Imaging Of Biological Tissues Research Articles

Periodic variations of intensity of diffraction orders in Raman-Nath diffraction

In acousto-optic imaging, the ultrasound-induced optical phase modulation has been widely used in the imaging of biological tissue. However, in Raman-Nath diffraction, the phase of diffracted light has not attracted much attention. Additionally, each order of diffraction has been simply treated as a plane light wave with optical phase shift, and the intensity of diffraction orders hence has been considered to be constant. Then, the phase shift is independent on the diffraction path of light wave in the acousto-optic interaction zone and the corresponding refractive index and the power of the ultrasound wave. Recently, we observe experimentally that the intensity of diffraction orders varies periodically with time. We hence study the periodic variations in depth. It is found that the diffracted light has an ultrasound-induced phase modulation and the periodic variations are due to the phase modulation.

Biomedical Photoacoustic Imaging With Unknown Spatially Distributed Ultrasound Sensor Array.

With the growth of interest in different medical study on biological function, non-invasive photoacoustic imaging of biological tissue attracts the interests for researchers. To eliminate the limited angle effect of photoacoustic imaging based on ultrasound linear array, spatially distributed ultrasound sensor array is applied. The accurate sensor array position determines the quality of the imaging results. In this study, we proposed three methods based on photoacoustic and ultrasound signals to enhance the imaging quality using a 256-element full-ring array. Groups of photoacoustic and ultrasound signals are used to regress the position of each element sensor. In phantom study and mouse brain study, photoacoustic imaging results can both yield details clearly with average error rate of less than 1% (50 [Formula: see text]). The performance of our three methods have proved that they can be potentially applied to other ultrasound-based medical imaging studies with unknown distributed positions of sensor array to enhance the imaging quality. The proposed methods can contribute to precise biomedical imaging with unknown distributed positions of sensor array in different application scenarios.

Develpoment and Characterization of Novel Probes for Photoacoustic Microscopy

The photoacoustic effect (PA) is a physical phenomenon based on the emission of sound waves following light absorption in material samples. The photon absorption and subsequent non-radiative depletion of the chromophores rapidly rises the temperature within the sample, increasing the pressure and inducing a thermoelastic expansion, leading to the emission of a pressure wave called photoacoustic wave. The reduced scattering of acoustic waves enables high-resolution, deeply penetrating imaging in biological tissues. The difference among the absorption coefficients of tissue components or suitable transgene labels in the sample gives the base of contrast in PA imaging but the few number of probes showing high PA efficiency reduces the applications to living systems and processes at the cellular and subcellular levels. The development of reversibly switchable fluorescent proteins (rsFPs) has revolutionized the life science imaging contributing to optical nanoscopy as agents able to improve contrast-to-noise ratio and spatial resolution. The competiveness between light and heating emission in rsFPs optimized for fluorescence imaging considerably reduces the acoustic emission efficiency making them not suitable for PA microscopy. The aim of this project is the development of a novel approach in photoacoustic microscopy inspired by the toolbox of knowledge we have for fluorescence imaging. The key point lies in the probes, belonging to two different families of photochromic proteins, which will be characterized and applied in the novel photoacoustic microscope: GAF3, and two new mutants of GFPs obtained adding a fluorescence-decreasing mutation to wildQ and wildQT proteins.

Object-dependent spatial resolution of the reflection-mode terahertz solid immersion microscopy.

Terahertz (THz) solid immersion microscopy is a novel promising THz imaging modality that overcomes the Abbe diffraction limit. In our prior work, an original reflection-mode THz solid immersion microscope system with the resolution of 0.15λ (in free space) was demonstrated and used for imaging of soft biological tissues. In this paper, a numerical analysis, using the finite-difference time-domain technique, and an experimental study, using a set of objects with distinct refractive indexes, were performed in order to uncover, for the first time, the object-dependent spatial resolution of the THz solid immersion microscopy. Our findings revealed that the system resolution remains strongly sub-wavelength 0.15-0.4λ for the wide range of sample refractive indices n = 1.0-5.0 and absorption coefficients α = 0-400 cm-1 (by power). Considering these findings, two distinct regimes of the THz solid immersion microscopy were identified. First is the total internal reflection regime that takes place when the sample refractive index is relatively low, while the sub-wavelength resolution is enabled by both the evanescent and ordinary reflected waves at the interface between a high-refractive-index material and an imaged object. Second is the ordinary reflection regime that occurs when the sample refractive index is high enough, so that there is no more total internal reflection at the interface, while only the ordinary reflected waves inside a high-refractive-index material are responsible for the sub-wavelength resolution. The resultant conclusions are general and can be applied for analysis of solid immersion lenses operating in other spectral ranges, such as visible and infrared, given linear nature of the Maxwell's equations.

A pH-responsive photoacoustic imaging probe for tumor pH imaging in vivo based on polyaniline–bovine serum albumin

Precise pH detection in tumors can guide the design of pH-responsive drugs and theranostic agents to improve treatment efficacy. However, most reported pH-responsive probes are fluorescent probes, for which in vivo application is limited by low probe penetration depth. In this study, a pH-responsive polyaniline–bovine serum albumin (BSA) probe was constructed for precise pH detection in tumors using photoacoustic imaging. The probe can be used to generate high-resolution images of deep biological tissues. The photoacoustic signal of the polyaniline–BSA probe exhibits a clear linear relationship with pH in the range of 5–6.8 both in vitro and in vivo, indicating that the probe is ideal for precise pH detection in most tumors. The polyaniline–BSA probe also exhibits satisfactory biocompatibility, low toxicity, fast response, and good reversibility. This work provides a useful in vivo pH detection probe for developing pH-responsive drugs and theranostic agents.

Improved accuracy of quantitative birefringence imaging by polarization sensitive OCT with simple noise correction and its application to neuroimaging.

Polarization-sensitive optical coherence tomography (PS-OCT) enables three-dimensional imaging of biological tissues based on the inherent contrast provided by scattering and polarization properties. In fibrous tissue such as the white matter of the brain, PS-OCT allows quantitative mapping of tissue birefringence. For the popular PS-OCT layout using a single circular input state, birefringence measurements are based on a straight-forward evaluation of phase retardation data. However, the accuracy of these measurements strongly depends on the signal-to-noise ratio (SNR) and is prone to mapping artifacts when the SNR is low. Here we present a simple yet effective approach for improving the accuracy of PS-OCT phase retardation and birefringence measurements. By performing a noise bias correction of the detected OCT signal amplitudes, the impact of the noise floor on retardation measurements can be markedly reduced. We present simulation data to illustrate the influence of the noise bias correction on phase retardation measurements and support our analysis with real-world PS-OCT image data.

Application of a Tissue Clearing Method for the Analysis of Dopaminergic Axonal Projections.

Parkinson's disease (PD) is a neurodegenerative disorder characterized with the progressive loss of dopaminergic (DA) neurons within the substantia nigra pars compacta (SNc). Quantitative analysis of neuronal loss including neuronal processes, axons and dendrites, would advance the understanding of the pathogenesis of PD. ScaleS, an aqueous tissue clearing method, provides stable tissue preservation while maintaining potent clearing capability, allowing quantitative three-dimensional (3D) imaging of biological tissues. In this chapter, we describe detailed procedures for 3D imaging of brain slice tissues with ScaleS technique. These include brain slice preparation, tissue clarification, chemical and immunohistochemical labeling (ChemScale and AbScale), and observation of labeled tissues using a confocal laser scanning microscope (CLSM).

Optical coherence tomography combined with convolutional neural networks analysis can differentiate between tumor and healthy liver parenchyma ex vivo

Purpose: Optical coherence tomography (OCT) is an imaging technology based on low-coherence interferometry which provides noninvasive, subsurface, high-resolution images of biological tissues. Potential clinical applications include intraoperative examination of resection margins or guidance of endoscopic biopsies, as a real-time adjunct to histological examination. In this study we investigated its ability to differentiate between healthy liver parenchyma and tumor ex vivo. Methods: Between June and August 2020, consecutive adult patients undergoing elective oncological liver surgery were included in this study. Fresh resection specimens were scanned ex vivo, before fixation in formalin, using a table-top OCT device at 1310nm wavelength. Scan dimensions were set at 3.0mm x 3.0mm x 2.5mm and 1024 x 1024 x 512 pixels, respectively. Scanned areas were excised and histologically examined separately. A pre-trained neural network (ResNet34) was used to match OCT-scans to their corresponding histological diagnoses, after splitting the dataset 70:30 into training and test data. The study was approved by the local ethics committee. Results: A total of 51 scans (comprising 50,176 images) were obtained from 19 patients, of which 18 (17,408 images) were of normal liver parenchyma and 33 (32,768 images) of tumor. The neural network analysis distinguished tumor from healthy liver parenchyma with a sensitivity and specificity of 92% and 87%, respectively. Conclusion: Optical coherence tomography combined with convolutional neural networks can distinguish between healthy and cancerous liver tissues with great accuracy ex vivo. Further studies are needed to improve upon these results and develop in vivo diagnostic technologies.

Employment of image oversampling and downsampling techniques for improving grayscale resolution

In multispectral transmission imaging of biological tissues, it is crucial to increase the grayscale resolution for accurate heterogeneity detection. This study proposes a method of obtaining high-grayscale-resolution images via image oversampling and downsampling. A single-wavelength transmission image of a simulated heterogeneous breast tissue was used to validate the effectiveness of the method experimentally. In the experiment, a high-resolution camera was used to capture transmission images of the simulated tissue with high spatial resolution $${\text{I}}_{\lambda }^{h}$$ and low spatial resolution $${\text{I}}_{\lambda }^{l}$$ . The high-spatial-resolution image $${\text{I}}_{\lambda }^{h}$$ was compressed into an image $${\text{I}}_{\lambda }^{hc}$$ with the same spatial resolution as that of the low-spatial-resolution image $${\text{I}}_{\lambda }^{l}$$ , thereby converting the spatial information into image depth information. The experimental results indicate that the compressed image $${\text{I}}_{\lambda }^{hc}$$ had higher grayscale resolution and richer grayscale details than those of the low-spatial-resolution image $${\text{I}}_{\lambda }^{l}$$ . Our results prove that it is feasible to improve the grayscale resolution of an image through image oversampling and downsampling while sacrificing the image spatial resolution to a certain extent. Further, this research provides an effective means to analyze heterogeneity in multispectral transmission imaging of a biological tissue.

A Spectroscopic Diffuse Optical Tomography System for the Continuous 3-D Functional Imaging of Tissue—A Phantom Study

This article demonstrates a spectroscopic diffuse optical tomography (DOT) system for the noninvasive continuous imaging of tissue. The system was built on an embedded system architecture along with an algorithm that performs entire system control, data acquisition, noise-free lock-in detection, and wireless data transmission to a host computer, equipped with a graphics processing unit (GPU). The GPU system executes a fast 3-D DOT spectroscopic image reconstruction algorithm. The algorithm computes Jacobians and solves four different depth-sensitive inverse problems of image reconstruction. The host computer sends commands to the DOT server system and collects data, and simultaneously performs high-speed 3-D spectroscopic image reconstruction to display images in real-time. We designed a configurable optical fiber patch to collect depth-resolved diffused light exiting the imaging media by placing the patch on the surface. The simulation and experimental results from two setups showed the spectroscopic imaging capability of the system to map the concentration of oxyhemoglobin, deoxyhemoglobin, and water, and to characterize the tumor located deep inside the tissue. The proposed system uses low-cost LEDs, photodiode detectors, embedded system, and algorithms to perform high-speed 3-D functional imaging and can be further miniaturized. Our promising results pave the way for the development of a low-cost hand-held spectroscopic DOT system for the real-time onsite functional imaging of biological tissue.

Recent advances in photoacoustic tomography.

Photoacoustic tomography (PAT) that integrates the molecular contrast of optical imaging with the high spatial resolution of ultrasound imaging in deep tissue has widespread applications in basic biological science, preclinical research and clinical trials. Recently, tremendous progress has been made in PAT regarding technical innovations, preclinical applications, and clinical translations. Here, we selectively review the recent progresses and advances in PAT, including the development of advanced PAT systems for small-animal and human imaging, newly engineered optical probes for molecular imaging, broad-spectrum PAT for label-free imaging of biological tissues, high-throughput snapshot photoacoustic topography, and integration of machine learning for image reconstruction and processing. We envision that PAT will have further technical developments and more impactful applications in biomedicine.

基于焦平面阵列的连续太赫兹波生物组织成像技术研究

基于焦平面阵列的连续太赫兹波生物组织成像技术研究

On fluorescence imaging: The diffusion equation model and recovery of the absorption coefficient of fluorophores

To quantify fluorescence imaging of biological tissues, we need to solve an inverse problem for the coupled radiative transfer equations which describe the excitation and emission fields in biological tissues. We begin by giving a concise mathematical argument to derive coupled diffusion equations with the Robin boundary condition as an approximation of the radiative transfer system. Then by using this coupled system of equations as a model for the fluorescence imaging, we have a nonlinear inverse problem to identify the absorption coefficient in this system. The associated linearized inverse problem is to ignore the absorbing effect on the excitation field. We firstly establish the estimates of errors on the excitation field and the solution to the inverse problem, which ensures the reasonability of the model approximation quantitatively. Some numerical verification is presented to show the validity of such a linearizing process quantitatively. Then, based on the analytic expressions of excitation and emission fields, the identifiability of the absorption coefficient from the linearized inverse problem is rigorously analyzed for the absorption coefficient in the special form, revealing the physical difficulty of the 3-dimensional imaging model by the back scattering diffusive system.

Continuous-Wave THz Imaging for Biomedical Samples

In the past few decades, the applications of terahertz (THz) spectroscopy and imaging technology have seen significant developments in the fields of biology, medical diagnosis, food safety, and nondestructive testing. Label-free diagnosis of malignant tumours has been obtained and also achieved significant development in THz biomedical imaging. This review mainly presents the research status and prospects of several common continuous-wave (CW) THz medical imaging systems and applications of THz medical imaging in biological tissues. Here, we first introduce the properties of THz waves and how these properties play a role in biomedical imaging. Then, we analyse both the advantages and disadvantages of the CW THz imaging methods and the progress of these methods in THz biomedical imaging in recent ten years. Finally, we summarise the obstacles in the way of the application of THz bio-imaging application technology in clinical detection, which need to be investigated and overcome in the future.

Squirrel search algorithm optimization for imaging through scattering media using gradient structural similarity

A wave-front shaping optimization algorithm is proposed to image through scattering media with higher accuracy. Pearson correlation coefficient (PCC), structural similarity (SSIM), and gradient structural similarity (GSSIM) are introduced as the loss functions to recover images. We have concluded that GSSIM has the optimal detail recovery performance among complex multivalued targets, followed by SSIM and PCC. To find the optimal phase mask, we propose the squirrel search algorithm and compared it with two classical global optimization algorithms including the genetic algorithm, the simulated annealing algorithm, and the commonly used continuous sequence algorithm. The simulation and experimental results show that the proposed squirrel search algorithm has a faster convergence speed and higher robustness and stability, which indicates an improved reconstruction quality. This algorithm will help realize imaging through scattering media better and quicker, which is meaningful in dynamic biological tissue imaging and related fields such as optical detection.

Sample preparation for energy dispersive X-ray imaging of biological tissues.

Traditional electron microscopy (EM) can be complemented with analytical EM to increase objective sample information enabling feature identification. Energy dispersive X-ray (EDX) imaging provides semi-quantitative elemental composition of the sample with high spatial resolution (~10nm) in ultrathin sections. However, EDX imaging of biological samples is still challenging as a routine method because many elements are at the detection limit for this technique. Moreover, samples undergo extensive preparation before analysis, which can introduce disruptive X-ray cross-talk or artifacts. EDX data can, for instance, be skewed by (i) osmium interference with endogenous phosphorus, (ii) chlorine present in EPON-embedded tissues, (iii) lead interference with endogenous sulfur, and (iv) potential spectral overlaps with grid material, contrast agents, and the in-microscope sample holder. Here, we highlight how to circumvent these potential pitfalls and outline how we approach sample preparation and analysis for detection of different elements of interest. Utilization of well-considered a priori sample preparation techniques will best ensure conclusive EDX experiments.

Direct Tissue Mass Spectrometry Imaging by Atmospheric Pressure UV-Laser Desorption Plasma Postionization.

Matrix-assisted laser desorption ionization (MALDI) operated at atmospheric pressure has been shown to be a promising technique for mass spectrometry imaging of biological tissues at high spatial resolution. Recent studies have shown several orders of magnitude improvement in sensitivity afforded by coupling with a low-temperature plasma (LTP) for postionization. In this work we report the first results from "matrix-free" imaging using our atmospheric pressure (AP) transmission mode (TM) (MA)LDI source with LTP postionization. Direct MSI analysis of murine testis with no sample preparation after tissue sectioning enabled imaging of a range of lipid classes at pixel sizes of 25 μm. We compared results from the matrix-free methods with MALDI experiments in which the matrix was applied on top, underneath, or layered as a sandwich. The sandwich preparation was found to lead to ion yields approximately 2- or 3-fold higher than the other methods, indicating that the addition of a light absorbing matrix remains beneficial. Nonetheless, LDI methods confer a range of advantages, and the sensitivity improvements provided by postionization strategies are a promising step toward high-efficiency laser sampling under ambient conditions.

Linear diattenuation imaging of biological tissues with near infrared Mueller scanning microscopy.

Among the multitude of optical polarization contrasts that can be observed in complex biological specimens, linear diattenuation (LD) imaging has received little attention. It is indeed challenging to image LD with basic polarizing microscopes because it is often relatively small in comparison with linear retardance (LR). In addition, interpretation of LD images is not straightforward when experiments are conducted in the visible range because LD can be produced by both dichroism and anisotropic scattering. Mueller polarimetry is a powerful implementation of polarization sensing able to differentiate and measure the anisotropies of specimens. In this article, near infrared transmission Mueller scanning microscopy is used to image LD in thin biological specimen sections made of various proteins with unprecedented resolution and sensitivity. The near infrared spectral range makes it possible to lower the contribution of dichroism to the total linear diattenuation in order to highlight anisotropic scattering. Pixel-by-pixel comparison of LD images with LR and multiphoton images demonstrates that LD is produced by under-resolved structures that are not revealed by other means, notably within the sarcomere of skeletal muscles. LD microscopy appears as a powerful tool to provide new insights into the macro-molecular organization of biological specimens at the sub-microscopic scale without labelling.

Simultaneous imaging of hard and soft biological tissues in a low-field dental MRI scanner

Magnetic Resonance Imaging (MRI) of hard biological tissues is challenging due to the fleeting lifetime and low strength of their response to resonant stimuli, especially at low magnetic fields. Consequently, the impact of MRI on some medical applications, such as dentistry, continues to be limited. Here, we present three-dimensional reconstructions of ex-vivo human teeth, as well as a rabbit head and part of a cow femur, all obtained at a field strength of 260 mT. These images are the first featuring soft and hard tissues simultaneously at sub-Tesla fields, and they have been acquired in a home-made, special-purpose, pre-medical MRI scanner designed with the goal of demonstrating dental imaging at low field settings. We encode spatial information with two pulse sequences: Pointwise-Encoding Time reduction with Radial Acquisition and a new sequence we have called Double Radial Non-Stop Spin Echo, which we find to perform better than the former. For image reconstruction we employ Algebraic Reconstruction Techniques (ART) as well as standard Fourier methods. An analysis of the resulting images shows that ART reconstructions exhibit a higher signal-to-noise ratio with a more homogeneous noise distribution.

Autoencoder based blind source separation for photoacoustic resolution enhancement

Photoacoustics is a promising technique for in-depth imaging of biological tissues. However, the lateral resolution of photoacoustic imaging is limited by size of the optical excitation spot, and therefore by light diffraction and scattering. Several super-resolution approaches, among which methods based on localization of labels and particles, have been suggested, presenting promising but limited solutions. This work demonstrates a novel concept for extended-resolution imaging based on separation and localization of multiple sub-pixel absorbers, each characterized by a distinct acoustic response. Sparse autoencoder algorithm is used to blindly decompose the acoustic signal into its various sources and resolve sub-pixel features. This method can be used independently or as a combination with other super-resolution techniques to gain further resolution enhancement and may also be extended to other imaging schemes. In this paper, the general idea is presented in details and experimentally demonstrated.