Ultra-parallel label-free optophysiology of neural activity.

The electrical activity of neurons has a spatiotemporal footprint that spans three orders of magnitude. Traditional electrophysiology lacks the spatial throughput to image the activity of an entire neural network; besides, labeled optical imaging using voltage-sensitive dyes and tracking Ca2+ ion dynamics lack the versatility and speed to capture fast-spiking activity, respectively. We present a label-free optical imaging technique to image the changes to the optical path length and the local birefringence caused by neural activity, at 4,000 Hz, across a 200 × 200 µm2 region, and with micron-scale spatial resolution and 300-pm displacement sensitivity using Superfast Polarization-sensitive Off-axis Full-field Optical Coherence Microscopy (SPoOF OCM). The undulations in the optical responses from mammalian neuronal activity were matched with field-potential electrophysiology measurements and validated with channel blockers. By directly tracking the widefield neural activity at millisecond timescales and micrometer resolution, SPoOF OCM provides a framework to progress from low-throughput electrophysiology to high-throughput ultra-parallel label-free optophysiology.

Simultaneous two-photon activation and imaging of neural activity based on spectral-temporal modulation of supercontinuum light.

SIGNIFICANCE: Recent advances in nonlinear optics in neuroscience have focused on using two ultrafast lasers for activity imaging and optogenetic stimulation. Broadband femtosecond light sources can obviate the need for multiple lasers by spectral separation for chromatically targeted excitation. AIM: We present a photonic crystal fiber (PCF)-based supercontinuum source for spectrally resolved two-photon (2P) imaging and excitation of GCaMP6s and C1V1-mCherry, respectively. APPROACH: A PCF is pumped using a 20-MHz repetition rate femtosecond laser to generate a supercontinuum of light, which is spectrally separated, compressed, and recombined to image GCaMP6s (930 nm excitation) and stimulate the optogenetic protein, C1V1-mCherry (1060 nm excitation). Galvanometric spiral scanning is employed on a single-cell level for multiphoton excitation and high-speed resonant scanning is employed for imaging of calcium activity. RESULTS: Continuous wave lasers were used to verify functionality of optogenetic activation followed by directed 2P excitation. Results from these experiments demonstrate the utility of a supercontinuum light source for simultaneous, single-cell excitation and calcium imaging. CONCLUSIONS: A PCF-based supercontinuum light source was employed for simultaneous imaging and excitation of calcium dynamics in brain tissue. Pumped PCFs can serve as powerful light sources for imaging and activation of neural activity, and overcome the limited spectra and space associated with multilaser approaches.

Single-shot two-dimensional spectroscopic magnetomotive optical coherence elastography with graphics processing unit acceleration.

Biomechanical contrast within tissues can be assessed based on the resonant frequency probed by spectroscopic magnetomotive optical coherence elastography (MM-OCE). However, to date, in vivo MM-OCE imaging has not been achieved, mainly due to the constraints on imaging speed. Previously, spatially-resolved spectroscopic contrast was achieved in a "multiple-excitation, multiple-acquisition" manner, where seconds of coil cooling time set between consecutive imaging frames lead to total acquisition times of tens of minutes. Here, we demonstrate an improved data acquisition speed by providing a single chirped force excitation prior to magnetomotion imaging with a BM-scan configuration. In addition, elastogram reconstruction was accelerated by exploiting the parallel computing capability of a graphics processing unit (GPU). The accelerated MM-OCE platform achieved data acquisition in 2.9 s and post-processing in 0.6 s for a 2048-frame BM-mode stack. In addition, the elasticity sensing functionality was validated on tissue-mimicking phantoms with high spatial resolution. For the first time, to the best of our knowledge, MM-OCE images were acquired from the skin of a living mouse, demonstrating its feasibility for in vivo imaging.

Dynamic Tracking Algorithm for Time-Varying Neuronal Network Connectivity using Wide-Field Optical Image Video Sequences.

Propagation of signals between neurons and brain regions provides information about the functional properties of neural networks, and thus information transfer. Advances in optical imaging and statistical analyses of acquired optical signals have yielded various metrics for inferring neural connectivity, and hence for mapping signal intercorrelation. However, a single coefficient is traditionally derived to classify the connection strength between two cells, ignoring the fact that neural systems are inherently time-variant systems. To overcome these limitations, we utilized a time-varying Pearson's correlation coefficient, spike-sorting, wavelet transform, and wavelet coherence of calcium transients from DIV 12-15 hippocampal neurons from GCaMP6s mice after applying various concentrations of glutamate. Results provide a comprehensive overview of resulting firing patterns, network connectivity, signal directionality, and network properties. Together, these metrics provide a more comprehensive and robust method of analyzing transient neural signals, and enable future investigations for tracking the effects of different stimuli on network properties.

Label-free visualization and characterization of extracellular vesicles in breast cancer.

Despite extensive interest, extracellular vesicle (EV) research remains technically challenging. One of the unexplored gaps in EV research has been the inability to characterize the spatially and functionally heterogeneous populations of EVs based on their metabolic profile. In this paper, we utilize the intrinsic optical metabolic and structural contrast of EVs and demonstrate in vivo/in situ characterization of EVs in a variety of unprocessed (pre)clinical samples. With a pixel-level segmentation mask provided by the deep neural network, individual EVs can be analyzed in terms of their optical signature in the context of their spatial distribution. Quantitative analysis of living tumor-bearing animals and fresh excised human breast tissue revealed abundance of NAD(P)H-rich EVs within the tumor, near the tumor boundary, and around vessel structures. Furthermore, the percentage of NAD(P)H-rich EVs is highly correlated with human breast cancer diagnosis, which emphasizes the important role of metabolic imaging for EV characterization as well as its potential for clinical applications. In addition to the characterization of EV properties, we also demonstrate label-free monitoring of EV dynamics (uptake, release, and movement) in live cells and animals. The in situ metabolic profiling capacity of the proposed method together with the finding of increasing NAD(P)H-rich EV subpopulations in breast cancer have the potential for empowering applications in basic science and enhancing our understanding of the active metabolic roles that EVs play in cancer progression.

Detection of weak near-infrared optical imaging signals under ambient light by optical parametric amplification.

We present a detection method based on optical parametric amplification to amplify and detect near-infrared (NIR) optical imaging signals. A periodically poled lithium niobate crystal is employed as an optical parametric amplifier (OPA), which provides excellent quasi-phase-matching conditions for the optical parametric amplification process. A weak reflectance imaging signal at 1465 nm is amplified by the OPA with a high gain of up to 92 dB, and the amplified optical signal is detected with a low-cost photodetector under ambient light conditions. Such a high gain leads to a detection limit of 23 pW under a 5 MHz detection bandwidth, which is remarkably lower than the theoretical value of a NIR photomultiplier tube (PMT). By exploiting the advantages of the OPA, the incident power needed for microscopy or imaging is reduced by 40-60 dB. The high imaging gain of the OPA also significantly enhances the imaging penetration depth by selectively detecting the weak signal reflected from deep tissue structures. The successful implementation of the OPA enables a robust and sensitive detection method that offers the potential to replace PMTs in imaging applications within the NIR spectral range.

Automated sensorless single-shot closed-loop adaptive optics microscopy with feedback from computational adaptive optics.

Traditional wavefront-sensor-based adaptive optics (AO) techniques face numerous challenges that cause poor performance in scattering samples. Sensorless closed-loop AO techniques overcome these challenges by optimizing an image metric at different states of a deformable mirror (DM). This requires acquisition of a series of images continuously for optimization - an arduous task in dynamic in vivo samples. We present a technique where the different states of the DM are instead simulated using computational adaptive optics (CAO). The optimal wavefront is estimated by performing CAO on an initial volume to minimize an image metric, and then the pattern is translated to the DM. In this paper, we have demonstrated this technique on a spectral-domain optical coherence microscope for three applications: real-time depth-wise aberration correction, single-shot volumetric aberration correction, and extension of depth-of-focus. Our technique overcomes the disadvantages of sensor-based AO, reduces the number of image acquisitions compared to traditional sensorless AO, and retains the advantages of both computational and hardware-based AO.

Local wavefront mapping in tissue using computational adaptive optics OCT.

The identification and correction of wavefront aberrations is often necessary to achieve high-resolution optical images of biological tissues, as imperfections in the optical system and the tissue itself distort the imaging beam. Measuring the localized wavefront aberration provides information on where the beam is distorted and how severely. We have recently developed a method to estimate the single-pass wavefront aberrations from complex optical coherence tomography (OCT) data. Using this method, localized wavefront measurement and correction using computational OCT was performed in ex vivo tissues. The computationally measured wavefront varied throughout the imaged OCT volumes and, therefore, a local wavefront correction outperformed a global wavefront correction. The local wavefront measurement was also used to generate tissue aberration maps. Such aberration maps could potentially be used as a new form of tissue contrast.

Combined hardware and computational optical wavefront correction.

In many optical imaging applications, it is necessary to overcome aberrations to obtain high-resolution images. Aberration correction can be performed by either physically modifying the optical wavefront using hardware components, or by modifying the wavefront during image reconstruction using computational imaging. Here we address a longstanding issue in computational imaging: photons that are not collected cannot be corrected. This severely restricts the applications of computational wavefront correction. Additionally, performance limitations of hardware wavefront correction leave many aberrations uncorrected. We combine hardware and computational correction to address the shortcomings of each method. Coherent optical backscattering data is collected using high-speed optical coherence tomography, with aberrations corrected at the time of acquisition using a wavefront sensor and deformable mirror to maximize photon collection. Remaining aberrations are corrected by digitally modifying the coherently-measured wavefront during imaging reconstruction. This strategy obtains high-resolution images with improved signal-to-noise ratio of in vivo human photoreceptor cells with more complete correction of ocular aberrations, and increased flexibility to image at multiple retinal depths, field locations, and time points. While our approach is not restricted to retinal imaging, this application is one of the most challenging for computational imaging due to the large aberrations of the dilated pupil, time-varying aberrations, and unavoidable eye motion. In contrast with previous computational imaging work, we have imaged single photoreceptors and their waveguide modes in fully dilated eyes with a single acquisition. Combined hardware and computational wavefront correction improves the image sharpness of existing adaptive optics systems, and broadens the potential applications of computational imaging methods.

Intravital imaging by simultaneous label-free autofluorescence-multiharmonic microscopy.

Intravital microscopy (IVM) emerged and matured as a powerful tool for elucidating pathways in biological processes. Although label-free multiphoton IVM is attractive for its non-perturbative nature, its wide application has been hindered, mostly due to the limited contrast of each imaging modality and the challenge to integrate them. Here we introduce simultaneous label-free autofluorescence-multiharmonic (SLAM) microscopy, a single-excitation source nonlinear imaging platform that uses a custom-designed excitation window at 1110 nm and shaped ultrafast pulses at 10 MHz to enable fast (2-orders-of-magnitude improvement), simultaneous, and efficient acquisition of autofluorescence (FAD and NADH) and second/third harmonic generation from a wide array of cellular and extracellular components (e.g., tumor cells, immune cells, vesicles, and vessels) in living tissue using only 14 mW for extended time-lapse investigations. Our work demonstrates the versatility and efficiency of SLAM microscopy for tracking cellular events in vivo, and is a major enabling advance in label-free IVM.

Wavefront measurement using computational adaptive optics.

In many optical imaging applications, it is necessary to correct for aberrations to obtain high quality images. Optical coherence tomography (OCT) provides access to the amplitude and phase of the backscattered optical field for three-dimensional (3D) imaging samples. Computational adaptive optics (CAO) modifies the phase of the OCT data in the spatial frequency domain to correct optical aberrations without using a deformable mirror, as is commonly done in hardware-based adaptive optics (AO). This provides improvement of image quality throughout the 3D volume, enabling imaging across greater depth ranges and in highly aberrated samples. However, the CAO aberration correction has a complicated relation to the imaging pupil and is not a direct measurement of the pupil aberrations. Here we present new methods for recovering the wavefront aberrations directly from the OCT data without the use of hardware adaptive optics. This enables both computational measurement and correction of optical aberrations.

Isobaric tag for relative and absolute quantitation-based comparative proteomic analysis of human pathogenic Prototheca zopfii genotype 2 and environmental genotype 1 strains.

BACKGROUND/PURPOSE: Prototheca species are ubiquitous achlorophyllic microalgae belonging to the family Chlorellaceae, which can cause a wide range of infections in humans and animals. Mainly in individuals with immunologic defects or trauma, Prototheca spp. can cause even lethal diseases. However, the exact pathogenic mechanism of Prototheca in causing disease remains largely unknown. To investigate the differences between pathogenic and nonpathogenic Prototheca spp. genotypes on proteome level, a nonpathogenic Prototheca zopfii genotype 1 strain, isolated from cow manure, and a human pathogenic P. zopfii genotype 2, isolated from human granulomatous lymphadenitis, were studied. METHODS: Differentially expressed proteins between the two genotypes were quantified by isobaric tag for relative and absolute quantitation-based quantitative proteomics, using liquid chromatography-tandem mass spectrometry. RESULTS: A total of 245 proteins were identified from the proteomic analysis after data filtering to eliminate low-scoring spectra. Among these, 35 proteins that displayed a significant (p<0.05) 1.5-fold change were considered as differentially expressed proteins. CONCLUSION: The differentially expressed proteins were associated with suppressed energy production and conversion, carbohydrate transport and metabolism, and enhanced translation in the genotype 2 strain, and are thus potentially relevant in the pathogenic mechanism of P. zopfii genotype 2, but need further investigation.

Computational optical coherence tomography [Invited].

Optical coherence tomography (OCT) has become an important imaging modality with numerous biomedical applications. Challenges in high-speed, high-resolution, volumetric OCT imaging include managing dispersion, the trade-off between transverse resolution and depth-of-field, and correcting optical aberrations that are present in both the system and sample. Physics-based computational imaging techniques have proven to provide solutions to these limitations. This review aims to outline these computational imaging techniques within a general mathematical framework, summarize the historical progress, highlight the state-of-the-art achievements, and discuss the present challenges.

Computed Optical Interferometric Imaging: Methods, Achievements, and Challenges.

Three-dimensional high-resolution optical imaging systems are generally restricted by the trade-off between resolution and depth-of-field as well as imperfections in the imaging system or sample. Computed optical interferometric imaging is able to overcome these longstanding limitations using methods such as interferometric synthetic aperture microscopy (ISAM) and computational adaptive optics (CAO) which manipulate the complex interferometric data. These techniques correct for limited depth-of-field and optical aberrations without the need for additional hardware. This paper aims to outline these computational methods, making them readily available to the research community. Achievements of the techniques will be highlighted, along with past and present challenges in implementing the techniques. Challenges such as phase instability and determination of the appropriate aberration correction have been largely overcome so that imaging of living tissues using ISAM and CAO is now possible. Computed imaging in optics is becoming a mature technology poised to make a significant impact in medicine and biology.

Automated computational aberration correction method for broadband interferometric imaging techniques.

Numerical correction of optical aberrations provides an inexpensive and simpler alternative to the traditionally used hardware-based adaptive optics techniques. In this Letter, we present an automated computational aberration correction method for broadband interferometric imaging techniques. In the proposed method, the process of aberration correction is modeled as a filtering operation on the aberrant image using a phase filter in the Fourier domain. The phase filter is expressed as a linear combination of Zernike polynomials with unknown coefficients, which are estimated through an iterative optimization scheme based on maximizing an image sharpness metric. The method is validated on both simulated data and experimental data obtained from a tissue phantom, an ex vivo tissue sample, and an in vivo photoreceptor layer of the human retina.

Automated interferometric synthetic aperture microscopy and computational adaptive optics for improved optical coherence tomography.

In this paper, we introduce an algorithm framework for the automation of interferometric synthetic aperture microscopy (ISAM). Under this framework, common processing steps such as dispersion correction, Fourier domain resampling, and computational adaptive optics aberration correction are carried out as metrics-assisted parameter search problems. We further present the results of this algorithm applied to phantom and biological tissue samples and compare with manually adjusted results. With the automated algorithm, near-optimal ISAM reconstruction can be achieved without manual adjustment. At the same time, the technical barrier for the nonexpert using ISAM imaging is also significantly lowered.

Correction of aberrations in the human eye using computational methods.

Phase-sensitive imaging and computational correction of patient-specific optical aberrations enable high-resolution imaging of the human retina to aid diagnosis and treatment of eye diseases.

Polarization-sensitive interferometric synthetic aperture microscopy.

Three-dimensional optical microscopy suffers from the well-known compromise between transverse resolution and depth-of-field. This is true for both structural imaging methods and their functional extensions. Interferometric synthetic aperture microscopy (ISAM) is a solution to the 3D coherent microscopy inverse problem that provides depth-independent transverse resolution. We demonstrate the extension of ISAM to polarization sensitive imaging, termed polarization-sensitive interferometric synthetic aperture microscopy (PS-ISAM). This technique is the first functionalization of the ISAM method and provides improved depth-of-field for polarization-sensitive imaging. The basic assumptions of polarization-sensitive imaging are explored, and refocusing of birefringent structures is experimentally demonstrated. PS-ISAM enables high-resolution volumetric imaging of birefringent materials and tissue.

Predictive value of quantitative contrast-enhanced ultrasound in hepatocellular carcinoma recurrence after ablation.

AIM: To investigate the relationship between contrast-enhanced ultrasound (CEUS), basic fibroblast growth factor (bFGF), endothelin-1 (ET-1), and hepatocellular carcinoma (HCC) recurrence after ablation. METHODS: A total of 51 HCC patients (38 males and 13 females) who received radiofrequency ablation in our hospital from June 2012 to July 2014 were enrolled in this study. The patients were divided into two groups: recurrence group and non-recurrence group. Routine abdominal examination was first performed in the horizontal position. Then the patients underwent CEUS and immunohistochemical staining before receiving radiofrequency ablation. All patients were followed-up every three months for one year. The results of CEUS and serum tumor marker levels were evaluated and combined together to estimate HCC recurrence and metastasis. Patients were divided into two groups: recurrence group and non-recurrence group. Quantitative parameters of CEUS and tumor expression levels of bFGF and ET-1 were compared between the two groups, respectively. Binary logistic regression analysis was used to analyze the relationship between CEUS quantitative parameters, expression levels of ET-1 and bFGF, and HCC recurrence after ablation. RESULTS: Based on the quantitative parameters of CEUS before patients received radiofrequency ablation, the levels of tumor rise time (tRT), tumor time to peak (tTTP), tumor peak intensity (tPI) and tumor-parenchymal peak intensity (t-pPI) in the recurrence group were significantly lower than those in the non-recurrence group (16.6 ± 6.1 vs 23.2 ± 7.0, P = 0.000; 41.2 ± 10.2 vs 59.6 ± 14.2, P = 0.000; 23.8 ± 6.7 vs 31.4 ± 6.4, P = 0.000; 7.1 ± 3.4 vs 14.6 ± 7.4, P = 0.000; respectively). The expression levels of bFGF in the recurrence group were significantly higher than those in the non-recurrence group (P < 0.05). Levels of tTTP showed a significant inverse correlation with the level of bFGF in tumors (r = -0.312, P = 0.037). The Binary logistic regression analysis results revealed that the levels of tRT, tTTP, tPI and the level of bFGF were associated with HCC recurrence after radiofrequency ablation (P < 0.05). CONCLUSION: CEUS is a noninvasive and effective method for evaluating the angiogenesis of HCC, and predicting its recurrence and prognosis.

Computational high-resolution optical imaging of the living human retina.

High-resolution in vivo imaging is of great importance for the fields of biology and medicine. The introduction of hardware-based adaptive optics (HAO) has pushed the limits of optical imaging, enabling high-resolution near diffraction-limited imaging of previously unresolvable structures1,2. In ophthalmology, when combined with optical coherence tomography, HAO has enabled a detailed three-dimensional visualization of photoreceptor distributions3,4 and individual nerve fibre bundles5 in the living human retina. However, the introduction of HAO hardware and supporting software adds considerable complexity and cost to an imaging system, limiting the number of researchers and medical professionals who could benefit from the technology. Here we demonstrate a fully automated computational approach that enables high-resolution in vivo ophthalmic imaging without the need for HAO. The results demonstrate that computational methods in coherent microscopy are applicable in highly dynamic living systems.