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Frozen section analysis is a frequently used method for examination of tissue samples, especially for tumour detection. In the majority of cases, the aim is to identify characteristic tissue morphologies or tumour margins. Depending on the type of tissue, a high number of misdiagnoses are associated with this process. In this work, a fast spectroscopic measurement device and workflow was developed that significantly improves the speed of whole frozen tissue section analyses and provides sufficient information to visualize tissue structures and tumour margins, dependent on their lipid and protein molecular vibrations. That optical and non-destructive method is based on selected wavenumbers in the mid-infrared (MIR) range. We present a measuring system that substantially outperforms a commercially available Fourier Transform Infrared (FT-IR) Imaging system, since it enables acquisition of reduced spectral information at a scan field of 1 cm2 in 3 s, with a spatial resolution of 20 µm. This allows fast visualization of segmented structure areas with little computational effort. For the first time, this multiphotometric MIR system is applied to biomedical tissue sections. We are referencing our novel MIR scanner on cryopreserved murine sagittal and coronal brain sections, especially focusing on the hippocampus, and show its usability for rapid identification of primary hepatocellular carcinoma (HCC) in mouse liver.

Near-infrared (NIR) microlasers play a significant role in telecommunication and biomedical tissue imaging. However, it remains a big challenge to realize NIR microlasers because of the difficulty in preparing highly efficient NIR luminescent materials and perfect optical resonators. Here, we propose a molecular design strategy to creatively realize the first spiropyrane (SP)-based NIR microlasers with low threshold from self-assembled microsphercial caps. The tetraphenylethylene (TPE) moiety with a highly twisted conformation provides a large free volume to facilitate the photoisomerization process of SP and enhance NIR emission of merocyanine in the solid state. Moreover, self-assembled TPE-SP microsphercial caps simultaneously serve as gain media and resonant microcavities, providing optical gain and feedback for NIR laser oscillations with a low threshold (3.68 μJ/cm

Complete characterization of biological samples is of potential interest in different industrial and research areas, as for instance, in biomedical applications, for the recognition of organic structures or for the early detection of some diseases. During the last decades, polarimetric methods are experiencing an increase of attention in the study of biomedical tissues, and they are nowadays used in such framework to provide qualitative (polarimetric imaging) and quantitative (data processing) information for the studied samples. Polarimetric methods are based on the analysis of polarization modifications produced by light-matter interactions which can be triggered by a number of complex internal processes but can be roughly understood as the result of the combination of three pure polarimetric features of the sample: its diattenuation, retardance and depolarization. For the analysis of the depolarization content, we propose the use of the Indices of Polarimetric Purity (IPP) to describe the sample behavior. Related with the randomness of the scattering processes, IPPs provide more information of depolarizing systems than the widely used depolarization index (p^), which further synthetize the depolarization content of samples. Moreover, certain combinations of IPP parameters leads to p^. As a result, IPPs allow the revelation of some structures from tissue samples hidden in regular intensity images of even in the p^ channel, leading to better tissue classification results. In this work, we present different applications of IPPs in biomedical tissue that show its potential, which are not restricted to the biomedical framework as relevant results in plants characterization are also presented.

Energy recovery methods are currently receiving a very great deal of attention from the research community. Especially, in the case of implantable biosensors where wireless energy transfer has become the main technique in these applications. An implant is a medical device manufactured to replace a missing biological structure, support a damaged biological structure, or enhance an existing biological structure. Biosensors are man-made devices, in contrast to a transplant, which is a transplanted biomedical tissue. The method of energy transfer eliminates the risk of skin infection, as well as the need for invasive surgery to change the battery. In this paper, we present the efficient approach to design an optimized octagonal spiral inductor operating at a frequency of 2.4 GHz with an inductance L value of 4 nH and a maximum factor of quality Q. The principle part of this work is based on the use of a collection of methods called metaheuristics, which are approaches used to solve a wide range of optimization problems, in order to achieve a high-performance optimized design. The problem is represented by an objective function that will be implemented using a MATLAB script and then the validation of the results obtained will be performed using the advanced design system (ADS) microwave circuit simulation software.

Due to the multiple scattering of light in biomedical tissue, the imaging depth of conventional optical coherence tomography is limited to 1-2 millimeters. In this research, a reflection-matrix-method-based optical coherence tomography has been developed to extend the imaging depth into scattering medium. After obtaining the matrix, singular value decomposition and imaging reconstruction are carried out in the post-process to recover the target image beneath turbid media. Specifically, in order to speed up the matrix measurement and reduce the phase noises during the acquisition process, wide-field heterodyne detection is adopted in our system by using a high-speed lock-in camera.

the dispersion properties of spoof surface plasmon polaritons with 1D rectangular groove structure by analytical solution and numerical solution respectively is analyzed, and the FEM method was used to simulate the refractive index sensing of SPR in terahertz band in an Otto configuration. From the simulation results, we can see that the 1D periodic groove has strong field constraint ability in THz regime as well as in optical band, and the variation of reflection coefficient with incident angle and frequency is very sensitive to the refractive index of the analyte. These results provide a new approach to sample detection and THz regime refractive index sensing, which has great advantages in biomedical tissue detection and sample detection in the future.

We have demonstrated a high-energy and broadly tunable monochromatic terahertz (THz) source via difference frequency generation (DFG) in DAST crystal. The THz frequency is tuned randomly in the range of 0.3-19.6 THz, which is much wider than the THz source based on the inorganic crystal and the photoconductive antenna. The highest energy of 2.53μJ/pulse is obtained at 18.9 THz corresponding to the optical-to-optical conversion efficiency of 1.31×10-4. The THz output spectroscopy is theoretically and experimentally explained by DFG process and Raman spectroscopy. Meanwhile, a phenomenon of blue light from the KTP-OPO with tunable and multiple wavelengths was firstly observed and explained. Based on our THz source, an ultra-wideband THz frequency domain system (THz-FDS) with transmission mode is realized to measure the ultra-wideband THz spectroscopies of typical materials in solid and liquid states, such as Si, SiC, White PE, water, isopropyl myristate, simethicone, atonlein and oleic acid, etc.. Furthermore, we have studied the THz spectral characteristic of biomedical tissue in the ultra-wideband THz frequency range of 0.3-15THz to study the biomedical response in the entire THz frequency range, which contains more abundant spectral information and was rarely focused with the limit of the THz source.

Multiple light scattering in biomedical tissue limits the penetration depth of optical imaging systems such as optical coherence tomography. To increase the imaging depth in scattering media, a computational method based on coherent reflection matrix measurement has been developed using low coherence interferometry. The complex reflection matrix is obtained via point-by-point scanning followed by a phase-shifting method; then singular value decomposition is used to retrieve the singly back-scattered light. However, the in vivo application of the current reported method is limited due to the slow acquisition speed of the matrix. In this Letter, a wide-field heterodyne-detection method is adopted to speed up the complex matrix measurement at a deep tissue layer. Compared to the phase-shifting method, the heterodyne-detection scheme retrieves depth-resolved complex amplitudes faster and is more stable without mechanical movement of the reference mirror. As a result, the matrix measurement speed is increased by more than one order of magnitude.

Many imaging technologies, such as two photon microscopy (TPM), second generation microscopy (SHG) and photoacoustic microscopy (PAM), have successfully demonstrated the ability to extract anatomical, functional and molecular information of biological samples. However, they always fail to obtain comprehensive information from biological tissue due to single imaging modality. To address this limitation, we developed a multimodal microscopy with fully integrated PAM, TPM and SHG. The home-built multimodal microscopy system enable label-free imaging of biomedical tissue with sub-micron resolution in vivo and in vitro. The results may offer a new tool to provide the capable of fast comprehensive information capturing for biological studies.

Biomedical tissue classification is of great interest in many fields, e.g. for finding a clear boundary for cancer resections. At the moment, no sufficient tool has been found to fulfill the needs for intraoperative surgical guidance. For a precise tumor removal, the resolution has to be as high as possible and the delivered information should be in real time. Otherwise intraoperative guidance cannot be done accurately. Optical coherence tomography (OCT) has already demonstrated its benefits in ophthalmology, dermatology and endoscopy. Providing μm resolution for a penetration depth of 1-2 mm at acquisition rates in the MHz regime, OCT is a perfect tool for contactless investigations during surgery. Additional benefit can be provided if the obtained images are analyzed and the tissue type is immediately classified. Usually, the histopathological analysis of ex vivo samples directly after removal conforms the tissue classification. A common practice for that is the histopathological analysis, where the samples are embedded in paraffin, stained with, e.g. hematoxylin and eosin and then, classified by an experienced pathologist, who analyzes tissue slices of approximately 10 μm thickness. By employing OCT for classification, an entire three-dimensional image can be classified without further preparation of the tissue. Here we present a texture feature based approach by utilizing local binary patterns, run length analysis, Haralicks texture features and Laws texture energy measures. After applying all these texture features, a principal component analysis (PCA) was performed, which decreased the dimensionality of the data set. This step was necessary in order to enhance the performance of the employed support vector machines (SVM) classifier. To find the best parameters for the kernel, a grid search and a 10 fold cross validation were done. As a first step, the texture analysis based post processing approaches were applied on 13 ex vivo brain tissue samples, which were diagnosed as meningioma (8), healthy white tissue (3) and healthy gray tissue (2). The samples were imaged with a commercial OCT system (Thorlabs Callisto). On the raw OCT images, some structural differences between healthy tissue and meningioma may already be recognized. However, an automated approach that does not require interpretation of the result, would certainly help the surgeon during surgery. At the end, we trained a SVM classifier, which was able to differentiate between healthy tissue and meningioma, with an accuracy of nearly 98%. As the next logical step, these findings will be validated intraoperatively and further application for texture based classification will be investigated.

Pharmacokinetic diffuse fluorescence tomography (DFT) can describe the metabolic processes of fluorescent agents in biomedical tissue and provide helpful information for tumor differentiation. In this paper, a dynamic DFT system was developed by employing digital lock-in-photon-counting with square wave modulation, which predominates in ultra-high sensitivity and measurement parallelism. In this system, 16 frequency-encoded laser diodes (LDs) driven by self-designed light source system were distributed evenly in the imaging plane and irradiated simultaneously. Meanwhile, 16 detection fibers collected emission light in parallel by the digital lock-in-photon-counting module. The fundamental performances of the proposed system were assessed with phantom experiments in terms of stability, linearity, anti-crosstalk as well as images reconstruction. The results validated the availability of the proposed dynamic DFT system.

The energy of light exposed on human skin is compulsively limited for safety reasons which affects the power of photoacoustic (PA) signal and its signal-to-noise ratio (SNR) level. Thus, the final reconstructed PA image quality is degraded. This Letter proposes an adaptive multi-sample-based approach to enhance the SNR of PA signals and in addition, detailed information in rebuilt PA images that used to be buried in the noise can be distinguished. Both ex vivo and in vivo experiments are conducted to validate the effectiveness of our proposed method which provides its potential value in clinical trials. OCIS codes: 100.2980, 170.1065, 170.5120. doi: 10.3788/COL201513.061001. Research on photoacoustic tomography (PAT) got prosperous development for its being promisingly characterized with noninvasive and nonionizing diagnose of breast cancer, arthritis, and relevant disease. PAT combines the metrics of both ultrasound imaging and pure optical imaging technique, providing high ultrasonic resolution and high optical contrast images [1–5] . Due to the peculiarity that the optical absorption characteristic of blood has a strong relationship with the hemoglobin content, functional imaging as well as structural imaging can also be realized by PAT, making this imaging modality extremely potential in clinical application [6] . The basic principle of PAT is that a tissue is irradiated with short nanosecond laser pulses, and then the absorbed energy may result in a thermo-elastic expansion and subsequent contraction of irradiated volume that generates time-trace photoacoustic (PA) waves, which can be acquired by scanning small-aperture ultrasound detectors over a surface that encloses the source under study. The recorded PA wave can then be reconstructed to spatially resolve the initial absorber distribution and concentration via PA reconstruction algorithms [7–9]. However, biomedical tissue is a highly scattering medium for electromagnetic waves in the optical spectral range, and the propagation ultrasound waves are extremely attenuated before received by ultrasound sensors. Furthermore, the dose of laser beam exposed on the biomedical tissue has to be limited under 20 mJ∕cm 2 for safety operation. Thus, in clinical trials, ultrasound transducer can only receive weak PA signals with low signal-to-noise ratio (SNR) which degraded the final reconstructed PA images [10–14] . This Letter proposes an adaptive multi-sample-based approach to enhance the SNR of PA signals and in addition, detailed information of PAT that used to be buried in the noise and artifacts can be distinguished. The PA reconstruction is an inverse problem of the source pressure. We assume that a tissue with inhomogeneous microwave absorption but a relatively homogeneous acoustic property and the heat diffusion’s effect on the thermoacoustic wave can be ignored. For cases where the scanning radius in a circular scan configuration is much greater than the PA wavelengths, the optical absorption p0ðrÞ within the sample at a given position r is given as [1]

In this paper we present a CAD model of optical fibre reflectance probe for biomedical diffuse reflectance spectroscopy applications. Henyey-Greenstein model is used to model the scattering form the biomedical tissue. The CAD model is used to predict the coupling efficiency of the fibre probe with different multimode fibre core diameter and to estimate the separation distance between the probe and the sample for optimized coupling.

We proposed a transcutaneous energy transmission system (TETS) for implantable ventricular assist devices (VADs) in order to improve the quality of life (QOL) of patients. In a conventional TETS, the patient must accurately and tightly fix a rigid coil on his body surfaces because the transmission efficiency remarkably depends on the alignment accuracy of the coil. In order to improve the robustness of the alignment, we proposed a magnetic resonant coupling TETS of long transmission range utilizing flexible coils embedded into clothes. We experimentally evaluated the influence of the coil deformation and biomedical tissue on the transmission efficiency.

This paper states wireless power transfer (WPT) from an AC power supply to a micro implant device in human body. At first, an equivalent circuit of WPT which contains biomedical tissue is constructed with an AC power supply, parasitic components, load resistance, and inductances. Then a state equation which stands for the behavior of circuit is found, and the expression of efficiency is derived as the ratio of the power of power supply and load. Finally an experiment is conducted based on the theoretical calculation, and the error between experimental and calculated result is computed and examined.

A new configuration of semiconductor detectors for backscattered electrons for a scanning electron microscope (SEM) is presented. The result of the optimization was the possibility to extract the information about the spatial relief (3D topology) of the sample and its subsurface structure (3D tomography) in the simplest way. The detector consists of 8 sensors-semiconductor plates, positioned in a certain way. The proposed method was tested on real structures having a surface micro relief or a subsurface volume structure. Experiments and simple calculations show increased effectiveness and a high signal-noise ratio in the proposed method. This is important, particularly for studying the radiation-sensitive biomedical tissue in SEM.

Three-dimensional computerized characterization of biomedical solid textures is key to large-scale and high-throughput screening of imaging data. Such data increasingly become available in the clinical and research environments with an ever increasing spatial resolution. In this text we exhaustively analyze the state-of-the-art in 3-D biomedical texture analysis to identify the specific needs of the application domains and extract promising trends in image processing algorithms. The geometrical properties of biomedical textures are studied both in their natural space and on digitized lattices. It is found that most of the tissue types have strong multi-scale directional properties, that are well captured by imaging protocols with high resolutions and spherical spatial transfer functions. The information modeled by the various image processing techniques is analyzed and visualized by displaying their 3-D texture primitives. We demonstrate that non-convolutional approaches are expected to provide best results when the size of structures are inferior to five voxels. For larger structures, it is shown that only multi-scale directional convolutional approaches that are non-separable allow for an unbiased modeling of 3-D biomedical textures. With the increase of high-resolution isotropic imaging protocols in clinical routine and research, these models are expected to best leverage the wealth of 3-D biomedical texture analysis in the future. Future research directions and opportunities are proposed to efficiently model personalized image-based phenotypes of normal biomedical tissue and its alterations. The integration of the clinical and genomic context is expected to better explain the intra class variation of healthy biomedical textures. Using texture synthesis, this provides the exciting opportunity to simulate and visualize texture atlases of normal ageing process and disease progression for enhanced treatment planning and clinical care management. (C) 2013 Elsevier B.V. All rights reserved.

Matrix-assisted laser desorption ionization (MALDI) mass spectrometry imaging (MSI) brings unique combined information on molecular identity and molecular distribution of a sample surface. During the past decade, it has matured and is now routinely employed for biomedical tissue sections analysis. However, owing to the high molecular complexity of tissue, MALDI-MSI suffers from ionization suppression effects. This directly results in a reduced ability to detect low-abundant molecular species. At the same time, the spatial resolution of separation techniques can be insufficient for an unambiguous determination of the local composition of a mixture. As analytical separation techniques can significantly reduce ion suppression, and MALDI-MSI has an ability to improve their spatial resolution, the two analytical approaches can successfully be combined in a pursuit of comprehensive local sample composition information. In the following review we summarize strategies of mutually beneficial combinations of MALDI-MSI and different separation techniques and discuss limitations and future developments.

A bioreactor has provided a new way for the biomedical tissue engineering, and it is a device system that simulates the metabolism and movement of organisms to obtain target product in vitro. By reference and study of the bioreactors, based on the linear motor of high-precision and high-frequency characteristics, we have designed a bioreactor with varieties of biomechanical functions by using CAD design software, that is especially used in the tissue engineering for mechanical stimulation. The bioreactor can not only load on the cultures under rolling, sliding or their combination as well as tension and compression, but also on the cultures under high-frequency and dual-frequency forces. It will provide a more effective research platform for tissue culture and regeneration.

Tingli Lu,1,* Yuhui Li,1,* Tao Chen1,21Key Laboratory of Space Bioscience and Biotechnology, School of Life Science, Northwestern Polytechnical University, 2Liposome Research Centre, Xi'an, China*These authors contributed equally to this workAbstract: Three-dimensional biomimetic scaffolds have widespread applications in biomedical tissue engineering because of their nanoscaled architecture, eg, nanofibers and nanopores, similar to the native extracellular matrix. In the conventional “top-down” approach, cells are seeded onto a biocompatible and biodegradable scaffold, in which cells are expected to populate in the scaffold and create their own extracellular matrix. The top-down approach based on these scaffolds has successfully engineered thin tissues, including skin, bladder, and cartilage in vitro. However, it is still a challenge to fabricate complex and functional tissues (eg, liver and kidney) due to the lack of vascularization systems and limited diffusion properties of these large biomimetic scaffolds. The emerging “bottom-up” method may hold great potential to address these challenges, and focuses on fabricating microscale tissue building blocks with a specific microarchitecture and assembling these units to engineer larger tissue constructs from the bottom up. In this review, state-of-the-art methods for fabrication of three-dimensional biomimetic scaffolds are presented, and their advantages and drawbacks are discussed. The bottom-up methods used to assemble microscale building blocks (eg, microscale hydrogels) for tissue engineering are also reviewed. Finally, perspectives on future development of the bottom-up approach for tissue engineering are addressed.Keywords: three-dimensional, extracellular matrix scaffolds, bottom-up, tissue engineering

Over the last two decades, considerable advances have been made toward modeling light propagation in tissue. ™ese advances have been mainly driven by the development of optical tomographic imaging techniques, which rely on accurate modeling of light-tissue interactions in biomedical tissue. ™ese techniques employ near-infrared (NIR) light in the wavelength range of 600-900 nm, to probe biological tissue and image physiological functions (Gibson et al. 2005, Nissila et al. 2005, Gibson and Dehghani 2009). ™e propagation of light in the NIR is governed by the spatial distribution of the tissue’s scattering and absorption coeŸcients, given by μs and μa, respectively. ™e scattering coeŸcient takes on values in the range of μs = 20, …, 200 cm−1 (Cheong et al. 1990, Cheong 1995, Collier et al. 2005). Also, o²en used to describe optical properties of tissue is the reduced scattering coeŸcient, μ′s = (1 − g)μs, which is a scaled scattering coeŸcient that takes into account the mean scattering cosine g (anisotropy factor) of a single scattering event. Typical values of g in tissue are between 0.8 and 0.98. Dižerence in the refractive index (RI) between intracellular and extracellular ¦uids, and various subcellular components, such as mitochondria or nuclei, as well as varying tissue densities give rise to dižerences in scattering coeŸcient and g-factors (Mourant et al. 1998, 2000). A multitude of chromophores inside tissue cause absorption at various wavelengths. ™e absorption coeŸcient covers a wide range of values from μa = 0.01 to 0.5 cm−1, for NIR (Utzingeret al. 2001, Culver et al. 2003, Drezek et al. 2003, Srinivasan et al. 2003). Endogenous chromophores are, for example, hemoglobin, cytochrome, ¦avins, and porphyrins. Dižerences in chromophore content and concentration lead to dižerent absorption coeŸcients μa(r).

We demonstrate high-resolution small-angle x-ray scattering computed tomography (SAXS-CT) of soft matter and soft tissue samples. Complete SAXS patterns over extended ranges of momentum transfer are reconstructed spatially resolved from volumes inside an extended sample. Several SAXS standard samples are used to quantitatively validate the method and demonstrate its performance. Further results on biomedical tissue samples (rat brains) are presented that demonstrate the advantages of the method compared to existing biomedical x-ray imaging approaches. Functional areas of the brains as well as tumor morphology are imaged. By providing insights into the structural organization at the nano-level, SAXS-CT complements and extends results obtainable with standard methods such as x-ray absorption tomography and histology.

Biomedical ultrasound is often used for investigations within and close to tissue inhomogeneities, such as lesions and plaques, that are midsized compared with the ultrasound wavelength. The scaled wavenumber is typically in the range 1 to 100. Even with small (less than 10%) sound speed variations, such objects are associated with very complicated diffractive field magnitude modulations. The corresponding phase modulations are much more regular, and this observation is the basis for the method described in this paper. The acoustic field can be expressed in terms of a scattering integral. For biomedical parameters, calculations with the widely used Born approximation give accurate results in only very limited circumstances. In this paper we demonstrate the importance of the initial phase estimate, and introduce the Phase Corrected Scattering Integral (PCSI) method. We show that remarkably accurate results for the acoustic field can be obtained from a single evaluation of the scattering integral if this incorporates an initial estimate of the phase modulation imposed by the inhomogeneity. A simple ray model can be used to find the phase correction. The PCSI method deals very effectively with scattering due to small changes in sound speed and irregular geometry, both characteristic of biomedical problems.

FTIR microscopy is a powerful technique which has become popular due to its ability to provide complementary information during histopathological assessment of biomedical tissue samples. Recently however, questions have been raised on the suitability of the transflection mode of operation for clinical diagnosis due to the so called Electric Field Standing Wave (EFSW) effect. In this paper we compare chemical images measured in transmission and transflection from prostate tissue obtained from five different patients, and discuss the variability of the spectra acquired with each sampling modality. We find that spectra obtained in transflection undergo a non-linear distortion, i.e. non-linear variations in absorption band strength across the spectra, and that there are significant differences in spectra measured from the same area of tissue depending on the mode of operation. Principal Component Analysis (PCA) is used to highlight that poorer discrimination between benign and cancerous tissue is obtained in transflection mode. In addition we show that use of second derivatives, while qualitatively improves spectral discrimination, does not completely alleviate the underlying problem.

In this paper, a wireless power transfer system for implantable medical devices using a miniaturized 3 mm diameter single arm circular spiral antenna is presented. The transmission characteristics, S 21 between the transmitting and receiving antennas with air and tissue as a medium between antennas are analyzed and measured. The receiver antenna receives almost 2 mW average power with power transfer efficiency of 53%. The power transfer efficiency could still reach to 4% with 274 µW average received power, with placement of 1.5 cm tissue and 1 cm air in between two antennas. With one PN diode rectifier, the total DC power from the receiver side is 489 nW.

Microwave tomography (MWT) and ultrasound tomography (UT) are two biomedical imaging modalities which are currently being investigated for applications such as breast cancer imaging. In MWT, the object of interest (OI) is surrounded by a number of antennas that are used to radiate the OI successively with electromagnetic waves in the microwave frequency range. The scattered electric fields are collected at receiver locations surrounding the OI. On the other hand, in UT the OI is surrounded by several ultrasound transducers illuminating the OI by acoustic waves and the scattered pressure from the OI is then collected at the receivers. In both MWT and UT, the scattered data is given to an inverse scattering algorithm to reconstruct specific properties of the object: in MWT the relative permittivity and conductivity (or complex permittivity) of the OI are reconstructed, whereas in UT the complex compressibility and inverse density are reconstructed. Both are quantitative imaging methods and thereby provide some insight into type of tissue corresponding to a pixel value in the image.

OCT is a high speed, high resolution imaging technique which is mostly used for ophthalmology & biomedical tissue imaging. This paper describes the mathematical modeling, simulation & signal analysis of Time-Domain OCT (TD-OCT) & Spectral-Domain OCT (SD-OCT) systems. Using this simulation model, user can enter their OCT system parameters such as center wavelength, bandwidth of the source, power of the source, responsivity of the detector to get the simulated signals of OCT systems, which can be used for further analysis. This mathematical modeling provides an environment for OCT parameter evaluation and OCT signal simulation for different configurations of OCT systems. With the use of this simulation one can predict the output of their OCT system.

Fourier transform infrared (FT-IR) chemical imaging has been demonstrated as a promising technique to complement histopathological assessment of biomedical tissue samples. Current histopathology practice involves preparing thin tissue sections and staining them using hematoxylin and eosin (H&E) after which a histopathologist manually assess the tissue architecture under a visible microscope. Studies have shown that there is disagreement between operators viewing the same tissue suggesting that a complementary technique for verification could improve the robustness of the evaluation, and improve patient care. FT-IR chemical imaging allows the spatial distribution of chemistry to be rapidly imaged at a high (diffraction-limited) spatial resolution where each pixel represents an area of 5.5 × 5.5 μm2 and contains a full infrared spectrum providing a chemical fingerprint which studies have shown contains the diagnostic potential to discriminate between different cell-types, and even the benign or malignant state of prostatic epithelial cells. We report a label-free (i.e. no chemical de-waxing, or staining) method of imaging large pieces of prostate tissue (typically 1 cm × 2 cm) in tens of minutes (at a rate of 0.704 × 0.704 mm2 every 14.5 s) yielding images containing millions of spectra. Due to refractive index matching between sample and surrounding paraffin, minimal signal processing is required to recover spectra with their natural profile as opposed to harsh baseline correction methods, paving the way for future quantitative analysis of biochemical signatures. The quality of the spectral information is demonstrated by building and testing an automated cell-type classifier based upon spectral features.

Side-effects and lowering effects by diffusion of drugs such as anticancer agents is one of the serious issues in medication. To solve the problem, it is necessary to control the drugs quantitatively, spatially and temporally within the human body. Magnetic drug delivery system (MDDS) is one of the technologies that would make it possible, in which the ferromagnetic drug injected into the blood vessel is conducted to diseased part by external magnetic force. The ultimate goal of our study is to develop MDDS which can be used to guide the drug to the diseased part by controlling its movements from outside of human body using superconducting bulk magnet and ferromagnetic needle, and fundamental experiments to establish the MDDS system was conducted. To estimate the magnetic force required to accumulate ferromagnetic particle in blood vessel, particle distribution in the limited biomedical tissue was calculated. To check the validity of calculation, accumulation experiment of ferromagnetic particle in a model tissue consisting of glass beads packed in a glass tube was conducted. Based on these results, design of MDDS using permanent magnet system with facing two poles in a glass tube was conducted.

Formalin-fixed, paraffin-embedded (FFPE) tissue sections have widely been adopted for more than a century as the standard method for morphological study, particularly in the field of diagnostic pathology, most of the criteria for pathological diagnosis are established by the observation of FFPE tissue sections. With remarkable achievements in morphologic research field during the past one more century, FFPE tissue samples have been accumulated worldwide that are accompanied with complete clinical data including follow-up results of treatment, or, experimental data collected previously, resulted in an invaluable resource of research. Three more decades ago, immunohistochemistry (IHC) started to show its power and beauty in the field of histopathology, however, at the early stage it was largely limited on frozen tissue sections only. Formalin fixation masks the proteins (antigen) in the tissue sections that unfortunately become inaccessible for antibody in IHC. Numerous scientists urged to find a way to apply IHC staining on FFPE tissue sections based on a dream that formalin-modified proteins may be retrievable.

FTIR chemical imaging has been demonstrated as a promising technique to construct automated systems to complement histopathological evaluation of biomedical tissue samples. The rapid chemical imaging of large areas of tissue has previously been a limiting factor in this application. Consequently, smaller areas of tissue have previously had to be sampled, possibly introducing sampling bias and potentially missing diagnostically important areas. In this report a high spatial resolution chemical image of a whole prostate cross section is shown comprising 66 million pixels. Each pixel represents an area 5.5 × 5.5 μm2 of tissue and contains a full infrared spectrum providing a chemical fingerprint. The data acquisition time was 14 hours, thus showing that a clinical time frame of hours rather than days has been achieved. © 2013 The Royal Society of Chemistry.

The advantages of nonlinear ultrasound propagation are exploited in an ever increasing number of applications. As a consequence, much research is devoted to the development of numerical methods capable of modeling nonlinear pressure wave fields propagating through (inhomogeneous) biomedical tissue. These tools are essential to design and optimize ultrasound transducers and to investigate novel ultrasound modalities or devices. The iterative nonlinear contrast source (INCS) method is an accurate full-wave method for modeling three-dimensional nonlinear acoustic wave fields propagating through soft biomedical tissue containing arbitrary inhomogeneities in the coefficient of nonlinearity, attenuation and speed of sound. This method is directionally independent and can deal with large three-dimensional domains, measuring hundreds of wavelengths and periods, and scattering. Here, we present the first synthetic harmonic ultrasound images generated with INCS. The images are created using a delay-and-sum aperture focusing scheme. Results show the applicability of the INCS method as a simulator for ultrasound harmonic imaging systems.

To support the translation of Raman spectroscopy into clinical applications, synthetic models are needed to accurately test, optimize and validate prototype fiber optic instrumentation. Synthetic models (also called tissue phantoms) are widely used for developing and testing optical instrumentation for diffuse reflectance, fluorescence, and Raman spectroscopies. While existing tissue phantoms accurately model tissue optical scattering and absorption, they do not typically model the anatomic shapes and chemical composition of tissue. Because Raman spectroscopy is sensitive to molecular composition, Raman tissue phantoms should also approximate the bulk tissue composition. We describe the fabrication and characterization of tissue phantoms for Raman tomography and spectroscopy. These phantoms have controlled chemical and optical properties, and also multilayer morphologies which approximate the appropriate anatomic shapes. Tissue phantoms were fabricated to support on-going Raman studies by simulating the human wrist and rat leg. Surface meshes (triangle patch models) were generated from computed tomography (CT) images of a human arm and rat leg. Rapid prototyping was used to print mold templates with complex geometric patterns. Plastic casting techniques used for movie special effects were adapted to fabricate molds from the rapid prototypes, and finally to cast multilayer gelatin tissue phantoms. The gelatin base was enriched with additives to model the approximate chemistry and optical properties of individual tissue layers. Additional studies were performed to determine optimal casting conditions, phantom stability, layer delamination and chemical diffusion between layers. Recovery of diffuse reflectance and Raman spectra in tissue phantoms varied with probe placement. These phantoms enable optimization of probe placement for human or rat studies. These multilayer tissue phantoms with complex geometries are shown to be stable, with minimal layer delamination and chemical diffusion.

This study describes a basic theory for reconstructing pure Raman signals of materials composing a multilayer sample from Raman spectra obtained using two types of miniaturized Raman probes. An illustrative example is demonstrated using a multilayer system of samples composed of the transparent plastics polymethylmethacrylate (PMMA) and polyethylene (PE) as a model of thin-layered biomedical tissues. When the same region of an object is measured using Raman probes with different focal properties, the Raman spectra provide different depth profile information depending on the level of light penetration. Thus, a detailed comparison of the spectra can provide an interesting opportunity to probe the differences between the layers. A simple analytic form is presented for reconstructing the pure Raman spectra of the embedded layer. The method applies an understanding of the Raman sampling volume in layered transparent materials to the interpretation of Raman spectra experimentally measured by multiple probes. The basic theory described here is necessary for the expansion of the technique to turbid media, such as biological samples, where light-scattering effects must be considered. The potential applications of the proposed method include material and catalyst subsurface probing through different embedded materials, such as assessment of silicon wafers, effective noninvasive screening for catalyst synthesis, and biomedical tissue research.

Magnetic induction tomography (MIT) in vivo is to reconstruct conductivity of biomedical tissue by coil sensors which are imposed alternating current as well as detecting signals induced by tissue around the coils. In addition to the secondary signals due to tissue parameters, the resulting signals also include the primary field signals contributed by excitation coils which are approximately 5 times orders of the secondary signals. This not only reduces measurement precision, but also affects reconstruction image resolution. Optimization coil sensors can cancel primary field greatly at source. The paper presents coil sensors arrangement suitable for Biomedical magnetic induction tomography. Relative position between the excitation and detection coils was adjusted to reduce the primary signals in resulting signals. Simulation was performed from single-channel to multiple-channels system. The measurement results of all the systems suggest that the signal due to the primary field can be reduced individually at the operating frequency of 10Mz.

We report on the recently emerging (Laser) Light Sheet based Fluorescence Microscopy field (LSFM). The techniques used in this field allow to study and visualize biomedical objects non-destructively in high-resolution through virtual optical sectioning with sheets of laser light. Fluorescence originating in the cross section of the sheet and sample is recorded orthogonally with a camera. In this paper, the first implementation of LSFM to image biomedical tissue in three dimensions - Orthogonal-Plane Fluorescence Optical Sectioning microscopy (OPFOS) - is discussed. Since then many similar and derived methods have surfaced (SPIM, Ultramicroscopy, HR-OPFOS, mSPIM, DSLM, TSLIM...) which we all briefly discuss. All these optical sectioning methods create images showing histological detail. We illustrate the applicability of LSFM on several specimen types with application in biomedical and life sciences., Comment: 19 pages, 10 figures, to be published in Anatomical Research International (Hindawi)

Raman spectroscopy is a vibrational spectroscopic technique capable of optically probing biomolecular changes of tissue associated with neoplastic transformation, and has shown promise for the noninvasive, in vivo diagnosis and detection of epithelial precancer and cancer in various organs [1-3]. But analyzing Raman spectroscopic information emitted from tissue remains complicated for tissue diagnosis and characterization due to the reasons that the overall Raman signals acquired from the tissue surface usually contain a mixture of Raman information originating from different tissue depths [4, 5], while the changes of tissue morphology or biochemical constituents associated with disease transformation may be depth-dependent in biomedical systems [6]. For instance, the epithelial tissue usually consists of a superficial epithelium and an underlying stroma, the dysplasia-related changes (precancer) may be associated with the thickening of epithelial tissue, which results in the attenuation of the excitation light to penetrate into deeper areas of tissue and also the attenuation of Raman emission from deeper tissue regions (e.g., stroma) [7, 8]. On the other hand, the changes of other optical properties (e.g., absorption coefficient, scattering coefficient, anisotropic factor, refractive index) of tissue are also correlated with tissue physiologic/pathologic status, significantly affecting the overall Raman signal collection from biomedical tissue [9]. Hence, to better understand the origins of Raman signals collected from tissue surface for further improving the diagnosis of epithelial precancer or early cancer, it is highly desirable to develop a depth-resolved Raman spectroscopic technique for facilitating the wide applications of Raman spectroscopy in biomedical diagnosis. A number of fiber-optic probe designs have been reported for depth-resolved optical spectroscopic measurements, but most work are centered on fluorescence and reflectance spectroscopy for tissue diagnosis [10-15]. The depth-resolved fiber probe designs can mainly be classified into two types: (i) single-fiber probe in which the same fiber is used for both light excitation and reflectance/fluorescence/Raman collection, and (ii) multiple-fiber probe

A specialized transient digitizer system was developed for spectroscopic collection of fluorescence wavelength-time matrices (WTMs) from biological tissues. The system is compact, utilizes fiber optic probes for clinical compatibility, and offers rapid collection of high signal-to-noise ratio (>100) time- and wavelength- resolved fluorescence. The system is compatible with excitation sources operating in excess of 25 kHz. Wavelength-resolved measurement range is 300?800 nm with ≥ 0.01 nm steps. Time-resolved measurement depth is 128 ns with fixed 0.2 ns steps. The information-rich WTM data provides comprehensive fluorescence sensing capabilities, as demonstrated on tissue simulating phantoms. Extracting wavelength-resolved fluorophore lifetimes illustrates the potential of using the technology to resolve exogenous or endogenous fluorophore contributions in tissue samples in a clinical setting for tissue diagnostics and monitoring.

The motivation for this work is the improvement in discrimination between anomalous biological tissue vis-a-vis normal tissue. When ultrasonically visualizing tissue surrounding a cancerous portion it is useful for medical diagnosis when the portion has a different contrast in the image. The cancer tends to grow with its own direction typically different from normal tissue. Therefore, if we could ultrasonically visualize both isotropy and anisotropy of the tissue, the cancerous tissue may be discriminated from the normal tissue.

The signal and noise properties of standard time domain optical coherence tomography system are analyzed in near-infrared region based on extended Huygens-Fresnel principle. The signal-to-noise ratio and maximum probing depth are estimated for scattering media with discontinuity plane inside. In numerical simulation, the relationship between coherent signal and scattering coefficients, and depth dependence SNR are calculated. The difference between specular and diffuse reflection is given out and analyzed. Numerical result is verified by well established experiment with different concentration mixture solution of Intralipid TM , from 1% to 15%. The OCT system consists of fiber Michelson interferometer and 1550 nm ASE optical source with coherent length of 14μm. Both numerical and experimental results show that multiple scattering events are the main reason for decreasing of signal-to-noise ratio. According to the research, wavelength at 1550 nm is also suitable for imaging of biomedical tissue because of lower scattering coefficients. More than 2 mm penetration depth is obtained in experiment for 10% Intralipid TM which has scattering coefficient similar to skin tissue.

Spectral data for each pixel in a confocal spatial scan are acquired by mapping spectral slices into the time domain with an array of visible fiber Bragg gratings. Multispectral images of biomedical tissue can be generated in real time.

In this work, a prototype polyvinylidene fluoride (PVDF) palpation sensor has been developed. The sensor aims to measure stiffness, which is one of the information of biomedical tissue by palpation. The sensor is composed of two PVDF films, a silicone cylindrical column, and an aluminum cylinder. And the classification of hardness is concerned with the ratio of these PVDF outputs. In this paper, the output behavior of the palpation sensor was evaluated in detail by the experimental and numerical approach, and the suitable design to diagnose by the stiffness of tissue was investigated. Using the finite element analysis, the sensor output behavior was predicted. It is confirmed that the analysis is available for investigation of the dimension and the limitation of the sensor against the measuring object.

Fluorescence lifetime imaging microscopy is a technique in which the fluorescence lifetime(s) of a fluorophore is measured at each spatially resolvable element of a microscope image. Imaging of fluorescence lifetimes enables biochemical reactions to be followed at each microscopically resolvable location within the cell. FLIM has thus become very useful for biomedical tissue imaging. Global analysis [1] is a method of recovering fluorescence decay parameters from either time-resolved emission spectra to yield Decay-Associated Spectra [2], or equivalently, from FLIM datasets to yield Decay-Associated Images. Global analysis offers a sensitive and non-invasive probe of metabolic state of intracellular molecules such as NADH. Using prior information, such as the spatial invariance of the lifetime of each fluorescent species in the image, to better refine the relevant parameters, global analysis can recover lifetimes and amplitudes more accurately than traditional pixel-by-pixel analysis. Here, we explain a method to analyze FLIM data so that more accurate lifetimes and DAIs can be computed in a reasonable time. This approach involves coupling an iterative global analysis with linear algebraic operations. It can be successfully applied to image, e.g. metabolic states of live cardiac myocytes, etc.