Spatial sensitivity distribution assessment and Monte Carlo simulations for needle-based bioimpedance imaging during venipuncture using the finite element method

Despite being among the most common medical procedures, needle insertions suffer from a high error rate. Impedance measurements using electrode-equipped needles offer promise for improved tissue targeting and reduced errors. Impedance visualization usually requires an extensive pre-measured impedance dataset for tissue differentiation and knowledge of the electric fields contributing to the resulting impedances. This work presents two finite element simulation approaches for both problems. The first approach describes the generation of a multitude of impedances with Monte Carlo simulations for both, homogeneous and inhomogeneous tissue to circumvent the need to rely on previously measured data. These datasets could be used for tissue discrimination. The second method describes the simulation of the spatial sensitivity distribution of an electrode layout. Two singularity analysis methods were employed to determine the bulk of the sensitivity within a finite volume, which in turn enables consistent 3D visualization. The modeled electrode layout consists of 12 electrodes radially placed around a hypodermic needle. Electrical excitation was simulated using two neighboring electrodes for current carriage and voltage pickup, which resulted in 12 distinct bipolar excitation states. Both, the impedance simulations and the respective singularity analysis methods were compared with each other. The results show that the statistical spread of impedances is highly dependent on the tissue type and its inhomogeneities. The bounded bulk of sensitivities of both methods are of similar extent and symmetry. Future models should incorporate more detailed tissue properties such as anisotropy or changing material properties due to tissue deformation to gain more accurate predictions.

Needle-Based Electrical Impedance Imaging Technology for Needle Navigation

Needle insertion is a common procedure in modern healthcare practices, such as blood sampling, tissue biopsy, and cancer treatment. Various guidance systems have been developed to reduce the risk of incorrect needle positioning. While ultrasound imaging is considered the gold standard, it has limitations such as a lack of spatial resolution and subjective interpretation of 2D images. As an alternative to conventional imaging techniques, we have developed a needle-based electrical impedance imaging system. The system involves the classification of different tissue types using impedance measurements taken with a modified needle and the visualization in a MATLAB Graphical User Interface (GUI) based on the spatial sensitivity distribution of the needle. The needle was equipped with 12 stainless steel wire electrodes, and the sensitive volumes were determined using Finite Element Method (FEM) simulation. A k-Nearest Neighbors (k-NN) algorithm was used to classify different types of tissue phantoms with an average success rate of 70.56% for individual tissue phantoms. The results showed that the classification of the fat tissue phantom was the most successful (60 out of 60 attempts correct), while the success rate decreased for layered tissue structures. The measurement can be controlled in the GUI, and the identified tissues around the needle are displayed in 3D. The average latency between measurement and visualization was 112.1 ms. This work demonstrates the feasibility of using needle-based electrical impedance imaging as an alternative to conventional imaging techniques. Further improvements to the hardware and the algorithm as well as usability testing are required to evaluate the effectiveness of the needle navigation system.

Intra-radiological pathology-calibrated Electrical Impedance Spectroscopy in the evaluation of excision-required breast lesions

PURPOSE

Evaluating a real-time complementary bioelectrical diagnostic device based on Electrical Impedance Spectroscopy(EIS) for improving breast imaging-reporting and data system (BIRADS) scoring accuracy, especially in high-risk or borderline breast diseases. The primary purpose is to characterize breast tumors based on their dielectric properties. Early detection of high-risk lesions and increasing the accuracy of tumor sampling and pathological diagnosis are secondary objectives of the study.

METHODS

The tumor detection probe (TDP) was first applied to the mouse model for electrical safety evaluations by electrical current measurement, then to 138 human palpable breast lesions undergo CNB, VAB, or FNA with the surgeon's requests. Impedance phase slope(IPS) in frequency ranges of 100 kHz to 500 kHz and impedance magnitude in f = 1kHz were extracted as the classification parameters. Consistency of radiological and pathological declarations for the excisional recommendation was then compared with the IPS values.

RESULTS

Considering pathological results as the gold standard, meaningful correlations between IPS and pathophysiological status of lesions recommended for excision (such as atypical ductal hyperplasia, papillary lesions, complex sclerosing adenosis, and fibroadenoma, etc.) were observed (p<0.0001). These pathophysiological properties may include cells size, membrane permeability, packing density, adenosis, cytoplasm structure, etc. Benign breast lesions showed IPS values greater than zero, while high-risk proliferative, precancerous, or cancerous lesions had negative IPS values. Statistical analysis showed 95% sensitivity with Area Under the Curve(AUC) equal to 0.92.

CONCLUSION

Borderline breast diseases and high-risk lesions that should be excised according to standard guidelines can be diagnosed with TDP before any sampling process. It is a precious outcome for high-risk lesions that are radiologically underestimated to BI-RADS3, specifically in younger patients with dense breast masses, challenging in mammographic and sonographic evaluations. Also, the lowest IPS value detects the most pathologic portions of the tumor for increasing sampling accuracy in large tumors.

SIGNIFICANCE

Precise detection of high-risk breast masses, which may be declared BI-RADS3 instead of BI-RADS4a. This article is protected by copyright. All rights reserved.

Humanin vivoliver and tumor bioimpedance measured with biopsy needle

Objective:Liver biopsy is an essential procedure in cancer diagnostics but targeting the biopsy to the actual tumor tissue is challenging. Aim of this study was to evaluate the clinical feasibility of a novel bioimpedance biopsy needle system in liver biopsy and simultaneously to gatherin vivobioimpedance data from human liver and tumor tissues.Approach:We measured human liver and tumor impedance datain vivofrom 26 patients who underwent diagnostic ultrasound-guided liver biopsy. Our novel 18G core biopsy needle tip forms a bipolar electrode that was used to measure bioimpedance during the biopsy in real-time with frequencies from 1 kHz to 349 kHz. The needle tip location was determined by ultrasound. Also, the sampled tissue type was determined histologically.Main results:The bioimpedance values showed substantial variation between individual cases, and liver and tumor data overlapped each other. However, Mann-Whitney U test showed that the median bioimpedance values of liver and tumor tissue are significantly (p<0.05) different concerning the impedance magnitude at frequencies below 25 kHz and the phase angle at frequencies below 3 kHz and above 30 kHz.Significance:This study uniquely employed a real-time bioimpedance biopsy needle in clinical liver biopsies and reported the measured humanin vivoliver and tumor impedance data. Impedance is always device-dependent and therefore not directly comparable to measurements with other devices. Although the variation in tumor types prevented coherent tumor identification, our study provides preliminary evidence that tumor tissue differs from liver tissuein vivoand this association is frequency-dependent.

Smart Bio-Impedance-Based Sensor for Guiding Standard Needle Insertion

A venipuncture is the most common non-invasive medical procedure, and is frequently used with patients; however, a high probability of post-injection complications accompanies intravenous injection. The most common complication is a hematoma, which is associated with puncture of the uppermost and lowermost walls. To simplify and reduce complications of the venipuncture procedure, and as well as automation of this process, a device that can provide information of the needle tip position into patient’s tissues needs to be developed. This paper presents a peripheral vascular puncture control system based on electrical impedance measurements. A special electrode system was designed to achieve the maximum sensitivity for puncture identification using a traditional needle, which is usually used in clinical practice. An experimental study on subjects showed that the electrical impedance signal changed significantly once the standard needle entered the blood vessel. On basis of theoretical and experimental studies, a decision rule of puncture identification based on the analysis of amplitude-time parameters of experimental signals was proposed. The proposed method was tested on 15 test and 9 control samples, with the results showing that 97% accuracy was obtained.

Development of a tissue discrimination electrode embedded surgical needle using vibro-tactile feedback derived from electric impedance spectroscopy

Some tumours may not be detected by ultrasound during biopsy, but recent evidence has shown that different tissues can be discerned by electric impedance. This paper explores the application of vibrotactile feedback in an electrode embedded needle to help classify tissue during fine-needle aspiration biopsy from bioimpedance measurements. The process uses electric impedance spectroscopy from 10 Hz to 349 kHz to fit the double-dispersion Cole model through the Newton-Raphson algorithm. A Naive Bayes classifier is then used on the equivalent circuit parameters to estimate the tissue at the needle tip. The method is validated through a series of experiments and user trials. The results show that the vibrotactile feedback is able to help the operator in determining the tissue the needle is in, suggesting that this may prove to be a useful supplement to the standard procedure used today. Graphical Abstract This paper explores the application of vibrotactile feedback for an electrode embedded needle to help classify tissue from electric impedance measurements. The data is fit to an equivalent circuit using Newton- Raphon's method. A Naive Bayes classifier is trained and later used in an experiment to estimate the tissue at the needle tip and provide an assigned vibrotacticle feedback to the user.

Electric impedance spectroscopy feature extraction for tissue classification with electrode embedded surgical needles through a modified forward stepwise method

There has been a growing interest in developing electric impedance sensing surgical tools for tissue identification during surgery. A key facet of this development is identifying distinct features that can be used to identify tissues from one another. This paper explores several feature extraction techniques and classification methods applied to electric impedance data. Furthermore, a modified forward stepwise method is proposed. The method introduces a scoring metric to help select features to add to the model, that is based off of the coefficient of variation and overlapping index from the feature's probability density functions for each of the classes. The proposed and existing methods were applied to spectral data measured at 23 frequencies, from 132 samples across 6 different tissues including ex-vivo bovine kidney, liver and muscle, poultry liver, as well as freshly excised canine testicle and ovary samples. These methods were able to successfully find impedance spectra features for the investigated biological tissues. The best predictive accuracy was with Boruta feature extraction and a Random Forest classifier but without significantly reducing the number of features in the classifier model. The proposed method was able to reduce the number of features in the model to an average of 5.8 features for all tested classifiers. These methods may have use in finding features to discriminate other tissue types, possibly to aid in targeting lesions in minimally invasive cancer treatment surgeries.

SmartProbe: a bioimpedance sensing system for head and neck cancer tissue detection

OBJECTIVES

This study presents SmartProbe, an electrical bioimpedance (EBI) sensing system based on a concentric needle electrode (CNE). The system allows the use of commercial CNEs for accurate EBI measurement, and was specially developed for in-vivo real-time cancer detection.

APPROACH

Considering the uncertainties in EBI measurements due to the CNE manufacturing tolerances, we propose a calibration method based on statistical learning. This is done by extracting the correlation between the measured impedance value |Z|, and the material conductivity σ, for a group of reference materials. By utilizing this correlation, the relationship of σ and |Z| can be described as a function and reconstructed using a single measurement on a reference material of known conductivity.

MAIN RESULTS

This method simplifies the calibration process, and is verified experimentally. Its effectiveness is demonstrate by results that show less than 6% relative error. An additional experiment is conducted for evaluating the system's capability to detect cancerous tissue. Four types of ex-vivo human tissue from the head and neck region, including mucosa, muscle, cartilage and salivary gland, are characterized using SmartProbe. The measurements include both cancer and surrounding healthy tissue excised from 10 different patients operated on for head and neck cancer. The measured data is then processed using dimension reduction and analyzed for tissue classification. The final results show significant differences between pathologic and healthy tissues in muscle, mucosa and cartilage specimens.

SIGNIFICANCE

These results are highly promising and indicate a great potential for SmartProbe to be used in various cancer detection tasks.

Design of a Drop-in EBI Sensor Probe for Abnormal Tissue Detection in Minimally Invasive Surgery

It is a common challenge for the surgeon to detect pathological tissues and determine the resection margin during a minimally invasive surgery. In this study, we present a drop-in sensor probe based on the electrical bioimpedance spectroscopic technology, which can be grasped by a laparoscopic forceps and controlled by the surgeon to inspect suspicious tissue area conveniently. The probe is designed with an optimized electrode and a suitable shape specifically for Minimally Invasive Surgery (MIS). Subsequently, a series of ex vivo experiments are carried out with porcine liver tissue for feasibility validation. During the experiments, impedance measured at frequencies from 1 kHz to 2 MHz are collected on both normal tissues and water soaked tissue. In addition, classifiers based on discriminant analysis are developed. The result of the experiment indicate that the sensor probe can be used to measure the impedance of the tissue easily and the developed tissue classifier achieved accuracy of 80% and 100% respectively.

Lock-in Amplifier-Based Impedance Detection of Tissue Type Using a Monopolar Injection Needle

For successful intra-articular injection therapy, it is essential to accurately position the tip of the injection needle into the target joint area while administering the drug into the affected tissue. In this study, we investigated the feasibility of a monopolar injection needle and lock-in amplifier (LIA)-based impedance measurement system for detecting the tissue type where the needle tip is located. After positioning the monopolar injection needle tip into the dermis, hypodermis, or muscle layer of pork tissue, the electrical impedance was measured in the frequency range of 10 Hz to 10 kHz. We observed a difference in the results based on the tissue type where the needle was positioned (p-value < 0.01). Therefore, the monopolar injection needle with electrical impedance measurement can be used to improve intra-articular injection therapy through non-destructive and real-time monitoring of the needle position in the tissues.

A New Venous Entry Detection Method Based on Electrical Bio-impedance Sensing

Peripheral intravenous catheterization (PIVC) is frequently required for various medical treatments. Over 1 billion PIVC operations are performed per year in the United States alone. However, this operation is characterized by a very low success rate, especially amongst pediatric patients. Statistics show that only 53% of first PIVC attempts are successful in pediatric patients. Since their veins are small and readily rupture, multiple attempts are commonly required before successfully inserting the catheter into the vein. This article presents and evaluates a novel venous entry detection method based on measuring the electrical bio-impedance of the contacting tissue at the tip of a concentric electrode needle (CEN). This detection method is then implemented in the design of a clinical device called smart venous entry indicator (SVEI), which lights up a LED to indicate the venous entry when the measured value is within the range of blood. To verify this detection method, two experiments are conducted. In the first experiment, we measured the bio-impedance during the insertion of a CEN into a rat's tail vein with different excitation frequencies. Then three classifiers are tested to discriminate blood from surrounding tissues. The experimental results indicate that with 100 kHz excitation frequency the blood bio-impedance can be identified with accuracy nearly 100%, demonstrating the feasibility and reliability of the proposed method for venous entry detection. The second experiment aims to assess the impact of SVEI on PIVC performance. Ten naive subjects were invited to catheterize a realistic baby arm phantom. The subjects are equally divided into two groups, where one group does PIVC with SVEI and the other group uses an ordinary IV catheter. The results show that subjects using SVEI can achieve much higher success rates (86%) than those performing PIVC in a conventional way (12%). Also, all subjects assisted by SVEI succeeded in their first trials while no one succeed in their first attempt using the conventional unassisted system. These results demonstrate the proposed detection method has great potential to improve pediatric PIVC performance, especially for non-expert clinicians. This supports further investment towards clinical validation of the technology.

Recording characteristics of electrical impedance myography needle electrodes

OBJECTIVE

Neurologists and physiatrists need improved tools for the evaluation of skeletal muscle condition. Here we evaluate needle electrical impedance myography (EIM), a new minimally invasive approach to determine muscle status that could ultimately become a bedside tool for the assessment of neuromuscular disorders.

APPROACH

We design and study the recording characteristics of tetrapolar EIM needle electrodes combining theory and finite-element model simulations. We then use these results to build and pilot in vivo an EIM needle electrode in the rat gastrocnemius muscle ([Formula: see text]). The dielectric properties of muscle are reported (mean  ±  standard deviation).

RESULTS

The numerical simulations show that the contribution of subcutaneous fat and muscle tissues to needle EIM data is <3% and >97%, respectively, and the sensed volume is [Formula: see text] cm³. Apparent resistivity [Formula: see text] [Formula: see text] cm and relative permittivity [Formula: see text] (dimensionless) measured at 10 kHz are in good agreement with in vivo dielectric properties reported in the literature.

SIGNIFICANCE

The results presented show the feasibility of measuring muscle impedivity in vivo using a needle electrode from 10 kHz to 1 MHz. The development of needle EIM technology can open up a new field of study in electrodiagnostic medicine, with potential applications to both disease diagnosis and biomarker assessment of therapy.

Measurement of subcutaneous adipose tissue thickness by near-infrared

Obesity is strongly associated with the risks of diabetes and cardiovascular disease, and there is a need to measure the subcutaneous adipose tissue (SAT) layer thickness and to understand the distribution of body fat. A device was designed to illuminate the body parts by near-infrared (NIR), measure the backscattered light, and predict the SAT layer thickness. The device was controlled by a single-chip microcontroller (SCM), and the thickness value was presented on a liquid crystal display (LCD). There were 30 subjects in this study, and the measurements were performed on 14 body parts for each subject. The paper investigated the impacts of pressure and skin colour on the measurement. Combining with principal component analysis (PCA) and support vector regression (SVR), the measurement accuracy of SAT layer thickness was 89.1 % with a mechanical caliper as reference. The measuring range was 5-11 mm. The study provides a non-invasive and low-cost technique to detect subcutaneous fat thickness, which is more accessible and affordable compared to other conventional techniques. The designed device can be used at home and in community.

A new measuring and identification approach for time-varying bioimpedance using multisine electrical impedance spectroscopy

The bioimpedance measurement/identification of time-varying biological systems Z(ω, t) by means of electrical impedance spectroscopy (EIS) is still a challenge today. This paper presents a novel measurement and identification approach, the so-called parametric-in-time approach, valid for time-varying (bio-)impedance systems with a (quasi) periodic character. The technique is based on multisine EIS. Contrary to the widely used nonparametric-in-time strategy, the (bio-)impedance Z(ω, t) is assumed to be time-variant during the measurement interval. Therefore, time-varying spectral analysis tools are required. This new parametric-in-time measuring/identification technique has experimentally been validated through three independent sets of in situ measurements of in vivo myocardial impedance. We show that the time-varying myocardial impedance Z(ω, t) is dominantly periodically time varying (PTV), denoted as ZPTV(ω, t). From the temporal analysis of ZPTV(ω, t), we demonstrate that it is possible to decompose ZPTV(ω, t) into a(n) (in)finite sum of fundamental (bio-)impedance spectra, the so-called harmonic impedance spectra (HIS) Zk(ω)s with [Formula: see text]. This is similar to the well-known Fourier series of a periodic signal, but now understood at the level of a periodic system's frequency response. The HIS Zk(ω)s for [Formula: see text] actually summarize in the bi-frequency (ω, k) domain all the temporal in-cycle information about the periodic changes of Z(ω, t). For the particular case k = 0 (i.e. on the ω-axis), Z0(ω) reflects the mean in-cycle behavior of the time-varying bioimpedance. Finally, the HIS Zk(ω)s are directly identified from noisy current and voltage myocardium measurements at the multisine measurement frequencies (i.e. nonparametric-in-frequency).