Dynamic imaging of zebrafish heart with multi-planar light sheet microscopy

Light sheet fluorescence microscopy has become a research hotspot in biomedicine because of low phototoxicity, high speed, and high resolution. However, the conventional methods to acquire three-dimensional spatial information are mainly based on scanning, which inevitably increases photodamage and is not real-time. Here, we propose a method to generate controllable multi-planar illumination with a dielectric isosceles triangular array and a design of multi-planar light sheet fluorescence microscopy system. We carry out experiments of three-dimensional illumination beam measurement, volumetric imaging of fluorescent microspheres, and dynamic in vivo imaging of zebrafish heart to evaluate the performance of this system. In addition, we apply this system to study the effects of bisphenol fluorene on the heart shape and heart-beating rate of zebrafish. Our experiment results indicate that the multi-planar light sheet microscopy system provides a novel and feasible method for three-dimensional selected plane imaging and low-phototoxicity in vivo imaging.     

Structured illumination imaging with quasi‐periodic patterns

Structured illumination microscopy (SIM) is a well‐established method for optical sectioning and super‐resolution. The core of structured illumination is using a periodic pattern to excite image signals. This work reports a method for estimating minor pattern distortions from the raw image data and correcting these distortions during SIM image processing. The method was tested with both simulated and experimental image data from two‐photon Bessel light‐sheet SIM. The results proves the method is effective in challenging situations, where strong scattering background exists, signal‐to‐noise ratio (SNR) is low and the sample structure is sparse. Experimental results demonstrate restoring synaptic structures in deep brain tissue, despite the presence of strong light scattering and tissue‐induced SIM pattern distortion.     

Optical coherence hyperspectral microscopy with a single supercontinuum light source

In the paper, we have developed an optical coherence hyperspectral microscopy with a single supercontinuum light source. The microscopy consists of optical coherence tomography (OCT) and hyperspectral imaging (HSI), which can visualize the structural and functional characteristics of biological tissues. The 500 to 700 nm band is selected for HSI and OCT imaging, where HSI enables imaging of oxygen saturation and hemoglobin (Hb) content, while OCT acquires structural characteristics to assess the morphology of biological tissues. The system performance of the optical coherence hyperspectral microscopy is verified by normal mice ears, and the practical applications of the microscopy is further performed in 4T1 and inflammation Balb/c mice ears in vivo. The experimental results demonstrate that the microscopy has potential to provide complementary information for clinical applications.     

Reduction in required volume of imaging data and image reconstruction time for adaptive-illumination Fourier ptychographic microscopy

Fourier ptychographic microscopy (FPM) is a promising super-resolution computational imaging technology. It stitches a series of low-resolution (LR) images in the Fourier domain by an iterative method. Thus, it obtains a large field of view and high-resolution quantitative phase images. Owing to its capability to perform high-spatial bandwidth product imaging, FPM is widely used in the reconstruction of conventional static samples. However, the influence of the FPM imaging mechanism limits its application in high-speed dynamic imaging. To solve this problem, an adaptive-illumination FPM scheme using regional energy estimation is proposed. Starting with several captured real LR images, the energy distribution of all LR images is estimated, and select the measurement images with large information to perform FPM reconstruction. Simulation and experimental results show that the method produces efficient imaging performance and reduces the required volume of data to more than 65% while ensuring the quality of FPM reconstruction.     

Fast and sensitive delineation of brain tumor with clinically compatible moxifloxacin labeling and confocal microscopy

Delineation of brain tumor margins during surgery is critical to maximize tumor removal while preserving normal brain tissue to obtain optimal clinical outcomes. Although various imaging methods have been developed, they have limitations to be used in clinical practice. We developed a high‐speed cellular imaging method by using clinically compatible moxifloxacin and confocal microscopy for sensitive brain tumor detection and delineation. Moxifloxacin is a Food and Drug Administration (FDA) approved antibiotic and was used as a cell labeling agent through topical administration. Its strong fluorescence at short visible excitation wavelengths allowed video‐rate cellular imaging. Moxifloxacin‐based confocal microscopy (MBCM) was characterized in normal mouse brain specimens and visualized their cytoarchitecture clearly. Then, MBCM was applied to both brain tumor murine models and two malignant human brain tumors of glioblastoma and metastatic cancer. MBCM detected tumors in all the specimens by visualizing dense and irregular cell distributions, and tumor margins were easily delineated based on the cytoarchitecture. An image analysis method was developed for automated detection and delineation. MBCM demonstrated sensitive delineation of brain tumors through cytoarchitecture visualization and would have potentials for human applications, such as a surgery‐guiding method for tumor removal.      

Fast denoising and lossless spectrum extraction in stimulated Raman scattering microscopy

Stimulated Raman scattering (SRS) microscopy is a nonlinear optical imaging method for visualizing chemical content based on molecular vibrational bonds. However, the imaging speed and sensitivity are currently limited by the noise of the light beam probing the Raman process. In this paper, we present a fast non-average denoising and high-precision Raman shift extraction method, based on a self-reinforcing signal-to-noise ratio (SNR) enhancement algorithm, for SRS spectroscopy and microscopy. We compare the results of this method with the filtering methods and the reported experimental methods to demonstrate its high efficiency and high precision in spectral denoising, Raman peak extraction and image quality improvement. We demonstrate a maximum SNR enhancement of 10.3 dB in fixed tissue imaging and 11.9 dB in vivo imaging. This method reduces the cost and complexity of the SRS system and allows for high-quality SRS imaging without use of special laser, complicated system design and Raman tags.     

Lightsheet fluorescence lifetime imaging microscopy with wide‐field time‐correlated single photon counting

We report on wide‐field time‐correlated single photon counting (TCSPC)‐based fluorescence lifetime imaging microscopy (FLIM) with lightsheet illumination. A pulsed diode laser is used for excitation, and a crossed delay line anode image intensifier, effectively a single‐photon sensitive camera, is used to record the position and arrival time of the photons with picosecond time resolution, combining low illumination intensity of microwatts with wide‐field data collection. We pair this detector with the lightsheet illumination technique, and apply it to 3D FLIM imaging of dye gradients in human cancer cell spheroids, and C. elegans.     

Structured illumination microscopy with interleaved reconstruction (SIMILR)

Structured illumination microscopy (SIM) is the commonly used super‐resolution (SR) technique for imaging subcellular dynamics. However, due to its need for multiple illumination patterns, the frame rate is just a fraction of that of conventional microscopy and is thus too slow for fast dynamic studies. A new SR image reconstruction method that maximizes the use of each subframe of the acquisition series is proposed for improving the super‐resolved frame rate by N times for N illumination directions. The method requires no changes in raw data and is appropriate for many versions of SIM setup, including those implementing fast illumination pattern generation mechanism based on spatial light modulator or digital micromirror device. The performance of the proposed method is demonstrated through imaging the highly dynamic endoplasmic reticulum where continuous rapid growths or shape changes of tiny structures are observed.      

Epi-illumination dark-field microscopy enables direct visualization of unlabeled small organisms with high spatial and temporal resolution

Dark-field microscopy is known to offer both high resolution and direct visualization of thin samples. However, its performance and optimization on thick samples is under-explored and so far, only meso-scale information from whole organisms has been demonstrated. In this work, we carefully investigate the difference between trans- and epi-illumination configurations. Our findings suggest that the epi-illumination configuration is superior in both contrast and fidelity compared to trans-illumination, while having the added advantage of experimental simplicity and an “open top” for experimental intervention. Guided by the theoretical analysis, we constructed an epi-illumination dark-field microscope with measured lateral and axial resolutions of 260 nm and 520 nm, respectively. Subcellular structures in whole organisms were directly visualized without the need for image reconstruction, and further confirmed via simultaneous fluorescence imaging. With an imaging speed of 20 to 50 fps, we visualize fast dynamic processes such as cell division and pharyngeal pumping in Caenorhabditis elegans.     

Acoustic resolution photoacoustic microscopy based on microelectromechanical systems scanner

Photoacoustic microscopy (PAM) can be classified as optical resolution (OR)‐PAM and acoustic resolution (AR)‐PAM depending on the type of resolution achieved. Using microelectromechanical systems (MEMS) scanner, high‐speed OR‐PAM system was developed earlier. Depth of imaging limits the use of OR‐PAM technology for many preclinical and clinical imaging applications. Here, we demonstrate the use of a high‐speed MEMS scanner for AR‐PAM imaging. Lateral resolution of 84 μm and an axial resolution of 27 μm with ~2.7 mm imaging depth was achieved using a 50 MHz transducer‐based AR‐PAM system. Use of a higher frequency transducer at 75 MHz has further improved the resolution characteristics of the system with a reduction in imaging depth and a lateral resolution of 53 μm and an axial resolution of 18 μm with ~1.8 mm imaging depth was achieved. Using the two‐axis MEMS scanner a 2 × 2 .5 mm² area was imaged in 3 seconds. The capability of achieving acoustic resolution images using the MEMS scanner makes it beneficial for the development of high‐speed miniaturized systems for deeper tissue imaging.      

Inside Cover: Efficient and cost‐effective 3D cellular imaging by sub‐voxel‐resolving light‐sheet add‐on microscopy

A type of compact and cost‐effective light‐sheet imaging device, termed sub‐voxel‐resolving light‐sheet add‐on module (SLAM), is developed to cooperate with conventional 2D epifluorescence microscope, allowing high‐contrast, resolution‐improved 3D imaging of various biological samples at high throughput. Further details can be found in the article by Fang Zhao, Yicong Yang, Yi Li, et al. ( e201960243 ).

     

Enhanced spatial resolution for snapshot hyperspectral imaging of blood perfusion and melanin information within human tissue

We report a reconstruction method to achieve high spatial resolution for hyperspectral imaging of chromophore features in skin in vivo. The method utilizes an established structure‐adaptive normalized convolution algorithm to reconstruct high spatial resolution of hyperspectral images from snapshot low‐resolution hyperspectral image sequences captured by a snapshot spectral camera. The reconstructed images at chromophore‐sensitive wavebands are used to map the skin features of interest. We demonstrate the method experimentally by mapping the blood perfusion and melanin features (moles) on the facial skin. The method relaxes the constrains of the relatively low spatial resolution in the snapshot hyperspectral camera, making it more usable in imaging applications.     

Double-flow convolutional neural network for rapid large field of view Fourier ptychographic reconstruction

Fourier ptychographic microscopy is a promising imaging technique which can circumvent the space-bandwidth product of the system and achieve a reconstruction result with wide field-of-view (FOV), high-resolution and quantitative phase information. However, traditional iterative-based methods typically require multiple times to get convergence, and due to the wave vector deviation in different areas, the millimeter-level full-FOV cannot be well reconstructed once and typically required to be separated into several portions with sufficient overlaps and reconstructed separately, which makes traditional methods suffer from long reconstruction time for a large-FOV (of the order of minutes) and limits the application in real-time large-FOV monitoring of live sample in vitro. Here we propose a novel deep-learning based method called DFNN which can be used in place of traditional iterative-based methods to increase the quality of single large-FOV reconstruction and reducing the processing time from 167.5 to 0.1125 second. In addition, we demonstrate that by training based on the simulation dataset with high-entropy property (Opt. Express 28, 24 152 [2020]), DFNN could has fine generalizability and little dependence on the morphological features of samples. The superior robustness of DFNN against noise is also demonstrated in both simulation and experiment. Furthermore, our model shows more robustness against the wave vector deviation. Therefore, we could achieve better results at the edge areas of a single large-FOV reconstruction. Our method demonstrates a promising way to perform real-time single large-FOV reconstructions and provides further possibilities for real-time large-FOV monitoring of live samples with sub-cellular resolution.     

Wide‐field monitoring and real‐time local recording of microvascular networks on small animals with a dual‐raster‐scanned photoacoustic microscope

Photoacoustic microscopy (PAM) provides a new method for the imaging of small‐animals with high‐contrast and deep‐penetration. However, the established PAM systems have suffered from a limited field‐of‐view or imaging speed, which are difficult to both monitor wide‐field activity of organ and record real‐time change of local tissue. Here, we reported a dual‐raster‐scanned photoacoustic microscope (DRS‐PAM) that integrates a two‐dimensional motorized translation stage for large field‐of‐view imaging and a two‐axis fast galvanometer scanner for real‐time imaging. The DRS‐PAM provides a flexible transition from wide‐field monitoring the vasculature of organs to real‐time imaging of local dynamics. To test the performance of DRS‐PAM, clear characterization of angiogenesis and functional detail was illustrated, hemodynamic activities of vasculature in cerebral cortex of a mouse were investigated. Furthermore, response of tumor to treatment were successfully monitored during treatment. The experimental results demonstrate the DRS‐PAM holds the great potential for biomedical research of basic biology.     

Integrated photoacoustic and hyperspectral dual‐modality microscopy for co‐imaging of melanoma and cutaneous squamous cell carcinoma in vivo

Skin carcinoma such as melanoma (MM) and cutaneous squamous cell carcinoma (cSCC) are considered as the highest mortality and the most aggressive skin cancers in dermatology. In view that early diagnosis and treatment can greatly improve the survival rate and life quality of the patients, developing noninvasive and effective evaluation methods is of great significance for the detection and identification of early stage cutaneous cancers. In this article, we propose a hybrid photoacoustic and hyperspectral dual‐modality microscopy to evaluate and differentiate skin carcinoma by structural and multiphysiological parameters. The proposed system's imaging abilities are verified by mimic phantoms and normal mice experiments. Furthermore, in vivo characterization and evaluation results of MM and cSCC mice are obtained successfully, which prove this novel method could be used as a reliable and useful method for skin cancer detection in early stages.     

Low-power compact continuous-wave stimulated emission depletion microscopy

Stimulated emission depletion (STED) microscopy can break the optical diffraction barrier and provide subdiffraction resolution. According to the STED superresolution imaging principle, the resolution of STED is positively related to the power of the depletion laser. However, high-laser power largely limits the study of living cells or living bodies. Moreover, the high complexity and high cost of conventional pulsed STED microscopy limit the application of this technique. Therefore, this paper describes a simple continuous-wave STED (CW-STED) system constructed on a 45 × 60 cm breadboard and combined with digitally enhanced (DE) technology; low-power superresolution imaging is realized, which has the advantages of reducing system complexity and cost. The low-system complexity, low cost, and low-power superresolution imaging features of CW-STED have great potential to advance the application of STED microscopy in biological research.     

Deep learning protocol for improved photoacoustic brain imaging

One of the key limitations for the clinical translation of photoacoustic imaging is penetration depth that is linked to the tissue maximum permissible exposures (MPE) recommended by the American National Standards Institute (ANSI). Here, we propose a method based on deep learning to virtually increase the MPE in order to enhance the signal‐to‐noise ratio of deep structures in the brain tissue. The proposed method is evaluated in an in vivo sheep brain imaging experiment. We believe this method can facilitate clinical translation of photoacoustic technique in brain imaging, especially in transfontanelle brain imaging in neonates.     

Dissolving microneedles containing aminolevulinic acid improves protoporphyrin IX distribution

One important limitation of topical photodynamic therapy (PDT) is the limited tissue penetration of precursors. Microneedles (MNs) are minimally invasive devices used to promote intradermal drug delivery. Dissolving MNs contain drug-associated to polymer blends, dissolving after insertion into skin, allowing drug release. This study comprises development and characterization of a pyramidal model of dissolving MNs (500 μm) prepared with 5% wt/wt aminolevulinic acid and 20% wt/wt Gantrez AN-139 in aqueous blend. Protoporphyrin IX formation and distribution were evaluated in tumor mice model by using fluorescence widefield imaging, spectroscopy, and confocal microscopy. MNs demonstrated excellent mechanical resistance penetrating about 250 μm with minor size alteration in vitro, and fluorescence intensity was 5-times higher at 0.5 mm on average compared to cream in vivo (being 10 ± 5 a.u. for MNs and 2.4 ± 0.8 a.u. for cream). Dissolving MNs have overcome topical cream application, being extremely promising especially for thicker skin lesions treatment using PDT.     

Near-infrared double-illumination optical-resolution photoacoustic microscopy

Label-free chemical bond imaging is of great importance in biology and medicine. Photoacoustic imaging at the third near-infrared windows (1600-1870 nm, near-infrared-III) provides a stable molecular vibrational imaging tool for lipid-rich tissue owing to the first overtone transition of the C H bond at 1.7 μm. However, lacking high-energy pulsed laser sources at 1.7 μm and the strong water absorption significantly limit the signal-to-noise ratio of the lipid imaging, especially for thin lipid tissues. To circumvent this barrier, we develop near-infrared-III double-illumination optical-resolution photoacoustic microscopy (DIOR-PAM) for improving the sensitivity of label-free lipid imaging. Using the same laser, DIOR-PAM can enhance the sensitivity by nearly 100%, which we prove in the Monte Carlo simulation. We experimentally demonstrated 50% ~ 100% sensitivity enhancements on nonbiological and biological lipid-rich samples.     

DeconvTest: Simulation framework for quantifying errors and selecting optimal parameters of image deconvolution

Deconvolution is an essential step of image processing that aims to compensate for the image blur caused by the microscope's point spread function. With many existing deconvolution methods, it is challenging to choose the method and its parameters most appropriate for particular image data at hand. To facilitate this task, we developed DeconvTest: an open‐source Python‐based framework for generating synthetic microscopy images, deconvolving them with different algorithms, and quantifying reconstruction errors. In contrast to existing software, DeconvTest combines all components required to analyze deconvolution performance in a systematic, high‐throughput and quantitative manner. We demonstrate the power of the framework by using it to identify the optimal deconvolution settings for synthetic and real image data. Based on this, we provide a guideline for (a) choosing optimal values of deconvolution parameters for image data at hand and (b) optimizing imaging conditions for best results in combination with subsequent image deconvolution.