Super-resolution fluorescence microscopy by line-scanning with an unmodified two-photon microscope.

Fluorescence-based microscopy as one of the standard tools in biomedical research benefits more and more from super-resolution methods, which offer enhanced spatial resolution allowing insights into new biological processes. A typical drawback of using these methods is the need for new, complex optical set-ups. This becomes even more significant when using two-photon fluorescence excitation, which offers deep tissue imaging and excellent z-sectioning. We show that the generation of striped-illumination patterns in two-photon laser scanning microscopy can readily be exploited for achieving optical super-resolution and contrast enhancement using open-source image reconstruction software. The special appeal of this approach is that even in the case of a commercial two-photon laser scanning microscope no optomechanical modifications are required to achieve this modality. Modifying the scanning software with a custom-written macro to address the scanning mirrors in combination with rapid intensity switching by an electro-optic modulator is sufficient to accomplish the acquisition of two-photon striped-illumination patterns on an sCMOS camera. We demonstrate and analyse the resulting resolution improvement by applying different recently published image resolution evaluation procedures to the reconstructed filtered widefield and super-resolved images. This article is part of the Theo Murphy meeting issue 'Super-resolution structured illumination microscopy (part 1)'.

Structured illumination microscopy and image scanning microscopy: a review and comparison of imaging properties.

Structured illumination microscopy and image scanning microscopy are two microscopical tech- niques, rapidly increasing in practical application, that can result in improvement in transverse spatial resolution, and/or improvement in axial imaging performance. The history and principles of these techniques are reviewed, and the imaging properties of the two methods compared. This article is part of the Theo Murphy meeting issue 'Super-resolution structured illumination microscopy (part 1)'.

Optical fiber-based dispersion for spectral discrimination in fluorescence lifetime imaging systems.

The excited state lifetime of a fluorophore together with its fluorescence emission spectrum provide information that can yield valuable insights into the nature of a fluorophore and its microenvironment. However, it is difficult to obtain both channels of information in a conventional scheme as detectors are typically configured either for spectral or lifetime detection. We present a fiber-based method to obtain spectral information from a multiphoton fluorescence lifetime imaging (FLIM) system. This is made possible using the time delay introduced in the fluorescence emission path by a dispersive optical fiber coupled to a detector operating in time-correlated single-photon counting mode. This add-on spectral implementation requires only a few simple modifications to any existing FLIM system and is considerably more cost-efficient compared to currently available spectral detectors.

Demonstration of flat-top beam illumination in widefield multiphoton microscopy.

Multiphoton microscopy provides a suitable technique for imaging biological tissues with submicrometer resolution. Usually a Gaussian beam (GB) is used for illumination, leading to a reduced power efficiency in the multiphoton response and vignetting for a square-shaped imaging area. A flat-top beam (FTB) provides a uniform spatial intensity distribution that equalizes the probability of a multiphoton effect across the imaging area. We employ a customized widefield multiphoton microscope to compare the performance of a square-shaped FTB illumination with that based on using a GB, for both two-photon fluorescence (TPF) and second-harmonic generation (SHG) imaging. The variation in signal-to-noise ratio across TPF images of fluorescent dyes spans ∼5.6 dB for the GB and ∼1.2 dB for the FTB illumination, respectively. For the GB modality, TPF images of mouse colon and Convallaria root, and SHG images of chicken tendon and human breast biopsy tissue showcase ∼20 % area that are not imaged due to either insufficient or lack of illumination. For quantitative analysis that depends on the illuminated area, this effect can potentially lead to inaccuracies. This work emphasizes the applicability of FTB illumination to multiphoton applications.

Bayesian hypothesis testing and experimental design for two-photon imaging data.

Variability, stochastic or otherwise, is a central feature of neural activity. Yet the means by which estimates of variation and uncertainty are derived from noisy observations of neural activity is often heuristic, with more weight given to numerical convenience than statistical rigour. For two-photon imaging data, composed of fundamentally probabilistic streams of photon detections, the problem is particularly acute. Here, we present a statistical pipeline for the inference and analysis of neural activity using Gaussian Process regression, applied to two-photon recordings of light-driven activity in ex vivo mouse retina. We demonstrate the flexibility and extensibility of these models, considering cases with non-stationary statistics, driven by complex parametric stimuli, in signal discrimination, hierarchical clustering and other inference tasks. Sparse approximation methods allow these models to be fitted rapidly, permitting them to actively guide the design of light stimulation in the midst of ongoing two-photon experiments.

DoGNet: A deep architecture for synapse detection in multiplexed fluorescence images.

Neuronal synapses transmit electrochemical signals between cells through the coordinated action of presynaptic vesicles, ion channels, scaffolding and adapter proteins, and membrane receptors. In situ structural characterization of numerous synaptic proteins simultaneously through multiplexed imaging facilitates a bottom-up approach to synapse classification and phenotypic description. Objective automation of efficient and reliable synapse detection within these datasets is essential for the high-throughput investigation of synaptic features. Convolutional neural networks can solve this generalized problem of synapse detection, however, these architectures require large numbers of training examples to optimize their thousands of parameters. We propose DoGNet, a neural network architecture that closes the gap between classical computer vision blob detectors, such as Difference of Gaussians (DoG) filters, and modern convolutional networks. DoGNet is optimized to analyze highly multiplexed microscopy data. Its small number of training parameters allows DoGNet to be trained with few examples, which facilitates its application to new datasets without overfitting. We evaluate the method on multiplexed fluorescence imaging data from both primary mouse neuronal cultures and mouse cortex tissue slices. We show that DoGNet outperforms convolutional networks with a low-to-moderate number of training examples, and DoGNet is efficiently transferred between datasets collected from separate research groups. DoGNet synapse localizations can then be used to guide the segmentation of individual synaptic protein locations and spatial extents, revealing their spatial organization and relative abundances within individual synapses. The source code is publicly available: https://github.com/kulikovv/dognet.

Spectral unmixing techniques for optoacoustic imaging of tissue pathophysiology.

A key feature of optoacoustic imaging is the ability to illuminate tissue at multiple wavelengths and therefore record images with a spectral dimension. While optoacoustic images at single wavelengths reveal morphological features, in analogy to ultrasound imaging or X-ray imaging, spectral imaging concedes sensing of intrinsic chromophores and externally administered agents that can reveal physiological, cellular and subcellular functions. Nevertheless, identification of spectral moieties within images obtained at multiple wavelengths requires spectral unmixing techniques, which present a unique mathematical problem given the three-dimensional nature of the optoacoustic images. Herein we discuss progress with spectral unmixing techniques developed for multispectral optoacoustic tomography. We explain how different techniques are required for accurate sensing of intrinsic tissue chromophores such as oxygenated and deoxygenated haemoglobin versus extrinsically administered photo-absorbing agents and nanoparticles. Finally, we review recent developments that allow accurate quantification of blood oxygen saturation (sO2) by transforming and solving the sO2 estimation problem from the spatial to the spectral domain.This article is part of the themed issue 'Challenges for chemistry in molecular imaging'.

[Frontiers in Live Bone Imaging Researches. Two-Photon Excitation Microscopy, principles and technologies].

The "two photon absorption" phenomenon had been predicted by the American Physicist, Maria Ghöppert-Mayer in 1931. Denk and Webb group had proved it in 1990 and the first product had been launched in the market in 1996. But ever since the product became available, the number of users are not increased. Moreover, the system had been too difficult to use and the system sometimes stay not working in labs. But recently, the new easier-to-use products are released and the ultra short pulse IR laser became stable. And its applications are extending from neuro-science to oncology or immunology fields. Due to these reasons, the shipment of multi-photon microscope in Japan in 2013 is approximately 40 units which is 3 times bigger than in 2010. In this paper, I would like to discuss the principles of two-photon microscopy and some of the new technologies for the higher signal capture efficiency.

Simple method to improve spatial resolution for in vivo two-photon fluorescence imaging.

There is a growing effort to image single neurons in vivo, and observe their individual contribution to the brain's functional organization. This effort generally relies on two-photon imaging to explore the structure and activity of cortical columns extending beneath the brain's surface. The need to protect living tissue, however, demands the introduction of coverslips and similar objects that can modify the optics of the imaging beam. This paper develops three-dimensional (3D) analytical and numerical models to characterize and correct for the resulting degradation of image quality. We have illustrated the use of these models by describing a simple, practical technique to reduce the effect of spherical aberration for in vivo two-photon fluorescence experiments.

Development of a doubly weighted Gerchberg-Saxton algorithm for use in multibeam imaging applications.

We report on the development of a doubly weighted Gerchberg-Saxton algorithm (DWGS) to enable generation of uniform beamlet arrays with a spatial light modulator (SLM) for use in multiphoton multifocal imaging applications. The algorithm incorporates the WGS algorithm as well as feedback of fluorescence signals from the sample measured with a single-photon avalanche diode (SPAD) detector array. This technique compensates for issues associated with nonuniform illumination onto the SLM, the effects due to aberrations and the variability in gain between detectors within the SPAD array to generate a uniformly illuminated multiphoton fluorescence image. We demonstrate the use of the DWGS with a number of beamlet array patterns to image muscle fibers of a 5-day-old fixed zebrafish larvae.

Quantitative evaluation of skeletal muscle defects in second harmonic generation images.

Skeletal muscle pathologies cause irregularities in the normally periodic organization of the myofibrils. Objective grading of muscle morphology is necessary to assess muscle health, compare biopsies, and evaluate treatments and the evolution of disease. To facilitate such quantitation, we have developed a fast, sensitive, automatic imaging analysis software. It detects major and minor morphological changes by combining texture features and Fourier transform (FT) techniques. We apply this tool to second harmonic generation (SHG) images of muscle fibers which visualize the repeating myosin bands. Texture features are then calculated by using a Haralick gray-level cooccurrence matrix in MATLAB. Two scores are retrieved from the texture correlation plot by using FT and curve-fitting methods. The sensitivity of the technique was tested on SHG images of human adult and infant muscle biopsies and of mouse muscle samples. The scores are strongly correlated to muscle fiber condition. We named the software MARS (muscle assessment and rating scores). It is executed automatically and is highly sensitive even to subtle defects. We propose MARS as a powerful and unbiased tool to assess muscle health.

Hyperspectral analysis using the correlation between image and reference.

We present the use of correlation analysis on spectral data in order to quantify the amount of a given spectrum present with respect to a reference spectrum. The method is shown to be useful in analyzing hyperspectral fluorescence images. It is unhindered by the linear relationship assumed in linear spectral unmixing, and in addition, it is shown to be robust with respect to noise.

Fast non-negative temporal deconvolution for laser scanning microscopy.

Laser scanning microscopy (LSM) is a common technique for high resolution fluorescent imaging. Here we describe a fast algorithm for non-negative deconvolution and apply it to readout of LSM detector photocurrents. By broadening photon impulses and deconvolving sampled photocurrent, effective quantum efficiency of the imaging system is increased. Using simulation and imaging with a custom-built two-photon microscope, we demonstrate improved fidelity of images acquired at short dwell times over a wide range of photon rates. Images formed show increased correlation-to-sample equivalent to a 25% increase in photon rate, lower noise, and reduced bleed-through compared to conventional image generation.

Spatiotemporal focusing-based widefield multiphoton microscopy for fast optical sectioning.

In this study, a microscope based on spatiotemporal focusing offering widefield multiphoton excitation has been developed to provide fast optical sectioning images. Key features of this microscope are the integrations of a 10 kHz repetition rate ultrafast amplifier featuring high instantaneous peak power (maximum 400 µJ/pulse at a 90 fs pulse width) and a TE-cooled, ultra-sensitive photon detecting, electron multiplying charge-coupled camera into a spatiotemporal focusing microscope. This configuration can produce multiphoton images with an excitation area larger than 200 × 100 µm² at a frame rate greater than 100 Hz (current maximum of 200 Hz). Brownian motions of fluorescent microbeads as small as 0.5 µm were observed in real-time with a lateral spatial resolution of less than 0.5 µm and an axial resolution of approximately 3.5 µm. Furthermore, second harmonic images of chicken tendons demonstrate that the developed widefield multiphoton microscope can provide high resolution z-sectioning for bioimaging.

Pupil-segmentation-based adaptive optical microscopy with full-pupil illumination.

Optical aberrations deteriorate the performance of microscopes. Adaptive optics can be used to improve imaging performance via wavefront shaping. Here, we demonstrate a pupil-segmentation based adaptive optical approach with full-pupil illumination. When implemented in a two-photon fluorescence microscope, it recovers diffraction-limited performance and improves imaging signal and resolution.

Two-photon microscopy of cortical NADH fluorescence intensity changes: correcting contamination from the hemodynamic response.

Quantification of nicotinamide adenine dinucleotide (NADH) changes during functional brain activation and pathological conditions provides critical insight into brain metabolism. Of the different imaging modalities, two-photon laser scanning microscopy (TPLSM) is becoming an important tool for cellular-resolution measurements of NADH changes associated with cellular metabolic changes. However, NADH fluorescence emission is strongly absorbed by hemoglobin. As a result, in vivo measurements are significantly affected by the hemodynamics associated with physiological and pathophysiological manipulations. We model NADH fluorescence excitation and emission in TPLSM imaging based on precise maps of cerebral microvasculature. The effects of hemoglobin optical absorption and optical scattering from red blood cells, changes in blood volume and hemoglobin oxygen saturation, vessel size, and location with respect to imaging location are explored. A simple technique for correcting the measured NADH fluorescence intensity changes is provided, with the utilization of a parallel measurement of a physiologically inert fluorophore. The model is applied to TPLSM measurements of NADH fluorescence intensity changes in rat somatosensory cortex during mild hypoxia and hyperoxia. The general approach of the correction algorithm can be extended to other TPLSM measurements, where changes in the optical properties of the tissue confound physiological measurements, such as the detection of calcium dynamics.

Imaging of normal and pathologic joint synovium using nonlinear optical microscopy as a potential diagnostic tool.

An estimated 1.3 million people in the United States suffer from rheumatoid arthritis (RA). RA causes profound changes in the synovial membrane of joints, and without early diagnosis and intervention, progresses to permanent alterations in joint structure and function. The purpose of this study is to determine if nonlinear optical microscopy (NLOM) can utilize the natural intrinsic fluorescence properties of tissue to generate images that would allow visualization of the structural and cellular composition of fresh, unfixed normal and pathologic synovial tissue. NLOM is performed on rabbit knee joint synovial samples using 730- and 800-nm excitation wavelengths. Less than 30 mW of excitation power delivered with a 40×, 0.8-NA water immersion objective is sufficient for the visualization of synovial structures to a maximum depth of 70 µm without tissue damage. NLOM imaging of normal and pathologic synovial tissue reveals the cellular structure, synoviocytes, adipocytes, collagen, vascular structures, and differential characteristics of inflammatory infiltrates without requiring tissue processing or staining. Further study to evaluate the ability of NLOM to assess the characteristics of pathologic synovial tissue and its potential role for the management of disease is warranted.

Toward surface quantification of liver fibrosis progression.

Monitoring liver fibrosis progression by liver biopsy is important for certain treatment decisions, but repeated biopsy is invasive. We envision redefinition or elimination of liver biopsy with surface scanning of the liver with minimally invasive optical methods. This would be possible only if the information contained on or near liver surfaces accurately reflects the liver fibrosis progression in the liver interior. In our study, we acquired the second-harmonic generation and two-photon excitation fluorescence microscopy images of liver tissues from bile duct-ligated rat model of liver fibrosis. We extracted morphology-based features, such as total collagen, collagen in bile duct areas, bile duct proliferation, and areas occupied by remnant hepatocytes, and defined the capsule and subcapsular regions on the liver surface based on image analysis of features. We discovered a strong correlation between the liver fibrosis progression on the anterior surface and interior in both liver lobes, where biopsy is typically obtained. The posterior surface exhibits less correlation with the rest of the liver. Therefore, scanning the anterior liver surface would obtain similar information to that obtained from biopsy for monitoring liver fibrosis progression.

A statistical model for multiphoton calcium imaging of the brain.

Multiphoton calcium fluorescence imaging has gained prominence as a valuable tool for the study of brain cells, but the corresponding analytical regimes remain rather naive. In this paper, we develop a statistical framework that facilitates principled quantitative analysis of multiphoton images. The proposed methods discriminate the stimulus-evoked response of a neuron from the background firing and image artifacts. We develop a harmonic regression model with colored noise, and estimate the model parameters with computationally efficient algorithms. We apply this model to in vivo characterization of cells from the ferret visual cortex. The results demonstrate substantially improved tuning curve fitting and image contrast.

Correlation of histology and linear and nonlinear microscopy of the living human cornea.

The morphology and the function of cellular and non-cellular structures in the living human cornea can be determined with modern correlative linear and nonlinear optical microscopic techniques and histology. Correlative microscopy is based on the use of different optical techniques to study the same specimen, ideally at the same location within the specimen, in order to increase the functional and/or morphological understanding of the specimen. A case study to assess the effect of overnight lid-closure on in vivo human corneal morphology is presented to illustrate correlative linear microscopy and optical low-coherence reflectometry. Nonlinear multiphoton excitation microscopy provides functional information on cellular metabolism based on the intrinsic fluorescence from the reduced pyridine nucleotides and the oxidized flavoproteins. Second-harmonic generation microscopy, a scattering process that does not deposit net energy into the tissue, provides structural information on corneal collagen organization. Molecular third-harmonic generation microscopy generates a signal in all materials and it an emerging technique. Coherent anti-Stokes Raman scattering microscopy provides chemical imaging for biology and medicine. The comparison and limitations of these microscopic modalities, linear and nonlinear microscopy applied to the cornea, and a review of some key findings is analyzed. A correlative integration and correlation of linear and nonlinear microscopies to study corneal function and structure is proposed to validate the clinical interpretation of microscopic images of the cornea.