Biological Tissue Distribution Research Articles

Unique identifiability of elastic parameters from time-dependent interior displacementmeasurement

We consider the question: what can be determined about the stiffness distribution inbiological tissue from indirect measurements? This leads us to consider an inverse problemfor the identification of coefficients in the second-order hyperbolic system that modelsthe propagation of elastic waves. The measured data for our inverse problemare the time-dependent interior vector displacements. In the isotropic case, weestablish sufficient conditions for the unique identifiability of wave speeds andthe simultaneous identifiability of both density and the Lamé parameters. In theanisotropic case, counterexamples are presented to exhibit the nonuniqueness and toshow the structure of the set of shear tensors corresponding to the same givendata.

Measurement and simulation of light distribution in biological tissues

Lateral light-distribution images of biologic tissues were used to study the tissues' optical characteristics. Monte Carlo simulation with the same conditions was performed to simulate the light distribution for comparison. Simulation results showed that the lateral light distribution was similar to the internal light distribution in biologic tissue. The direction of muscle fibers and the temperature both affect the near-field light distribution in tissue. The lateral view distribution can be both measured and simulated to study photon migration in tissue. It can also be used to estimate or verify the optical coefficients of tissue.

Determining Concentration Limits for Boron Quantification Using EELS and for Energy-Filtered Imaging

Abstract Electron energy-loss spectrometry and energy-filtered imaging allow the possibility of detecting, quantifying and mapping of boron. Boron spatial distribution in biological tissue is of particular interest for boron neutron capture therapy (BNCT) for cancer. We have studied the limits of boron quantification and mapping using electron energy-loss spectroscopy and energy-filtered imaging. To evaluate the concentration limits for boron mapping and quantification three types of specimens were used. First, a uniform boron layer of well known thickness deposited onto of 50 nm-thick carbon film was used to determine the limits for boron quantification. Second, samples for boron mapping with non-uniform boron distribution were prepared by electron-beam evaporation of boron onto a shadow-masked 50 nm-thick carbon film. Third, tobacco mosaic virus (TMV) in a water solution of boronophenylalanine fructrose (BPA-F) was deposited onto a 2 nm—thick carbon film.

The effect of anisotropy on the potential distribution in biological tissue and its impact on nerve excitation simulations.

We present a finite difference solution of the potential distribution associated with electrical current stimulation in an anisotropic in-homogeneous tissue environment and compare it to the isotropic case. The results demonstrate that there can be significant errors associated with the assumption of isotropic tissue properties in calculating the potential distribution along an axon in nerve excitation simulations. These errors can have a significant impact on predicted nerve fiber recruitment patterns when evaluating the efficacy of specific surface or intramuscular stimulus electrode configurations. The results of this study also suggest when a more comprehensive tissue model should be implemented in an electrode design study. Simulation results indicate that the isotropy assumption is worst under bipolar electrode stimulation as opposed to monopolar stimulation and that the bipolar error increases as the distance between electrodes decreases. In light of these results, it is concluded that in order to avoid large errors in the calculated potential distribution along an axon, the isotropy assumption should only be used when the transverse depth from the electrode to the nerve is relatively small.

Computer Simulation of Ultrasonic Images with Self-Similarity of Tissue Structures

A simulation model of reflection source distribution in biological tissues is proposed. The tissue is considered to consist of cells of various sizes. The distribution is computed using the fractal Brownian function. The ultrasound wave is reflected at the center of a cell and the coefficient of reflection is proportional to the area of a cell. The cell distribution is computed for the initial Hurst coefficient range of 0.2 to 0.8. The occupied area of every image is equal, because the cell density is kept constant. The Hurst coefficient of the ultrasonic image which is computed from the cell distribution is dependent on the initial Hurst coefficient for the cell distribution. As a result, it is indicated that the fractal analysis is effective for the characterization of tissue structure.

Characterization of Tissue Microstructure Scatterer Distribution with Spectral Correlation

Characterization of tissue microstructure from the backscattered ultrasound signal using the spectral autocorrelation (SAC) function provides information about the scatterer distribution in biological tissue. This paper demonstrates SAC capabilities in characterizing periodicities in A-scans due to regularity in the scatterer distribution. The A-scan is modelled as a cyclostationary signal, where the statistical parameters of the signal vary in time with single or multiple periodicities. This periodicity manifests itself as spectral peaks both in the power spectral density (PSD) and in the SAC. Periodicity in the PSD will produce a well defined dominant peak in the cepstrum, which has been used to determine the scatterer spacing. The relationship between the scatterer spacing and the spacing of the spectral peaks is established using a stochastic model of the echo-formation process from biological tissue. The distribution of the scatterers within the microstructure is modelled using a Gamma function, which offers a flexible method of simulating parametric regularity in the scatterer spacing. Simulations of the tissue microstructure for lower orders of regularity indicate that the SAC components reveal information about the scatterer spacing that are not seen in the PSD and the cepstrum. The echoformation process is tested by simulating microstructure of varying regularity and analyzing their effect on the SAC, PSD and cepstrum. Experimental validation of the simulation results are provided using in vivo scans of the breast and liver tissue that show the presence of significant spectral correlation components in the SAC.

PHOTOACTIVABLE FLUOROPHORES FOR THE MEASUREMENT OF FLUENCE IN TURBID MEDIA

AbstractKnowledge of the fluence distribution in biological tissue is essential for applications of lasers and light in medicine. A method using a photoactivable fluorophore as a chemical actinometer is presented to investigate the fluence (J/cm2) distribution in tissue‐simulating phantoms. Such a chemical actinometer provides high spatial resolution (≤20 μm) while minimizing the disturbance of the fluence distribution. The actinometer substance, nonfluorescent in its native state, is incorporated into an acrylamide gel. Upon absorption of 351 nm radiation (λact), the actinometer substance becomes a Ruorophorc, which is excited at λex≤ 485 nm. Thus the spatial distribution of the emitted fluorescence (λem≤ 515 nm) in the actinometer represents the fluence distribution of the activating radiation. Using histological techniques, 20 μm sections are cut from gel‐like optical phantoms containing the actinometric substance. The fluorescence intensity in the section is recorded under a standard fluorescence microscope equipped with a sensitive video camera. To simulate different biological tissues, the scattering and absorption properties of the gel phantoms arc varicd over a wide range. The experimentally obtained fluence distributions are compared with theoretical models of light distribution in turbid media.

Characterization of Tissue Microstructure Scatterer Distribution with Spectral Correlation

Characterization of tissue microstructure from the backscattered ultrasound signal using the spectral autocorrelation (SAC) function provides information about the scatterer distribution in biological tissue. This paper demonstrates SAC capabilities in characterizing periodicities in A-scans due to regularity in the scatterer distribution. The A-scan is modelled as a cyclostationary signal, where the statistical parameters of the signal vary in time with single or multiple periodicities. This periodicity manifests itself as spectral peaks both in the power spectral density (PSD) and in the SAC. Periodicity in the PSD will produce a well defined dominant peak in the cepstrum, which has been used to determine the scatterer spacing. The relationship between the scatterer spacing and the spacing of the spectral peaks is established using a stochastic model of the echo-formation process from biological tissue. The distribution of the scatterers within the microstructure is modelled using a Gamma function, which offers a flexible method of simulating parametric regularity in the scatterer spacing. Simulations of the tissue microstructure for lower orders of regularity indicate that the SAC components reveal information about the scatterer spacing that are not seen in the PSD and the cepstrum. The echo-formation process is tested by simulating microstructure of varying regularity and analyzing their effect on the SAC, PSD and cepstrum. Experimental validation of the simulation results are provided using in vivo scans of the breast and liver tissue that show the presence of significant spectral correlation components in the SAC.

Multiangle method for temperature measurement of biological tissues by microwave radiometry

A new approach for deriving the temperature distribution in biological tissues of microwave radiometry is proposed. It consists in the measurement of the thermal radiation of the body, at a given frequency, as a function of the observation angle, for two mutually orthogonal polarizations. Theoretically, this method yields results comparable to those obtained with the multispectral method. In order to derive the relations between the body temperature and the emitted thermal signal, the biological body is modeled by a set of parallel planar layers, each characterized by constant permittivity and temperature. It is demonstrated that for all practical purposes the radiation pattern of the antenna may be approximated by that of an unbounded plane wave.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Modelling ultrasonic response to defects in girth welds

Characterization of tissue microstructure from the backscattered ultrasound signal using the spectral autocorrelation (SAC) function provides information about the scatterer distribution in biological tissue. This paper demonstrates SAC capabilities in characterizing periodicities in A-scans due to regularity in the scatterer distribution. The A-scan is modelled as a cyclostationary signal, where the statistical parameters of the signal vary in time with single or multiple periodicities. This periodicity manifests itself as spectral peaks both in the power spectral density (PSD) and in the SAC. Periodicity in the PSD will produce a well defined dominant peak in the cepstrum, which has been used to determine the scatterer spacing. The relationship between the scatterer spacing and the spacing of the spectral peaks is established using a stochastic model of the echo-formation process from biological tissue. The distribution of the scatterers within the microstructure is modelled using a Gamma function, which offers a flexible method of simulating parametric regularity in the scatterer spacing. Simulations of the tissue microstructure for lower orders of regularity indicate that the SAC components reveal information about the scatterer spacing that are not seen in the PSD and the cepstrum. The echo-formation process is tested by simulating microstructure of varying regularity and analyzing their effect on the SAC, PSD and cepstrum. Experimental validation of the simulation results are provided using in vivo scans of the breast and liver tissue that show the presence of significant spectral correlation components in the SAC.

Electromagnetic remote sensing of the temperature profile in a stratified medium of biological tissues by stochastic inversion of radiometric data

Some results are presented from investigations studying the process of inversion of multispectral microwave radiometric data to determine the subcutaneous temperature distribution in biological tissues. A transmission line concept is used to model a three‐layer planar configuration as typical for the tissue composition of a human upper arm (skin‐fat‐muscle). Computer‐simulated data are generated at 3, 5, and 10 GHz using the Rayleigh‐Jeans approximation and the radiative transfer approach. Starting from a characteristic temperature profile, the radiometric data set is inverted to yield reconstructed values of the profile. Using the process of stochastic inversion, it is shown how to compromise between penetration depths, temperature resolution, and confidence level of the temperature values retrieved.