Extracellular Total Electrolyte Concentration Imaging for Electrical Brain Stimulation (EBS)

Validation of conductivity tensor imaging against diffusion tensor magnetic resonance electrical impedance tomography

Diffusion tensor magnetic resonance electrical impedance tomography (DT-MREIT) and electrodeless conductivity tensor imaging (CTI) are two emerging modalities that can quantify low-frequency tissue anisotropic conductivity properties by assuming similar properties underlie ionic mobility and water diffusion. While both methods have potential applications to estimating neuro-modulation fields or formulating forward models used for electrical source imaging, a direct comparison of the two modalities has not yet been performed in-vitro or in-vivo. Therefore, the aim of this study was to test the equivalence of these two modalities. We scanned a tissue phantom and the head of human subject using DT-MREIT and CTI protocols and reconstructed conductivity tensor and effective low frequency conductivities. We found both gray and white matter conductivities recovered by each technique were equivalent within 0.05 S/m. Both DT-MREIT and CTI require multiple processing steps, and we further assess the effects of each factor on reconstructions and evaluate the extent to which different measurement mechanisms potentially cause discrepancies between the two methods. Finally, we discuss the implications for spectral models of measuring conductivity using these techniques. The study further establishes the credibility of CTI as an electrodeless non-invasive method of measuring low frequency conductivity properties.

Ion-modulated interfacial fluorescence in droplet microfluidics using an ionophore-doped oil

Fluorescence at the oil-water interface is used for chemical sensing in droplet microfluidics. Potassium ions in aqueous droplets are extracted into oil segments doped with an ionophore, a cation exchanger, and a cationic dye to expel the dye. When a low concentration of dye with a balanced solubility is used, it actively accumulates at the thin interface between oil and water instead of getting dissolved in the aqueous phase. The interfacial fluorescence is monitored distinct from the fluorescence in the oil sensor and the aqueous sample, allowing for highly sensitive and selective turn-on fluorescence sensing of ions.

Magnetic Resonance Electrical Impedance Tomography

Magnetic Resonance Electrical Impedance Tomography (MREIT) is a high-resolution bioimpedance imaging technique that has developed over a period beginning in the early 1990s to measure low-frequency (<1 kHz) tissue electrical properties. Low-frequency electrical properties are particularly important because they provide valuable information on cell structures and ionic composition of tissues, which may be very useful for diagnostic purposes. MREIT uses one component of the magnetic flux density data induced due to an exogenous-current administration, measured using an MRI machine, to reconstruct isotropic or anisotropic electrical property distributions. The MREIT technique typically requires two linearly independent current administrations to reconstruct conductivity uniquely. Since its invention, researchers have explored its potential for measuring electrical conductivity in regions such as the brain and muscle tissue. It has also been investigated in disease models, for example, cerebral ischemia and early tumor detection. In this chapter, we aim to provide a solid foundation of the different MREIT image reconstruction algorithms, including both isotropic and anisotropic conductivity reconstruction approaches. We will also explore the newly developed diffusion tensor magnetic resonance electrical impedance tomography (DT-MREIT) method, a practical method for anisotropic tissue property imaging, at the end of the chapter.

Magnetic-resonance-based measurement of electromagnetic fields and conductivity in vivo using single current administration-A machine learning approach

Diffusion tensor magnetic resonance electrical impedance tomography (DT-MREIT) is a newly developed technique that combines MR-based measurements of magnetic flux density with diffusion tensor MRI (DT-MRI) data to reconstruct electrical conductivity tensor distributions. DT-MREIT techniques normally require injection of two independent current patterns for unique reconstruction of conductivity characteristics. In this paper, we demonstrate an algorithm that can be used to reconstruct the position dependent scale factor relating conductivity and diffusion tensors, using flux density data measured from only one current injection. We demonstrate how these images can also be used to reconstruct electric field and current density distributions. Reconstructions were performed using a mimetic algorithm and simulations of magnetic flux density from complementary electrode montages, combined with a small-scale machine learning approach. In a biological tissue phantom, we found that the method reduced relative errors between single-current and two-current DT-MREIT results to around 10%. For in vivo human experimental data the error was about 15%. These results suggest that incorporation of machine learning may make it easier to recover electrical conductivity tensors and electric field images during neuromodulation therapy without the need for multiple current administrations.

Lorentz force induced shear waves for magnetic resonance elastography applications

Quantitative mechanical properties of biological tissues can be mapped using the shear wave elastography technique. This technology has demonstrated a great potential in various organs but shows a limit due to wave attenuation in biological tissues. An option to overcome the inherent loss in shear wave magnitude along the propagation pathway may be to stimulate tissues closer to regions of interest using alternative motion generation techniques. The present study investigated the feasibility of generating shear waves by applying a Lorentz force directly to tissue mimicking samples for magnetic resonance elastography applications. This was done by combining an electrical current with the strong magnetic field of a clinical MRI scanner. The Local Frequency Estimation method was used to assess the real value of the shear modulus of tested phantoms from Lorentz force induced motion. Finite elements modeling of reported experiments showed a consistent behavior but featured wavelengths larger than measured ones. Results suggest the feasibility of a magnetic resonance elastography technique based on the Lorentz force to produce an shear wave source.

Visualization of microwave near-field distribution in sodium chloride and glucose aqueous solutions by a thermo-elastic optical indicator microscope

In this study, a new optical method is presented to determine the concentrations of NaCl and glucose aqueous solutions by using a thermo-elastic optical indicator microscope. By measuring the microwave near-field distribution intensity, concentration changes of NaCl and glucose aqueous solutions were detected in the 0-100 mg/ml range, when exposed to microwave irradiation at 12 GHz frequency. Microwave near-field distribution intensity decreased as the NaCl or glucose concentration increased due to the changes of the absorption properties of aqueous solution. This method provides a novel approach for monitoring NaCl and glucose in biological liquids by using a CCD sensor capable of visualizing NaCl and glucose concentrations without scanning.

In Vivo Measurement of Brain Tissue Response After Irradiation: Comparison of T2 Relaxation, Apparent Diffusion Coefficient, and Electrical Conductivity

Radiation therapy (RT) has been widely used as a powerful treatment tool to address cancerous tissues because of its ability to control cell growth. Its ionizing radiation damages the DNA of cancerous tissues, leading to cell death. Medical imaging, however, still has limitations regarding the reliability of its assessment of tissue response and in predicting the treatment effect because of its inability to provide contrast information on the gradual, minute tissue changes after RT. A recently developed magnetic resonance (MR)-based conductivity imaging method may provide direct, highly sensitive information on this tissue response because its contrast mechanism is based on the concentration and mobility of ions in intracellular and extracellular spaces. In this feasibility study, we applied T2-weighted, diffusion-weighted, and electrical conductivity imaging to mouse brain, thus, using the MR imaging to map the tissue response after radiation exposure. To evaluate the degree of response, we measured the T2 relaxation, apparent diffusion coefficient (ADC), and electrical conductivity of brain tissues before and after irradiation. The conductivity images, which showed significantly higher sensitivity than other MR imaging methods, indicated that the contrast is distinguishable in different ways at different areas of the brain. Future studies will focus on verifying these results and the long-term evaluation of conductivity changes using various irradiation methods for clinical applications.

Electrical Characterization of Pork Tissue Measured by a Monopolar Injection Needle and Discrete Fourier Transform based Impedance Measurement

Ultrasonography or fluoroscopy-guided needle injection has been used for intra-articular injection therapy against adhesive capsulitis and joint diseases. To improve the image-guided intra-articular injection therapy, electrical impedance measurement based positioning of the needle tip in the target tissue can be applied. The feasibility of the discrimination for the tissue layer at which the disposable monopolar injection needle tip position was investigated using the discrete Fourier transform (DFT)-based impedance measurement system and the ultrasound imaging device. The electrical impedance spectra of the pork tissue measured in the frequency range of 200 Hz to 50 kHz were characterized by designed equivalent circuit modeling analysis. The normalized impedance data of the tissue layers (dermis, hypodermis, and muscle) were significantly different from each other (p-value < 0.001). The DFT-based impedance measurement system with a monopolar injection needle can be complementary to the image-guided intra-articular injection therapy.

Conductivity Tensor Imaging of In Vivo Human Brain and Experimental Validation Using Giant Vesicle Suspension

Human brain mapping of low-frequency electrical conductivity tensors can realize patient-specific volume conductor models for neuroimaging and electrical stimulation. We report experimental validation and in vivo human experiments of a new electrodeless conductivity tensor imaging (CTI) method. From CTI imaging of a giant vesicle suspension using a 9.4-T MRI scanner, the relative error in the reconstructed conductivity tensor image was found to be less than 1.7% compared with the measured value using an impedance analyzer. In vivo human brain imaging experiments of five subjects were followed using a 3-T clinical MRI scanner. With the spatial resolution of 1.87 mm, the white matter conductivity showed considerably more position dependency compared with the gray matter and cerebrospinal fluid (CSF). The anisotropy ratio of the white matter was in the range of 1.96-3.25 with a mean value of 2.43, whereas that of the gray matter was in the range of 1.12-1.19 with a mean value of 1.16. The three diagonal components of the reconstructed conductivity tensors were from 0.08 to 0.27 S/m for the white matter, from 0.20 to 0.30 S/m for the gray matter, and from 1.55 to 1.82 S/m for the CSF. The reconstructed conductivity tensor images exhibited significant inter-subject variabilities in terms of frequency and position dependencies. The high-frequency and low-frequency conductivity values can quantify the total and extracellular water contents, respectively, at every pixel. Their difference can quantify the intracellular water content at every pixel. The CTI method can separately quantify the contributions of ion concentrations and mobility to the conductivity tensor.

Hypoxia and the Tumor Secretome

Metastasis remains the leading cause of cancer-related deaths. To date, there are no specific treatments targeting disseminated disease. New therapeutic options will become available only if we enhance our understanding of mechanisms underlying metastatic spread. A large body of literature shows that the metastatic potential of tumor cells is strongly influenced by microenvironmental cues such as low oxygen (hypoxia). Clinically, hypoxia is a hallmark of most solid tumors and is associated with increased metastasis and poor survival in a variety of cancer types. Mechanistically, hypoxia influences multiple steps within the metastatic cascade and particularly impacts the interactions between tumor cells and host stroma at both primary and secondary sites. Here we review current evidence for a hypoxia-induced tumor secretome and its impact on metastatic progression. These studies have identified potential biomarkers and therapeutic targets that could be integrated into strategies for preventing and treating metastatic disease.