Dielectric Properties of Normal and Metastatic Lymph Nodes Ex Vivo From Lung Cancer Surgeries

Continuous-flow electrorotation (cROT): improved throughput characterization for dielectric properties of cancer cells

This paper presents the concept of a newly developed high-throughput measurement device for determining the dielectric properties of cancer cells. The proposed continuous-flow electrorotation (cROT) device can induce electrorotation (ROT) with vertical rotation using two sets of interdigitated electrodes on the top and bottom substrates to torque the cells. In the developed device, multiple rotating cells flowing in a microchannel are aligned between electrodes using dielectrophoresis. This allows for the measurement of the rotational behavior of the cells with continuous flow, resulting in a significant improvement in throughput compared to the conventional ROT devices reported previously. The dielectric properties, permittivity of the cell membrane and conductivity of the cell cytoplasm, of HeLa cells obtained by simultaneous measurements using the developed cROT device were 9.13 ± 1.02 and 0.93 ± 0.10 S m-1, respectively. Moreover, the measurement throughput was successfully increased to 2700 cells per h using the cROT technique.

Dielectric Spectroscopy Shows a Permittivity Contrast between Meningioma Tissue and Brain White and Gray Matter-A Potential Physical Biomarker for Meningioma Discrimination

The effectiveness of surgical resection of meningioma, the most common primary CNS tumor, depends on the capability to intraoperatively discriminate between the meningioma tissue and the surrounding brain white and gray matter tissues. Aiming to find a potential biomarker based on tissue permittivity, dielectric spectroscopy of meningioma, white matter, and gray matter ex vivo tissues was performed using the open-ended coaxial probe method in the microwave frequency range from 0.5 to 18 GHz. The averages and the 95% confidence intervals of the measured permittivity for each tissue were compared. The results showed the absence of overlap between the 95% confidence intervals for meningioma tissue and for brain white and gray matter, indicating a significant difference in average permittivity (p ≤ 0.05) throughout almost the entire measured frequency range, with the most pronounced contrast found between 2 GHz and 5 GHz. The discovered contrast is relevant as a potential physical biomarker to discriminate meningioma tissue from the surrounding brain tissues by means of permittivity measurement, e.g., for intraoperative meningioma margin assessment. The permittivity models for each tissue, developed in this study as its byproducts, will allow more accurate electromagnetic modeling of brain tumor and healthy tissues, facilitating the development of new microwave-based medical devices and tools.

Sensitivity investigation of open-ended coaxial probe in skin cancer detection

Open-ended coaxial probe method is one of the most common modalities in measuring dielectric properties (DPs) of biological tissues. Due to the significant differences between the tumors and normal tissues in DPs, the technique can be used to detect skin cancer in the early stage. Although various studies have been reported, systematic assessment is in urgent need to advance it to clinical applications, for its parameters interactions and detecting limitations remained unclear. In this study, we aim to provide a comprehensive examination of this method, including the minimum detectable tumor size by using a three-layer skin model via simulation and demonstrated that open-ended coaxial probe method can be used for detection of early-stage skin cancer. The smallest detecting size are subject to different subtypes: for BCC, inside the skin is 0.5 mm radius × 0.1 mm height; for SCC, inside the skin is 1.4 mm × 1.3 mm in radius and height; the smallest distinguishing size of BCC is 0.6 mm × 0.7 mm in radius and height; for SCC is 1.0 mm × 1.0 mm in radius and height; for MM is 0.7 mm × 0.4 mm in radius and height. The experiment results showed that sensitivity was affected by tumor dimension, probe size, skin height, and cancer subtype. The probe is more sensitive to cylinder tumor radius than height growing on the surface of the skin while the smallest size probe is the most sensitive among the working probes. We provide a detailed systematic evaluation of the parameters employed in the method for further applications.

Simulations of surface charge density changes during the untreated solid tumour growth

Understanding untreated tumour growth kinetics and its intrinsic behaviour is interesting and intriguing. The aim of this study is to propose an approximate analytical expression that allows us to simulate changes in surface charge density at the cancer-surrounding healthy tissue interface during the untreated solid tumour growth. For this, the Gompertz and Poisson equations are used. Simulations reveal that the unperturbed solid tumour growth is closely related to changes in the surface charge density over time between the tumour and the surrounding healthy tissue. Furthermore, the unperturbed solid tumour growth is governed by temporal changes in this surface charge density. It is concluded that results corroborate the correspondence between the electrical and physiological parameters in the untreated cancer, which may have an essential role in its growth, progression, metastasis and protection against immune system attack and anti-cancer therapies. In addition, the knowledge of surface charge density changes at the cancer-surrounding healthy tissue interface may be relevant when redesigning the molecules in chemotherapy and immunotherapy taking into account their polarities. This can also be true in the design of completely novel therapies.

Measurement and image-based estimation of dielectric properties of biological tissues —past, present, and future—

The dielectric properties of biological tissues are fundamental pararmeters that are essential for electromagnetic modeling of the human body. The primary database of dielectric properties compiled in 1996 on the basis of dielectric measurements at frequencies from 10 Hz to 20 GHz has attracted considerable attention in the research field of human protection from non-ionizing radiation. This review summarizes findings on the dielectric properties of biological tissues at frequencies up to 1 THz since the database was developed. Although the 1996 database covered general (normal) tissues, this review also covers malignant tissues that are of interest in the research field of medical applications. An intercomparison of dielectric properties based on reported data is presented for several tissue types. Dielectric properties derived from image-based estimation techniques developed as a result of recent advances in dielectric measurement are also included. Finally, research essential for future advances in human body modeling is discussed.

Water Dynamics in Cancer Cells: Lessons from Quasielastic Neutron Scattering

The severity of the cancer statistics around the globe and the complexity involving the behavior of cancer cells inevitably calls for contributions from multidisciplinary areas of research. As such, materials science became a powerful asset to support biological research in comprehending the macro and microscopic behavior of cancer cells and untangling factors that may contribute to their progression or remission. The contributions of cellular water dynamics in this process have always been debated and, in recent years, experimental works performed with Quasielastic neutron scattering (QENS) brought new perspectives to these discussions. In this review, we address these works and highlight the value of QENS in comprehending the role played by water molecules in tumor cells and their response to external agents, particularly chemotherapy drugs. In addition, this paper provides an overview of QENS intended for scientists with different backgrounds and comments on the possibilities to be explored with the next-generation spectrometers under construction.

Displacement Patterns in Magnetomotive Ultrasound Explored by Finite Element Analysis

Magnetomotive ultrasound is an emerging technique that enables detection of magnetic nanoparticles. This has implications for ultrasound molecular imaging, and potentially addresses clinical needs regarding determination of metastatic infiltration of the lymphatic system. Contrast is achieved by a time-varying magnetic field that sets nanoparticle-laden regions in motion. This motion is governed by vector-valued mechanical and magnetic forces. Understanding how these forces contribute to observed displacement patterns is important for the interpretation of magnetomotive ultrasound images. Previous studies have captured motion adjacent to nanoparticle-laden regions that was attributed to diamagnetism. While diamagnetism could give rise to a force, it cannot fully account for the observed displacements in magnetomotive ultrasound. To isolate explanatory variables of the observed displacements, a finite element model is set up. Using this model, we explore potential causes of the unexplained motion by comparing numerical models with earlier experimental findings. The simulations reveal motion outside particle-laden regions that could be attributed to mechanical coupling and the principle of mass conservation. These factors produced a motion that counterbalanced the time-varying magnetic excitation, and whose extent and distribution was affected by boundary conditions as well as compressibility and stiffness of the surroundings. Our findings emphasize the importance of accounting for the vector-valued magnetic force in magnetomotive ultrasound imaging. In an axisymmetric geometry, that force can be represented by a simple scalar expression, an oversimplification that rapidly becomes inaccurate with distance from the symmetry axis. Additionally, it results in an underestimation of the vertical force component by up to 30%. We therefore recommend using the full vector-valued force to capture the magnetic interaction. This study enhances our understanding of how forces govern magnetic nanoparticle displacement in tissue, contributing to accurate analysis and interpretation of magnetomotive ultrasound imaging.

[Comparison of dielectric properties of normal human esophagus and esophageal cancer using an open-ended coaxial probe]

OBJECTIVE

To study the difference in dielectric properties (relative permittivity and electrical conductivity) between normal human esophageal tissues and esophageal cancer tissues resected in esophageal cancer surgery for rapid identification of esophageal cancer during surgery.

METHODS

An open- end coaxial probe in the frequency range of 50 MHz to 4 GHz was used for dielectric measurement of the normal tissues and tumor tissues immediately after resection in 51 esophageal cancer cases. The difference in dielectric characteristics of the tissues was analyzed in the full frequency range, and the measurement data at 6 specific frequencies (64, 128, 298, 433, 915, and 2450 MHz) were analyzed statistically. The Cole-Cole model was used for data fitting in the entire frequency band and the measured values were compared with reported values.

RESULTS

In the frequency range of 50 MHz- 4 GHz, the dielectric measurement values of esophageal cancer tissues were significantly higher than those of normal esophageal tissues. At the 6 specific frequencies, the dielectric properties also differed significantly between normal esophageal tissues and esophageal cancer tissues (P < 0.01). The Cole-Cole model achieved a good fitting result of the measured data. The measured values in this study were lower than the reported values.

CONCLUSION

There are significant differences in the dielectric properties between normal esophageal tissue and tumor tissue, which may provide a new theoretical basis for rapid identification of esophageal cancer during surgery.

Development of MRI-based axillary numerical models and estimation of axillary lymph node dielectric properties for microwave imaging

PURPOSE

Microwave imaging (MWI) has been studied as a complementary imaging modality to improve sensitivity and specificity of diagnosis of axillary lymph nodes (ALNs), which can be metastasized by breast cancer. The feasibility of such a system is based on the dielectric contrast between healthy and metastasized ALNs. However, reliable information such as anatomically realistic numerical models and matching dielectric properties of the axillary region and ALNs, which are crucial to develop MWI systems, are still limited in the literature. The purpose of this work is to develop a methodology to infer dielectric properties of structures from magnetic resonance imaging (MRI), in particular, ALNs. We further use this methodology, which is tailored for structures farther away from MR coils, to create MRI-based numerical models of the axillary region and share them with the scientific community, through an open-access repository.

METHODS

We use a dataset of breast MRI scans of 40 patients, 15 of them with metastasized ALNs. We apply image processing techniques to minimize the artifacts in MR images and segment the tissues of interest. The background, lung cavity, and skin are segmented using thresholding techniques and the remaining tissues are segmented using a K-means clustering algorithm. The ALNs are segmented combining the clustering results of two MRI sequences. The performance of this methodology was evaluated using qualitative criteria. We then apply a piecewise linear interpolation between voxel signal intensities and known dielectric properties, which allow us to create dielectric property maps within an MRI and consequently infer ALN properties. Finally, we compare healthy and metastasized ALN dielectric properties within and between patients, and we create an open-access repository of numerical axillary region numerical models which can be used for electromagnetic simulations.

RESULTS

The proposed methodology allowed creating anatomically realistic models of the axillary region, segmenting 80 ALNs and analyzing the corresponding dielectric properties. The estimated relative permittivity of those ALNs ranged from 16.6 to 49.3 at 5 GHz. We observe there is a high variability of dielectric properties of ALNs, which can be mainly related to the ALN size and, consequently, its composition. We verified an average dielectric contrast of 29% between healthy and metastasized ALNs. Our repository comprises 10 numerical models of the axillary region, from five patients, with variable number of metastasized ALNs and body mass index.

CONCLUSIONS

The observed contrast between healthy and metastasized ALNs is a good indicator for the feasibility of a MWI system aiming to diagnose ALNs. This paper presents new contributions regarding anatomical modeling and dielectric properties' characterization, in particular for axillary region applications.

Microwave ablation of lung tumors: A probabilistic approach for simulation-based treatment planning

PURPOSE

Microwave ablation (MWA) is a clinically established modality for treatment of lung tumors. A challenge with existing application of MWA, however, is local tumor progression, potentially due to failure to establish an adequate treatment margin. This study presents a robust simulation-based treatment planning methodology to assist operators in comparatively assessing thermal profiles and likelihood of achieving a specified minimum margin as a function of candidate applied energy parameters.

METHODS

We employed a biophysical simulation-based probabilistic treatment planning methodology to evaluate the likelihood of achieving a specified minimum margin for candidate treatment parameters (i.e., applied power and ablation duration for a given applicator position within a tumor). A set of simulations with varying tissue properties was evaluated for each considered combination of power and ablation duration, and for four different scenarios of contrast in tissue biophysical properties between tumor and normal lung. A treatment planning graph was then assembled, where distributions of achieved minimum ablation zone margins and collateral damage volumes can be assessed for candidate applied power and treatment duration combinations. For each chosen power and time combination, the operator can also visualize the histogram of ablation zone boundaries overlaid on the tumor and target volumes. We assembled treatment planning graphs for generic 1, 2, and 2.5 cm diameter spherically shaped tumors and also illustrated the impact of tissue heterogeneity on delivered treatment plans and resulting ablation histograms. Finally, we illustrated the treatment planning methodology on two example patient-specific cases of tumors with irregular shapes.

RESULTS

The assembled treatment planning graphs indicate that 30 W, 6 min ablations achieve a 5-mm minimum margin across all simulated cases for 1-cm diameter spherical tumors, and 70 W, 10 min ablations achieve a 3-mm minimum margin across 90% of simulations for a 2.5-cm diameter spherical tumor. Different scenarios of tissue heterogeneity between tumor and lung tissue revealed 2 min overall difference in ablation duration, in order to reliably achieve a 4-mm minimum margin or larger each time for 2-cm diameter spherical tumor.

CONCLUSIONS

An approach for simulation-based treatment planning for microwave ablation of lung tumors is illustrated to account for the impact of specific geometry of the treatment site, tissue property uncertainty, and heterogeneity between the tumor and normal lung.

Classification of Metastatic and Non-Metastatic Thoracic Lymph Nodes in Lung Cancer Patients Based on Dielectric Properties Using Adaptive Probabilistic Neural Networks

Objective

Dielectric properties can be used in normal and malignant tissue identification, which requires an effective classifier because of the high throughput nature of the data. With easy training and fast convergence, probabilistic neural networks (PNNs) are widely applied in pattern classification problems. This study aims to propose a classifier to identify metastatic and non-metastatic thoracic lymph nodes in lung cancer patients based on dielectric properties.

Methods

The dielectric properties (permittivity and conductivity) of lymph nodes were measured using an open-ended coaxial probe. The Synthetic Minority Oversampling Technique method was adopted to modify the dataset. Feature parameters were scored to select the appropriate feature vector using a Statistical Dependency algorithm. The dataset was classified using adaptive PNNs with an optimized smooth factor using the simulated annealing PNN (SA-PNN). The results were compared with traditional Probabilistic, Support Vector Machines, k-Nearest Neighbor and the Classify functions in MATLAB.

Results

The conductivity frequencies of 3959, 3958, 3960, 3978, 3510, 3889, 3888, and 3976 MHz were selected as the feature vectors for 219 lymph nodes (178 non-metastatic and 41 metastatic). Compared with the other methods, SA-PNN achieved the highest classification accuracy (92.92%) and the corresponding specificity and sensitivity were 94.72% and 91.11%, respectively.

Conclusions

Compared with the other methods, the SA-PNN proposed in the present study achieved a higher classification accuracy, which provides a new scheme for classification of metastatic and non-metastatic thoracic lymph nodes in lung cancer patients based on dielectric properties.

Differences in the dielectric properties of various benign and malignant thyroid nodules

PURPOSE

This experiment was conducted to investigate the dielectric properties of different types of thyroid nodules. Our goal was to find a simple and fast method to detect thyroid diseases at different stages from the dielectric properties of thyroid nodules.

METHODS

We used the open-ended coaxial line method to measure the dielectric permittivities of thyroid tissues from 155 patients at frequencies ranging from 1 to 4000 MHz. Tissues that were investigated included normal thyroid tissue and benign and malignant thyroid nodules (nodular goiter, follicular adenoma, papillary carcinoma, and follicular carcinoma), as determined from pathological reports. Differences in dielectric properties were measured between each nodule and the surrounding 1 cm of tissue.

RESULTS

The analysis results revealed that the dielectric permittivity and conductivity values were positively correlated with the degree of malignancy of the nodule (normal < benign < malignant; all differences P < 0.05). This was more obvious at frequencies within 20~70 MHz, following the order normal tissue < nodular goiter < follicular adenoma < papillary carcinoma < follicular carcinoma. A significant difference (P < 0.05) in dielectric permittivity and conductivity was found when comparing these nodules with the surrounding 1 cm of tissue.

CONCLUSIONS

Normal, benign, and malignant nodules were successfully distinguished from one another, and dielectric permittivity was found to be a more sensitive parameter than conductivity. In particular, different disease types can be distinguished at a stimulation frequency of 20~70 MHz, which shows that dielectric properties have application prospects for the detection and diagnosis of cancer. At the same time, the dielectric parameter differences between the surrounding 1 cm of tissue and the diseased nodule can distinguish the tumor and its surrounding tissues in real time during surgery to determine the tumor boundary.

[Sensing volume of tissue dielectric property measurement with open-ended coaxial probe]

OBJECTIVE

To investigate the sensing volume of open-ended coaxial probe technique for measurement of dielectric characteristics.

METHODS

A measurement model combining macro- measurement device with a layer model of dielectric properties parameters was established for evaluating the sensing volume of open-ended coaxial probe technique. We defined sensing depth and sensing diameter to describe the distance that could be detected in vertical and horizontal direction. Using a variety of materials with different dielectric properties (Teflon, deionized water, ethanol, and gradient concentration sodium chloride solution), a layered model of dielectric properties differentiation was established. The total combined uncertainties (TCU) were calculated for different output power, and the output power was controlled to increase from -50 dBm to 15 dBm to calibrate the error range of the dielectric properties measurement system. The optimal output power range was determined based on the results of TCU test. In sensing volume measurement experiment, we set the control groups based on measurement parameters that potentially affect the sensing volume including output power (-10, -5, 0, 3, 6, and 9 dBm), frequency (1-500 MHz), Teflon, deionized water, and ethanol to form a dielectric constant difference between high and low contrast groups. Different concentrations of sodium chloride solution and Teflon were used to generate a conductivity difference between high and low contrast groups. These groups were tested in the sensing depth and sensing diameter measurement experiments.

RESULTS

The result of TCU test indicated that accurate and stable measurement results could be obtained when the output power was greater or equal to-10 dBm (TCU &lt; 2%). Sensing volume measurement experiment revealed a positive correlation between the sensing depth and output power (P &lt; 0.05). As the measured power increased, the sensing depth gradually increased in deionized water and ethanol, and the difference reached 70 μm. The sensing depth was negatively correlated frequency (P &lt; 0.05). As the concentration of sodium chloride solution increased, the corresponding sensing depth gradually decreased, with a difference reaching 270 μm. The sensing depth of high dielectric materials was greater than that pf low dielectric materials. The results of sensing diameter measurement were not obviously affected by the measurement parameters, and the sensing diameter was stable in a fixed range (1.0 to 1.8 mm) between the diameter of the inner conductor and the diameter of the insulation layer, and was less than the diameter of the probe.

CONCLUSIONS

The sensing volume of open-ended coaxial probe technique is affected by measurement parameters and dielectric properties of materials, which significantly affect the sensing depth.