristics. Furthermore, mean diffusivity (MD) maps were generated from DTI data and correlated with cellularity using image analysis. While the presence of melanin was difficult to interpret in in vivo MRI with certainty due to concomitant hemosiderin pigments and calcium depositions, ex vivo tissue imaging clearly demonstrated pieces of tissue exhibiting the characteristic MR signal pattern for melanin with pathologic confirmation in a histoanatomically identical location. There was also concordant correlation between MD and cellularity. Although it is still in an initial phase of development, ex vivo tissue imaging is a promising approach, which offers radiology–pathology correlation in a straightforward and comprehensive manner.

Evaluation of Electrical Impedance Spectroscopy-on-a-Needle as a Novel Tool to Determine Optimal Surgical Margin in Partial Nephrectomy

A hypodermic needle has been introduced incorporating an electrical impedance spectroscopy (EIS) sensor, called micro-EIS-on-a-needle for depth profiling (μEoN-DP). The μEoN-DP can locate endophytic renal tumors as well as determine tumor margins by detecting the impedance difference between normal and cancer tissues. To evaluate the μEoN-DP as a novel tool to determine the optimal surgical margin during partial nephrectomy (PN), the electrical impedance differences between renal parenchymal tissues and renal cell carcinoma (RCC) tumors are investigated with regard to the distance from the tumors. Optimal frequencies at which the discrimination extent is maximized are suggested based on the discrimination index. The resistance and capacitance of normal and cancer tissues are extracted using electrical equivalent circuit by excluding the influences of other electrical components on the sensor output. The extracted resistance and capacitance of cancer tissues are 37.8% larger and 25.7% smaller than that of normal tissues, respectively. Additionally, high sensitivity and specificity are obtained by using extracted resistance and capacitance, thus implying that the μEoN-DP shows promise as a supplementary tool for PN margin evaluation and decreasing the prevalence of positive surgical margins while maximizing parenchymal preservation.

In Vivo Bioimpedance Spectroscopy Characterization of Healthy, Hemorrhagic and Ischemic Rabbit Brain within 10 Hz-1 MHz

Acute stroke is a serious cerebrovascular disease and has been the second leading cause of death worldwide. Conventional diagnostic modalities for stroke, such as CT and MRI, may not be available in emergency settings. Hence, it is imperative to develop a portable tool to diagnose stroke in a timely manner. Since there are differences in impedance spectra between normal, hemorrhagic and ischemic brain tissues, multi-frequency electrical impedance tomography (MFEIT) shows great promise in detecting stroke. Measuring the impedance spectra of healthy, hemorrhagic and ischemic brain in vivo is crucial to the success of MFEIT. To our knowledge, no research has established hemorrhagic and ischemic brain models in the same animal and comprehensively measured the in vivo impedance spectra of healthy, hemorrhagic and ischemic brain within 10 Hz–1 MHz. In this study, the intracerebral hemorrhage and ischemic models were established in rabbits, and then the impedance spectra of healthy, hemorrhagic and ischemic brain were measured in vivo and compared. The results demonstrated that the impedance spectra differed significantly between healthy and stroke-affected brain (i.e., hemorrhagic or ischemic brain). Moreover, the rate of change in brain impedance following hemorrhagic and ischemic stroke with regard to frequency was distinct. These findings further validate the feasibility of using MFEIT to detect stroke and differentiate stroke types, and provide data supporting for future research.

The Frequency Spectral Properties of Electrode-Skin Contact Impedance on Human Head and Its Frequency-Dependent Effects on Frequency-Difference EIT in Stroke Detection from 10Hz to 1MHz

Frequency-difference electrical impedance tomography (fdEIT) reconstructs frequency-dependent changes of a complex impedance distribution. It has a potential application in acute stroke detection because there are significant differences in impedance spectra between stroke lesions and normal brain tissues. However, fdEIT suffers from the influences of electrode-skin contact impedance since contact impedance varies greatly with frequency. When using fdEIT to detect stroke, it is critical to know the degree of measurement errors or image artifacts caused by contact impedance. To our knowledge, no study has systematically investigated the frequency spectral properties of electrode-skin contact impedance on human head and its frequency-dependent effects on fdEIT used in stroke detection within a wide frequency band (10 Hz-1 MHz). In this study, we first measured and analyzed the frequency spectral properties of electrode-skin contact impedance on 47 human subjects’ heads within 10 Hz-1 MHz. Then, we quantified the frequency-dependent effects of contact impedance on fdEIT in stroke detection in terms of the current distribution beneath the electrodes and the contact impedance imbalance between two measuring electrodes. The results showed that the contact impedance at high frequencies (>100 kHz) significantly changed the current distribution beneath the electrode, leading to nonnegligible errors in boundary voltages and artifacts in reconstructed images. The contact impedance imbalance at low frequencies (<1 kHz) also caused significant measurement errors. We conclude that the contact impedance has critical frequency-dependent influences on fdEIT and further studies on reducing such influences are necessary to improve the application of fdEIT in stroke detection.