The current growing of food industry for low production costs and high efficiency needs for maintenance of high-quality standards and assurance of food safety while avoiding liability issues. Quality and safety of food depend on physical (texture, color, tenderness etc.), chemical (fat content, moisture, protein content, pH, etc.), and biological (total bacterial count etc.) features. There is a need for a rapid (less than a few minutes) and accurate detection system in order to optimize quality and assure safety of food. However, the fluorescence ranges for known fluorophores are limited to ultraviolet emission bands, which are not in the tissue near infrared (NIR) “optical window”. Biological tissues excited by far-red or NIR light would exhibit strong emission in spectral range of 650-1,100 nm although no characteristic peaks show the emission from which known fluorophores. The characteristics of the auto-fluorescence emission of different types of tissues were found to be different between different tissue components such as fat, high quality muscle food. In this paper, NIR auto-fluorescence emission from different types of muscle food and fat was measured. The differences of fluorescence intensities of the different types of muscle food and fat emissions were observed. These can be explained by the change of the microscopic structure of physical, chemical, and biological features in meat. The difference of emission intensities of fat and lean meat tissues was applied to monitor food quality and safety using spectral polarized imaging, which can be detect deep depth fat under the muscle food up to several centimeter.
Raman spectroscopy has become widely used for diagnostic purpose of breast, lung and brain cancers. This report introduced a new approach based on spatial frequency spectra analysis of the underlying tissue structure at different stages of brain tumor. Combined spatial frequency spectroscopy (SFS), Resonance Raman (RR) spectroscopic method is used to discriminate human brain metastasis of lung cancer from normal tissues for the first time. A total number of thirty-one label-free micrographic images of normal and metastatic brain cancer tissues obtained from a confocal micro- Raman spectroscopic system synchronously with examined RR spectra of the corresponding samples were collected from the identical site of tissue. The difference of the randomness of tissue structures between the micrograph images of metastatic brain tumor tissues and normal tissues can be recognized by analyzing spatial frequency. By fitting the distribution of the spatial frequency spectra of human brain tissues as a Gaussian function, the standard deviation, σ, can be obtained, which was used to generate a criterion to differentiate human brain cancerous tissues from the normal ones using Support Vector Machine (SVM) classifier. This SFS-SVM analysis on micrograph images presents good results with sensitivity (85%), specificity (75%) in comparison with gold standard reports of pathology and immunology. The dual-modal advantages of SFS combined with RR spectroscopy method may open a new way in the neuropathology
applications.
The extinction spectra and optical coefficients of human cancerous and normal prostate tissues were investigated in the spectral range of 750 nm - 860 nm. The scattering coefficient (μs) was determined from the extinction measurements on thin prostate tissue and Beer’s law. The absorption coefficient (μa) and the reduced scattering coefficient (μs') were extracted from integrate sphere intensity measurements on prostate tissue of which the thickness is in the multiple scattering range. The anisotropy factor (g) was calculated using the extracted values of μs and μs'. A micro-optical model of soft biological tissue was introduced to simulate the numerical computation of the absolute magnitudes of its scattering coefficients from the refractive index and a particle distribution function based on the Mie theory. A key assumption of the model is that the refractive index variations caused by microscopic tissue elements can be treated as particles with sizes distributed according to a skewed log-normal distribution function. The particle distribution and mean particle size of the two types of tissues were then calculated. Results show that the mean diameter of the particle size of cancerous tissue is larger than that of the cancerous tissue, which is responsible for larger reduced scattering coefficient of normal tissue in comparison with cancerous tissue. The results can be explained the change of tissue during prostate cancer evolution defined by Gleason Grade. The difference of the particles distribution and optical coefficients of cancerous and normal prostate tissues may present a potential criterion for prostate cancer detection.
The purpose of this study is to quantitatively assess the myocardial perfusion by first-pass technique in swine model. Numerous techniques based on the analysis of Computed Tomography (CT) Hounsfield Unit (HU) density have emerged. Although these methods proposed to be able to assess haemodynamically significant coronary artery stenosis, their limitations are noticed. There are still needs to develop some new techniques. Experiments were performed upon five (5) closed-chest swine. Balloon catheters were placed into the coronary artery to simulate different degrees of luminal stenosis. Myocardial Blood Flow (MBF) was measured using color microsphere technique. Fractional Flow Reserve (FFR) was measured using pressure wire. CT examinations were performed twice during First-pass phase under adenosine-stress condition. CT HU Density (HUDCT) and CT HU Density Ratio (HUDRCT) were calculated using the acquired CT images. Our study presents that HUDRCT shows a good (y=0.07245+0.09963x, r2=0.898) correlation with MBF and FFR. In receiver operating characteristic (ROC) curve analyses, HUDRCT provides excellent diagnostic performance for the detection of significant ischemia during adenosine-stress as defined by FFR indicated by the value of Area Under the Curve (AUC) of 0.927. HUDRCT has the potential to be developed as a useful indicator of quantitative assessment of myocardial perfusion.
To evaluate the feasibility of measuring the myocardial blood flow using 320 row detector CT by first-pass technique. Heart was simulated with a container that was filled with pipeline of 3mm diameter; coronary artery was simulated with a pipeline of 2 cm diameter and connected with the simulated heart. The simulated coronary artery was connected with a big container with 1500 ml saline and 150ml contrast agent. One pump linking with simulated heart will withdraw with a speed of 10 ml/min, 15 ml/min, 20 ml/min, 25 ml/min and 30 ml/min. First CT scan starts after 30 s of pumpback with certain speed. The second CT scan starts 5 s after first CT scans. CT images processed as follows: The second CT scan images subtract first CT scan images, calculate the increase of CT value of simulated heart and the CT value of the unit volume of simulated coronary artery and then to calculate the total inflow of myocardial blood flow. CT myocardial blood flows were calculated as: 0.94 ml/s, 2.09 ml/s, 2.74 ml/s, 4.18 ml/s, 4.86 ml/s. The correlation coefficient is 0.994 and r2 = 0.97. The method of measuring the myocardial blood flow using 320 row detector CT by 2 scans is feasible. It is possible to develop a new method for quantitatively and functional assessment of myocardial perfusion blood flow with less radiation does.
Tissues are an impressive complex creation comprised of a vast of assortment of molecules, structures and functional units. Despite this overwhelming complexity, we may still discuss average optical properties as long as we realize the limitations involved. There are five independent macroscopic parameters that are believed to characterize light propagation in tissue: the index of refraction (n), the absorption coefficient (μa), the scattering coefficient (μs), the reduced scattering coefficient (μ's), and the scattering anisotropy (g). This paper summarizes the Optical characteristics of tissue of prostate tissues ex vivo and the key fluorophores related to carcinogenesis. The absorption coefficient (μa) describes the effectiveness of light absorbed by certain chromophore. The key spectra fingerprints of water were introduced to distinguish different water contents in normal and cancerous prostate tissues. Fluorescence occurs when a molecule, atom or nanostructure relaxes to its ground state after being electrically excited. There are three fluorescence parameters of interest we may concern in tissue optics: the fluorescence lifetime (τf), the fluorescence quantum yield (Φ) and the fluorescence emission peak (λmax). The key wavelengths which can be used for cancer detection were reviewed. Scattering of light occurs in media which contains fluctuations in the refractive index n. Tissue ultrastructure extends from membranes to membrane aggregates to collagen fibers to nuclei to cells, which may be an alternative way to detect cancer in tissues.
The fluorophores of malignant human breast cells change their compositions that may be exposed in the fluorescence spectroscopy and blind source separation method. The content of the fluorophores mixture media such as tryptophan, collagen, elastin, NADH, and flavin were varied according to the cancer development. The native fluorescence spectra of these key fluorophores mixture media excited by the selective excitation wavelengths of 300 nm and 340 nm were analyzed using a blind source separation method: Nonnegative Matrix Factorization (NMF). The results show that the contribution from tryptophan, NADH and flavin to the fluorescence spectra of the mixture media is proportional to the content of each fluorophore. These data present a possibility that native fluorescence spectra decomposed by NMF can be used as potential native biomarkers for cancer detection evaluation of the cancer.
It is well-known that light transport can be well described using Maxwell’s electromagnetic theory. In biological tissue, the scattering particles cause the interaction of scattered waves from neighboring particles. Since such interaction cannot be ignored, multiple scattering occurs. The theoretical solution of multiple scattering is complicated. A suitable description is that the wavelike behavior of light is ignored and the transport of an individual photon is considered to be absorbed or scattered. This is known as the Radiative Transfer Equation (RTE) theory. Analytical solutions to the RTE that explicitly describes photon migration can be obtained by introducing some proper approximations. One of the most popular models used in the field of tissue optics is the Diffusion Approximation (DA). In this study, we report on the results of our initial study of optical properties of ex vivo normal and cancerous prostate tissues and how tissue parameters affect the near infrared light transporting in the two types of tissues. The time-resolved transport of light is simulated as an impulse isotropic point source of energy within a homogeneous unbounded medium with different absorption and scattering properties of cancerous and normal prostate tissues. Light source is also modulated sinusoidally to yield a varied fluence rate in frequency domain at a distant observation point within the cancerous and normal prostate tissues. Due to difference of the absorption and scattering coefficients between cancerous and normal tissues, the expansion of light pulse, intensity, phase are found to be different.
The scattering coefficient, μs, the anisotropy factor, g, the scattering phase function, p(θ), and the angular dependence of scattering intensity distributions of human cancerous and normal prostate tissues were systematically investigated as a function of wavelength, scattering angle and scattering particle size using Mie theory and experimental parameters. The Matlab-based codes using Mie theory for both spherical and cylindrical models were developed and applied for studying the light propagation and the key scattering properties of the prostate tissues. The optical and structural parameters of tissue such as the index of refraction of cytoplasm, size of nuclei, and the diameter of the nucleoli for cancerous and normal human prostate tissues obtained from the previous biological, biomedical and bio-optic studies were used for Mie theory simulation and calculation. The wavelength dependence of scattering coefficient and anisotropy factor were investigated in the wide spectral range from 300 nm to 1200 nm. The scattering particle size dependence of μs, g, and scattering angular distributions were studied for cancerous and normal prostate tissues. The results show that cancerous prostate tissue containing larger size scattering particles has more contribution to the forward scattering in comparison with the normal prostate tissue. In addition to the conventional simulation model that approximately considers the scattering particle as sphere, the cylinder model which is more suitable for fiber-like tissue frame components such as collagen and elastin was used for developing a computation code to study angular dependence of scattering in prostate tissues. To the best of our knowledge, this is the first study to deal with both spherical and cylindrical scattering particles in prostate tissues.
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