A THREE-PHASE INDUCTIVE SENSOR FOR IN VIVO MEASUREMENT OF ELECTRICAL ANISOTROPY OF BIOLOGICAL TISSUES

Biological tissue will have anisotropy in electrical conductivity, due to the orientation of muscular fibers or neural axons as well as the distribution of large size blood vessels. Thus, the in vivo measurement of electrical conductivity anisotropy can be used to detect deep-seated vessels in large organs such as the liver during surgeries. For diagnostic applications, decrease of anisotropy may indicate the existence of cancer in anisotropic tissues such as the white matter of the brain or the mammary gland in the breast. In this paper, we will introduce a new tri-phase induction method to drive rotating high-frequency electrical current in the tissue for the measurement of electrical conductivity anisotropy. In the measurement, three electromagnets are symmetrically placed on the tissue surface and driven by high-frequency alternative currents of 0 kHz, modulated with 1 kHz 3-phase signals. In the center area of three magnets, magnetic fields are superimposed to produce a rotating induction current. This current produces electrical potentials among circularly arranged electrodes to be used to find the conductivity in each direction determined by the electrode pairs. To find the horizontal and vertical signal components, the measured potentials are amplified by a 2ch lock-in amplifier phase-locked with the 1 kHz reference signal. The superimposed current in the tissue was typically 45 micro Amperes when we applied 150 micro Tesla of magnetic field. We showed the validity of our method by conducting in vitro measurements with respect to artificially formed anisotropic materials and preliminary in vivo measurements on the pig’s liver. Compared to diffusion tensor MRI method, our anisotropy sensor is compact and advantageous for use during surgical operations because our method does not require strong magnetic field that may disturb ongoing surgical operations.

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Machine learning estimation of tissue optical properties

Scientific Reports ◽

10.1038/s41598-021-85994-w ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Brett H. Hokr ◽

Joel N. Bixler

Keyword(s):

Neural Network ◽

Optical Properties ◽

Biological Tissues ◽

Homogeneous Layer ◽

In Vivo Measurement ◽

Tissue Optical Properties ◽

The Neural Network ◽

Spatio Temporal ◽

Fully Connected

AbstractDynamic, in vivo measurement of the optical properties of biological tissues is still an elusive and critically important problem. Here we develop a technique for inverting a Monte Carlo simulation to extract tissue optical properties from the statistical moments of the spatio-temporal response of the tissue by training a 5-layer fully connected neural network. We demonstrate the accuracy of the method across a very wide parameter space on a single homogeneous layer tissue model and demonstrate that the method is insensitive to parameter selection of the neural network model itself. Finally, we propose an experimental setup capable of measuring the required information in real time in an in vivo environment and demonstrate proof-of-concept level experimental results.

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Measurement of the Optical Properties of Muscle Tissue In Vivo

10.1115/imece2000-2214 ◽

2000 ◽

Author(s):

P. L. Kopsombut ◽

D. Willis ◽

A. E. Schen ◽

L. X. Xu ◽

X. Xu

Keyword(s):

Optical Properties ◽

Transport Theory ◽

Rapid Development ◽

Ccd Camera ◽

High Sensitivity ◽

Biological Tissues ◽

In Vivo Measurement ◽

Living Tissues

Abstract Along with rapid development of diagnostic and therapeutic applications of lasers in medicine, optical properties of various biological tissues have been extensively studied [1]. Most of the studies were performed in vitro owing to the complexity involved in in vivo measurement. To date, it is well understood that living tissue is an absorbing and scattering heterogeneous medium because of its complex structures including blood network. The transport theory cannot be readily used due to the heterogeneity and the absence of the optical properties of living tissues [2]. In this research, we have developed a procedure for measuring the total attenuation coefficient (μ1) of the exteriorized rat 2-D spinotrapezius muscle in the wavelength ranged from 480–560 nm using the collimated light from a Nitrogen-pumped dye laser and a high-sensitivity CCD camera.

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Comparative analysis of indentation and magnetic resonance elastography for measuring viscoelastic properties

Acta Mechanica Sinica ◽

10.1007/s10409-020-01042-2 ◽

2021 ◽

Author(s):

Yu Chen ◽

Suhao Qiu ◽

Zhao He ◽

Fuhua Yan ◽

Ruokun Li ◽

...

Keyword(s):

Magnetic Resonance ◽

Viscoelastic Properties ◽

Soft Tissues ◽

Biological Tissues ◽

Magnetic Resonance Elastography ◽

Small Samples ◽

Model Parameters ◽

In Vivo Measurement ◽

Pathological Behavior

Abstract Measurement the viscoelastic properties is important for studying the developmental and pathological behavior of soft biological tissues. Magnetic resonance elastography (MRE) is a non-invasive method for in vivo measurement of tissue viscoelasticity. As a flexible method capable of testing small samples, indentation has been widely used for characterizing soft tissues. Using 2nd-order Prony series and dimensional analysis, we analyzed and compared the model parameters estimated from both indentation and MRE. Conversions of the model parameters estimated from the two methods were established. We found that the indention test is better at capturing the dynamic response of tissues at a frequency less than 10 Hz, while MRE is better for describing the frequency responses at a relatively higher range. The results provided helpful information for testing soft tissues using indentation and MRE. The models analyzed are also helpful for quantifying the frequency response of viscoelastic tissues. Graphic Abstract

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G110 In Vivo Measurement of Thermal Conductivity and Thermal Diffusivity of Biological Tissues

Proceedings of thermal engineering conference ◽

10.1299/jsmeptec.2001.0_281 ◽

2001 ◽

Vol 2001 (0) ◽

pp. 281-282

Author(s):

Xing ZHANG ◽

Ryousuke TOBETA ◽

Motoo FUJII ◽

Horoshi TAKAMATSU

Keyword(s):

Thermal Conductivity ◽

Thermal Diffusivity ◽

Biological Tissues ◽

In Vivo Measurement

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Decomposition of High-Frequency Electrical Conductivity into Extracellular and Intracellular Compartments based on Two-Compartment Model using Low-to-High Multi-b Diffusion MRI

10.21203/rs.3.rs-117848/v1 ◽

2020 ◽

Author(s):

Mun Bae Lee ◽

Hyung Joong Kim ◽

Oh-In Kwon

Keyword(s):

Electrical Conductivity ◽

Electrical Properties ◽

High Frequency ◽

Compartment Model ◽

Biological Tissues ◽

Extracellular Medium ◽

Two Compartment Model ◽

Random Decision Forests ◽

Human Experiments ◽

Micro Structures

Abstract Background: As an object's electrical passive property, the electrical conductivity is proportional to the mobility and concentration of charged carriers that reflect the brain micro-structures. The measured Mb-DWI data by controlling the degree of applied diffusion weights can quantify the apparent mobility of water molecules within biological tissues. Without any external electrical stimulation, magnetic resonance electrical properties tomography (MREPT) techniques have successfully recovered the conductivity distribution at a Larmor-frequency. Methods: This work provides a non-invasive method to decompose the high-frequency conductivity into the extracellular medium conductivity based on a two-compartment model using multi-b diffusion-weighted imaging (Mb-DWI). To separate the intra- and extracellular micro-structures from the recovered high-frequency conductivity, we include higher b-values DWI and apply the random decision forests to stably determine the micro-structural diffusion parameters. Results: To demonstrate the proposed method, we conducted human experiments by comparing the results of reconstructed conductivity of extracellular medium and the conductivity in the intra-neurite and intra-cell body. Human experiments verify that the proposed method can recover the extracellular electrical properties from the high-frequency conductivity using a routine protocol sequence of MRI scan. Conclusion: We have proposed a method to decompose the electrical properties in the extracellular, intra-neurite, and soma compartments from the high-frequency conductivity map, reconstructed by solving the electro-magnetic equation with measured B1 phase signals.

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Development of a portable setup suitable for in vivo measurement of the dielectric properties of biological tissues

2017 11th European Conference on Antennas and Propagation (EUCAP) ◽

10.23919/eucap.2017.7928435 ◽

2017 ◽

Author(s):

L. Farina ◽

G. Ruvio ◽

R. Pinto ◽

L. Vannucci ◽

M. Cavagnaro ◽

...

Keyword(s):

Dielectric Properties ◽

Biological Tissues ◽

In Vivo Measurement

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Decomposition of high-frequency electrical conductivity into extracellular and intracellular compartments based on two-compartment model using low-to-high multi-b diffusion MRI

BioMedical Engineering OnLine ◽

10.1186/s12938-021-00869-5 ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Mun Bae Lee ◽

Hyung Joong Kim ◽

Oh In Kwon

Keyword(s):

Electrical Conductivity ◽

Electrical Properties ◽

High Frequency ◽

Compartment Model ◽

Biological Tissues ◽

Extracellular Medium ◽

Two Compartment Model ◽

Random Decision Forests ◽

Human Experiments ◽

Micro Structures

Abstract Background As an object’s electrical passive property, the electrical conductivity is proportional to the mobility and concentration of charged carriers that reflect the brain micro-structures. The measured multi-b diffusion-weighted imaging (Mb-DWI) data by controlling the degree of applied diffusion weights can quantify the apparent mobility of water molecules within biological tissues. Without any external electrical stimulation, magnetic resonance electrical properties tomography (MREPT) techniques have successfully recovered the conductivity distribution at a Larmor-frequency. Methods This work provides a non-invasive method to decompose the high-frequency conductivity into the extracellular medium conductivity based on a two-compartment model using Mb-DWI. To separate the intra- and extracellular micro-structures from the recovered high-frequency conductivity, we include higher b-values DWI and apply the random decision forests to stably determine the micro-structural diffusion parameters. Results To demonstrate the proposed method, we conducted phantom and human experiments by comparing the results of reconstructed conductivity of extracellular medium and the conductivity in the intra-neurite and intra-cell body. The phantom and human experiments verify that the proposed method can recover the extracellular electrical properties from the high-frequency conductivity using a routine protocol sequence of MRI scan. Conclusion We have proposed a method to decompose the electrical properties in the extracellular, intra-neurite, and soma compartments from the high-frequency conductivity map, reconstructed by solving the electro-magnetic equation with measured B1 phase signals.

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