Stain-free histopathology by programmable supercontinuum pulses

Wavelength-tunable 1104 nm nonlinear amplifier loop mirror laser based on a polarization-maintaining double-cladding fiber

An ytterbium-doped stretched-pulse mode-locked fiber oscillator was fabricated by applying a nonlinear amplifier loop mirror (NALM). The fiber cavity was built using a large-mode area (LMA) polarization-maintaining (PM) double-cladding (DC) fiber. The central wavelength of the generated 24.7 MHz laser can be modified from 1034 to 1104 nm by tuning the intra-cavity loss. The output power of this laser with a wavelength of 1104 nm at the transmission and reflection ports is 7.61 and 0.33 mW, respectively. The corresponding compressed pulse durations are 192 and 187 fs, which are 1.54 and 1.02 times the Fourier-transform-limited pulse duration, respectively.

Weakly Supervised Deep Ordinal Cox Model for Survival Prediction From Whole-Slide Pathological Images

Whole-Slide Histopathology Image (WSI) is generally considered the gold standard for cancer diagnosis and prognosis. Given the large inter-operator variation among pathologists, there is an imperative need to develop machine learning models based on WSIs for consistently predicting patient prognosis. The existing WSI-based prediction methods do not utilize the ordinal ranking loss to train the prognosis model, and thus cannot model the strong ordinal information among different patients in an efficient way. Another challenge is that a WSI is of large size (e.g., 100,000-by-100,000 pixels) with heterogeneous patterns but often only annotated with a single WSI-level label, which further complicates the training process. To address these challenges, we consider the ordinal characteristic of the survival process by adding a ranking-based regularization term on the Cox model and propose a weakly supervised deep ordinal Cox model (BDOCOX) for survival prediction from WSIs. Here, we generate amounts of bags from WSIs, and each bag is comprised of the image patches representing the heterogeneous patterns of WSIs, which is assumed to match the WSI-level labels for training the proposed model. The effectiveness of the proposed method is well validated by theoretical analysis as well as the prognosis and patient stratification results on three cancer datasets from The Cancer Genome Atlas (TCGA).

Particle swarm optimization of SPM-enabled spectral selection to achieve an octave-spanning wavelength-shift

SPM-enabled spectral selection (SESS) constitutes a powerful fiber-optic technique to generate wavelength broadly tunable femtosecond pulses. In the current demonstration, the maximum tuning range is 400 nm and the energy conversion efficiency from the pump source to the outmost spectral lobes is ∼25%. In this submission, we apply the particle swarm optimization method to the generalized nonlinear Schrödinger equation to identify the optimal parameters that maximize both the tuning range and the conversion efficiency. We show that SESS in an optical fiber with the optimized dispersion can deliver SESS pulses tunable in one octave wavelength range and the conversion efficiency can be as high as 80%. We further show the feasibility of experimental implementation based on specially designed fibers or on-chip waveguides.

Association of Tumor-Associated Collagen Signature With Prognosis and Adjuvant Chemotherapy Benefits in Patients With Gastric Cancer

IMPORTANCE

The current TNM staging system provides limited information for prognosis prediction and adjuvant chemotherapy benefits for patients with gastric cancer (GC).

OBJECTIVE

To develop a tumor-associated collagen signature of GC (TACSGC) in the tumor microenvironment to predict prognosis and adjuvant chemotherapy benefits in patients with GC.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study included a training cohort of 294 consecutive patients treated between January 1, 2012, and December 31, 2013, from Nanfang Hospital, Southern Medical University, People's Republic of China, and a validation cohort of 225 consecutive patients treated between October 1, 2010, and December 31, 2012, from Fujian Provincial Cancer Hospital, Fujian Medical University, People's Republic of China. In total, 146 collagen features in the tumor microenvironment were extracted with multiphoton imaging. A TACSGC was then constructed using the least absolute shrinkage and selection operator Cox proportional hazards regression model in the training cohort. Data analysis was conducted from October 1, 2020, to April 30, 2021.

MAIN OUTCOMES AND MEASURES

The association of TACSGC with disease-free survival (DFS) and overall survival (OS) was assessed. An independent external cohort was included to validate the results. Interactions between TACSGC and adjuvant chemotherapy were calculated.

RESULTS

This study included 519 patients (median age, 57 years [IQR, 49-65 years]; 360 [69.4%] male). A 9 feature-based TACSGC was built. A higher TACSGC level was significantly associated with worse DFS and OS in both the training (DFS: hazard ratio [HR], 3.57 [95% CI, 2.45-5.20]; OS: HR, 3.54 [95% CI, 2.41-5.20]) and validation (DFS: HR, 3.10 [95% CI, 2.26-4.27]; OS: HR, 3.24 [95% CI, 2.33-4.50]) cohorts (continuous variable, P < .001 for all comparisons). Multivariable analyses found that carbohydrate antigen 19-9, depth of invasion, lymph node metastasis, distant metastasis, and TACSGC were independent prognostic predictors of GC, and 2 integrated nomograms that included the 5 predictors were established for predicting DFS and OS. Compared with clinicopathological models that included only the 4 clinicopathological predictors, the integrated nomograms yielded an improved discrimination for prognosis prediction in a C index comparison (training cohort: DFS, 0.80 [95% CI, 0.73-0.88] vs 0.78 [95% CI, 0.71-0.85], P = .03; OS, 0.81 [95% CI, 0.75-0.88] vs 0.80 [95% CI, 0.73-0.86], P = .03; validation cohort: DFS, 0.78 [95% CI, 0.70-0.87] vs 0.76 [95% CI, 0.67-0.84], P = .006; OS, 0.78 [95% CI, 0.69-0.86] vs 0.75 [95% CI, 0.67-0.84], P = .002). Patients with stage II and III GC and low TACSGC levels rather than high TACSGC levels had a favorable response to adjuvant chemotherapy (DFS: HR, 0.65 [95% CI, 0.43-0.96]; P = .03; OS: HR, 0.55 [95% CI, 0.36-0.82]; P = .004; dichotomized variable, P < .001 for interaction for both comparisons).

CONCLUSIONS AND RELEVANCE

The findings suggest that TACSGC provides additional prognostic information for patients with GC and may distinguish patients with stage II and III disease who are more likely to derive benefits from adjuvant chemotherapy.

Unveiling the Molecular Dynamics in a Living Cell to the Subcellular Organelle Level Using Second-Harmonic Generation Spectroscopy and Microscopy

Second-harmonic generation (SHG) microscopy has been proved to be a powerful method for investigating the structures of biomaterials. SHG spectra were also generally used to probe the adsorption and cross-membrane transport of molecules on lipid bilayers in situ and in real time. In this work, we applied SHG and two-photon fluorescence (TPF) spectra to investigate the dynamics of an amphiphilic ion with an SHG and TPF chromophore, D289 (4-(4-diethylaminostyry)-1-methyl-pyridinium iodide), on the surface of human chronic myelogenous leukemia (K562) cells and the subcellular structures inside the cells. The adsorption and cross-membrane transport of D289 into the cells and then into the organelles such as mitochondria were revealed. SHG images were also recorded and used to demonstrate their capability of probing molecular dynamics in organelles in K562 cells. This work demonstrated the first SHG investigation of the cross-membrane transport dynamics on the surface of subcellular organelles. It may also shed light on the differentiation of different types of subcellular structures in cells.

Enhanced medical diagnosis for dOCTors: a perspective of optical coherence tomography

SIGNIFICANCE

After three decades, more than 75,000 publications, tens of companies being involved in its commercialization, and a global market perspective of about USD 1.5 billion in 2023, optical coherence tomography (OCT) has become one of the fastest successfully translated imaging techniques with substantial clinical and economic impacts and acceptance.

AIM

Our perspective focuses on disruptive forward-looking innovations and key technologies to further boost OCT performance and therefore enable significantly enhanced medical diagnosis.

APPROACH

A comprehensive review of state-of-the-art accomplishments in OCT has been performed.

RESULTS

The most disruptive future OCT innovations include imaging resolution and speed (single-beam raster scanning versus parallelization) improvement, new implementations for dual modality or even multimodality systems, and using endogenous or exogenous contrast in these hybrid OCT systems targeting molecular and metabolic imaging. Aside from OCT angiography, no other functional or contrast enhancing OCT extension has accomplished comparable clinical and commercial impacts. Some more recently developed extensions, e.g., optical coherence elastography, dynamic contrast OCT, optoretinography, and artificial intelligence enhanced OCT are also considered with high potential for the future. In addition, OCT miniaturization for portable, compact, handheld, and/or cost-effective capsule-based OCT applications, home-OCT, and self-OCT systems based on micro-optic assemblies or photonic integrated circuits will revolutionize new applications and availability in the near future. Finally, clinical translation of OCT including medical device regulatory challenges will continue to be absolutely essential.

CONCLUSIONS

With its exquisite non-invasive, micrometer resolution depth sectioning capability, OCT has especially revolutionized ophthalmic diagnosis and hence is the fastest adopted imaging technology in the history of ophthalmology. Nonetheless, OCT has not been completely exploited and has substantial growth potential-in academics as well as in industry. This applies not only to the ophthalmic application field, but also especially to the original motivation of OCT to enable optical biopsy, i.e., the in situ imaging of tissue microstructure with a resolution approaching that of histology but without the need for tissue excision.

Multimodal microscopy for the simultaneous visualization of five different imaging modalities using a single light source

Optical microscopy has been widely used in biomedical research as it provides photophysical and photochemical information of the target in subcellular spatial resolution without requiring physical contact with the specimen. To obtain a deeper understanding of biological phenomena, several efforts have been expended to combine such optical imaging modalities into a single microscope system. However, the use of multiple light sources and detectors through separated beam paths renders previous systems extremely complicated or slow for in vivo imaging. Herein, we propose a novel high-speed multimodal optical microscope system that simultaneously visualizes five different microscopic contrasts, i.e., two-photon excitation, second-harmonic generation, backscattered light, near-infrared fluorescence, and fluorescence lifetime, using a single femtosecond pulsed laser. Our proposed system can visualize five modal images with a frame rate of 3.7 fps in real-time, thereby providing complementary optical information that enhances both structural and functional contrasts. This highly photon-efficient multimodal microscope system enables various properties of biological tissues to be assessed.

Hexachromatic bioinspired camera for image-guided cancer surgery

Cancer affects one in three people worldwide. Surgery remains the primary curative option for localized cancers, but good prognoses require complete removal of primary tumors and timely recognition of metastases. To expand surgical capabilities and enhance patient outcomes, we developed a six-channel color/near-infrared image sensor inspired by the mantis shrimp visual system that enabled near-infrared fluorescence image guidance during surgery. The mantis shrimp's unique eye, which maximizes the number of photons contributing to and the amount of information contained in each glimpse of its surroundings, is recapitulated in our single-chip imaging system that integrates arrays of vertically stacked silicon photodetectors and pixelated spectral filters. To provide information about tumor location unavailable from a single instrument, we tuned three color channels to permit an intuitive perspective of the surgical procedure and three near-infrared channels to permit multifunctional imaging of optical probes highlighting cancerous tissue. In nude athymic mice bearing human prostate tumors, our image sensor enabled simultaneous detection of two tumor-targeted fluorophores, distinguishing diseased from healthy tissue in an estimated 92% of cases. It also permitted extraction of near-infrared structured illumination enabling the mapping of the three-dimensional topography of tumors and surgical sites to within 1.2-mm error. In the operating room, during surgical resection in 18 patients with breast cancer, our image sensor further enabled sentinel lymph node mapping using clinically approved near-infrared fluorophores. The flexibility and performance afforded by this simple and compact architecture highlights the benefits of biologically inspired sensors in image-guided surgery.

Coherent Raman scattering microscopy for chemical imaging of biological systems

Coherent Raman scattering (CRS) processes, including both the coherent anti-Stokes Raman scattering and stimulated Raman scattering, have been utilized in state-of-the-art microscopy platforms for chemical imaging of biological samples. The key advantage of CRS microscopy over fluorescence microscopy is label-free, which is an attractive characteristic for modern biological and medical sciences. Besides, CRS has other advantages such as higher selectivity to metabolites, no photobleaching, and narrow peak width. These features have brought fast-growing attention to CRS microscopy in biological research. In this review article, we will first briefly introduce the history of CRS microscopy, and then explain the theoretical background of the CRS processes in detail using the classical approach. Next, we will cover major instrumentation techniques of CRS microscopy. Finally, we will enumerate examples of recent applications of CRS imaging in biological and medical sciences.

Intraoperative Label-Free Multimodal Nonlinear Optical Imaging for Point-of-Procedure Cancer Diagnostics

Intraoperative imaging in surgical oncology can provide information about the tumor microenvironment as well as information about the tumor margin. Visualizing microstructural features and molecular and functional dynamics may provide important diagnostic and prognostic information, especially when obtained in real-time at the point-of-procedure. A majority of current intraoperative optical techniques are based on the use of the labels, such as fluorescent dyes. However, these exogenous agents disrupt the natural microenvironment, perturb biological processes, and alter the endogenous optical signatures that cells and the microenvironment can provide. Portable nonlinear imaging systems have enabled intraoperative imaging for real-time detection and diagnosis of tissue. We review the development of a label-free multimodal nonlinear optical imaging technique that was adapted into a portable imaging system for intraoperative optical assessment of resected human breast tissue. New developments have applied this technology to assessing needle-biopsy specimens. Needle-biopsy procedures most always precede surgical resection and serve as the first sampling of suspicious masses for diagnosis. We demonstrate the diagnostic feasibility of imaging core needle-biopsy specimens during veterinary cancer surgeries. This intraoperative label-free multimodal nonlinear optical imaging technique can potentially provide a powerful tool to assist in cancer diagnosis at the point-of-procedure.

Real-time pixelwise phasor analysis for video-rate two-photon fluorescence lifetime imaging microscopy

Two-photon fluorescence lifetime imaging microscopy (FLIM) is a widely used technique in biomedical optical imaging. Presently, many two-photon time-domain FLIM setups are limited by long acquisition and postprocessing times that decrease data throughput and inhibit the ability to image fast sub-second processes. Here, we present a versatile two-photon FLIM setup capable of video-rate (up to 25 fps) imaging with graphics processing unit (GPU)-accelerated pixelwise phasor analysis displayed and saved simultaneously with acquisition. The system uses an analog output photomultiplier tube in conjunction with 12-bit digitization at 3.2 GHz to overcome the limited maximum acceptable photon rate associated with the photon counting electronics in many FLIM systems. This allows for higher throughput FLIM acquisition and analysis, and additionally enables the user to assess sample fluorescence lifetime in real-time. We further explore the capabilities of the system to examine the kinetics of Rhodamine B uptake by human breast cancer cells and characterize the effect of pixel dwell time on the reduced nicotinamide adenine dinucleotide and reduced nicotinamide adenine dinucleotide phosphate (NAD(P)H) autofluorescence lifetime estimation accuracy.

Monitoring the extracellular matrix remodeling of high-grade serous ovarian cancer with nonlinear optical microscopy

The mortality of high-grade serous ovarian cancer (HGSOC) accounts for 70% to 80% of all ovarian cancer deaths and overall mortality rate has not declined in the last decade. Recently, many studies have demonstrated that HGSOC originates from the fallopian tubes. The extracellular matrix (ECM) is present in all tissues, its remodeling and interaction with cells are crucial for regulating cell proliferation, migration, and differentiation. In this paper, we used label-free nonlinear optical microscopy to image tissues of the fallopian tube and ovary. Combining a set of image processing algorithms, we monitored the remodeling of ECM in the fallopian tube and ovary during the invasion of primary serous fallopian tube tumor into the ovary in microscopic dimension. With this approach, we can obtain physiological information of HGSOC at the early stage, which provided useful data for auxiliary clinical diagnosis.

Ultrasensitive Vibrational Imaging of Retinoids by Visible Preresonance Stimulated Raman Scattering Microscopy

High-sensitivity chemical imaging offers a window to decipher the molecular orchestra inside a living system. Based on vibrational fingerprint signatures, coherent Raman scattering microscopy provides a label-free approach to map biomolecules and drug molecules inside a cell. Yet, by near-infrared (NIR) pulse excitation, the sensitivity is limited to millimolar concentration for endogenous biomolecules. Here, the imaging sensitivity of stimulated Raman scattering (SRS) is significantly boosted for retinoid molecules to 34 micromolar via electronic preresonance in the visible wavelength regime. Retinoids play critical roles in development, immunity, stem cell differentiation, and lipid metabolism. By visible preresonance SRS (VP-SRS) imaging, retinoid distribution in single embryonic neurons and mouse brain tissues is mapped, retinoid storage in chemoresistant pancreatic and ovarian cancers is revealed, and retinoids stored in protein network and lipid droplets of Caenorahbditis elegans are identified. These results demonstrate VP-SRS microscopy as an ultrasensitive label-free chemical imaging tool and collectively open new opportunities of understanding the function of retinoids in biological systems.

Label-Free Deep Profiling of the Tumor Microenvironment

Label-free nonlinear microscopy enables nonperturbative visualization of structural and metabolic contrast within living cells in their native tissue microenvironment. Here a computational pipeline was developed to provide a quantitative view of the microenvironmental architecture within cancerous tissue from label-free nonlinear microscopy images. To enable single-cell and single-extracellular vesicle (EV) analysis, individual cells, including tumor cells and various types of stromal cells, and EVs were segmented by a multiclass pixelwise segmentation neural network and subsequently analyzed for their metabolic status and molecular structure in the context of the local cellular neighborhood. By comparing cancer tissue with normal tissue, extensive tissue reorganization and formation of a patterned cell-EV neighborhood was observed in the tumor microenvironment. The proposed analytic pipeline is expected to be useful in a wide range of biomedical tasks that benefit from single-cell, single-EV, and cell-to-EV analysis. SIGNIFICANCE: The proposed computational framework allows label-free microscopic analysis that quantifies the complexity and heterogeneity of the tumor microenvironment and opens possibilities for better characterization and utilization of the evolving cancer landscape.

Tracking the formation and degradation of fatty-acid-accumulated mitochondria using label-free chemical imaging

The mitochondrion is one of the key organelles for maintaining cellular homeostasis. External environmental stimuli and internal regulatory processes may alter the metabolism and functions of mitochondria. To understand these activities of mitochondria, it is critical to probe the key metabolic molecules inside these organelles. In this study, we used label-free chemical imaging modalities including coherent anti-Stokes Raman scattering and multiphoton-excited fluorescence to investigate the mitochondrial activities in living cancer cells. We found that hypothermia exposure tends to induce fatty-acid (FA) accumulation in some mitochondria of MIAPaCa-2 cells. Autofluorescence images show that the FA-accumulated mitochondria also have abnormal metabolism of nicotinamide adenine dinucleotide hydrogen, likely induced by the dysfunction of the electron transport chain. We also found that when the cells were re-warmed to physiological temperature after a period of hypothermia, the FA-accumulated mitochondria changed their structural features. To the best of our knowledge, this is the first time that FA accumulation in mitochondria was observed in live cells. Our research also demonstrates that multimodal label-free chemical imaging is an attractive tool to discover abnormal functions of mitochondria at the single-organelle level and can be used to quantify the dynamic changes of these organelles under perturbative conditions.

Harnessing non-destructive 3D pathology

High-throughput methods for slide-free three-dimensional (3D) pathological analyses of whole biopsies and surgical specimens offer the promise of modernizing traditional histology workflows and delivering improvements in diagnostic performance. Advanced optical methods now enable the interrogation of orders of magnitude more tissue than previously possible, where volumetric imaging allows for enhanced quantitative analyses of cell distributions and tissue structures that are prognostic and predictive. Non-destructive imaging processes can simplify laboratory workflows, potentially reducing costs, and can ensure that samples are available for subsequent molecular assays. However, the large size of the feature-rich datasets that they generate poses challenges for data management and computer-aided analysis. In this Perspective, we provide an overview of the imaging technologies that enable 3D pathology, and the computational tools-machine learning, in particular-for image processing and interpretation. We also discuss the integration of various other diagnostic modalities with 3D pathology, along with the challenges and opportunities for clinical adoption and regulatory approval.

Label-free histological imaging of tissues using Brillouin light scattering contrast

Brillouin light scattering offers a unique label-free approach to measure biomechanical properties non-invasively. While this technique is used in biomechanical analysis of cells and tissues, its potential for visualizing structural features of tissues based on the biomechanical contrast has not been much exploited. Here, we present high-resolution Brillouin microscopy images of four basic tissue types: muscular, connective, epithelial, and nervous tissues. The Brillouin contrast distinguishes between muscle fiber cells and endomysium in skeletal muscle and reveals chondrocytes along with spatially varying stiffness of the extracellular matrix in articular cartilage. The hydration-sensitive contrast can visualize the stratum corneum, epidermis, and dermis in the skin epithelium. In brain tissues, the Brillouin images show the mechanical heterogeneity across the cortex and deeper regions. This work demonstrates the versatility of using the Brillouin shift as histological contrast for examining intact tissue substructures via longitudinal modulus without the need for laborious tissue processing steps.

Multiplex-multiphoton microscopy and computational strategy for biomedical imaging

We demonstrate the benefit of a novel laser strategy in multiphoton microscopy (MPM). The cheap, simple, and turn-key supercontinuum laser system with its spectral shaping module, constitutes an ideal approach for the one-shot microscopic imaging of many fluorophores without modification of the excitation parameters: central wavelength, spectral bandwidth, and average power. The polyvalence of the resulting multiplex-multiphoton microscopy (M-MPM) device is illustrated by images of many biomedical models from several origins (biological, medical, or vegetal), generated while keeping constant the spectral parameters of excitation. The resolution of the M-MPM device is quantified by a procedure of point-spread-function (PSF) assessment led by an original, robust, and reliable computational approach FIGARO. The estimated values for the PSF width for our M-MPM system are shown to be comparable to standard values found in optical microscopy. The simplification of the excitation system constitutes a significant instrumental progress in biomedical MPM, paving the way to the imaging of many fluorophores with a single shot of excitation without any modification of the lighting device. RESEARCH HIGHLIGHTS: A new solution of multiplex-multiphoton microscopy device is shown, resting on a supercontinuum laser. The one-shot excitation device has imaged biomedical and vegetal models. Our original computational strategy measures usual microscopy resolution.

All-fiber single-cavity dual-comb for coherent anti-Stokes Raman scattering spectroscopy based on spectral focusing

We report an all-fiber free-running bidirectional dual-comb laser system for coherent anti-Stokes Raman scattering spectroscopy based on spectral focusing. The mode-locked oscillator is a bidirectional ring-cavity erbium fiber laser running at a repetition rate of ∼114MHz. One output of the bidirectional laser is wavelength-shifted from 1560 to 1060 nm via supercontinuum generation for use as the pump source. We have been able to record the Raman spectra of various samples such as polystyrene, olive oil, polymethyl methacrylate (PMMA), and polyethylene in the C-H stretching window. We believe that this all-fiber laser design has promising potential for coherent Raman spectroscopy and also label-free imaging for a variety of practical applications.

Large-scale tumor-associated collagen signatures identify high-risk breast cancer patients

The notion of personalized medicine demands proper prognostic biomarkers to guide the optimal therapy for an invasive breast cancer patient. However, various risk prediction models based on conventional clinicopathological factors and emergent molecular assays have been frequently limited by either a low strength of prognosis or restricted applicability to specific types of patients. Therefore, there is a critical need to develop a strong and general prognosticator. Methods: We observed five large-scale tumor-associated collagen signatures (TACS4-8) obtained by multiphoton microscopy at the invasion front of the breast primary tumor, which contrasted with the three tumor-associated collagen signatures (TACS1-3) discovered by Keely and coworkers at a smaller scale. Highly concordant TACS1-8 classifications were obtained by three independent observers. Using the ridge regression analysis, we obtained a TACS-score for each patient based on the combined TACS1-8 and established a risk prediction model based on the TACS-score. In a blind fashion, consistent retrospective prognosis was obtained from 995 breast cancer patients in both a training cohort (n= 431) and an internal validation cohort (n = 300) collected from one clinical center, and in an external validation cohort (n = 264) collected from a different clinical center. Results: TACS1-8 model alone competed favorably with all reported models in predicting disease-free survival (AUC: 0.838, [0.800-0.872]; 0.827, [0.779-0.868]; 0.807, [0.754-0.853] in the three cohorts) and stratifying low- and high-risk patients (HR 7.032, [4.869-10.158]; 6.846, [4.370-10.726], 4.423, [2.917-6.708]). The combination of these factors with the TACS-score into a nomogram model further improved the prognosis (AUC: 0.865, [0.829-0.896]; 0.861, [0.816-0.898]; 0.854, [0.805-0.894]; HR 7.882, [5.487-11.323]; 9.176, [5.683-14.816], and 5.548, [3.705-8.307]). The nomogram identified 72 of 357 (~20%) patients with unsuccessful 5-year disease-free survival that might have been undertreated postoperatively. Conclusions: The risk prediction model based on TACS1-8 considerably outperforms the contextual clinical model and may thus convince pathologists to pursue a TACS-based breast cancer prognosis. Our methodology identifies a significant portion of patients susceptible to undertreatment (high-risk patients), in contrast to the multigene assays that often strive to mitigate overtreatment. The compatibility of our methodology with standard histology using traditional (non-tissue-microarray) formalin-fixed paraffin-embedded (FFPE) tissue sections could simplify subsequent clinical translation.

Isoenergetic two-photon excitation enhances solvent-to-solute excited-state proton transfer

Two-photon excitation (TPE) is an attractive means for controlling chemistry in both space and time. Since isoenergetic one- and two-photon excitations (OPE and TPE) in non-centrosymmetric molecules are allowed to reach the same excited state, it is usually assumed that they produce similar excited-state reactivity. We compare the solvent-to-solute excited-state proton transfer of the super photobase FR0-SB following isoenergetic OPE and TPE. We find up to 62% increased reactivity following TPE compared to OPE. From steady-state spectroscopy, we rule out the involvement of different excited states and find that OPE and TPE spectra are identical in non-polar solvents but not in polar ones. We propose that differences in the matrix elements that contribute to the two-photon absorption cross sections lead to the observed enhanced isoenergetic reactivity, consistent with the predictions of our high-level coupled-cluster-based computational protocol. We find that polar solvent configurations favor greater dipole moment change between ground and excited states, which enters the probability for TPE as the absolute value squared. This, in turn, causes a difference in the Franck-Condon region reached via TPE compared to OPE. We conclude that a new method has been found for controlling chemical reactivity via the matrix elements that affect two-photon cross sections, which may be of great utility for spatial and temporal precision chemistry.

Reflection-mode virtual histology using photoacoustic remote sensing microscopy

Histological visualizations are critical to clinical disease management and are fundamental to biological understanding. However, current approaches that rely on bright-field microscopy require extensive tissue preparation prior to imaging. These processes are both labor intensive and contribute to creating significant delays in clinical feedback for treatment decisions that can extend to 2-3 weeks for standard paraffin-embedded tissue preparation and interpretation, especially if ancillary testing is needed. Here, we present the first comprehensive study on the broad application of a novel label-free reflection-mode imaging modality known as photoacoustic remote sensing (PARS) for visualizing salient subcellular structures from various common histopathological tissue preparations and for use in unprocessed freshly resected tissues. The PARS modality permits non-contact visualizations of intrinsic endogenous optical absorption contrast to be extracted from thick and opaque biological targets with optical resolution. The technique was examined both as a rapid assessment tool that is capable of managing large samples (> 1 cm2) in under 10 min, and as a high contrast imaging modality capable of extracting specific biological contrast to simulate conventional histological stains such as hematoxylin and eosin (H&E). The capabilities of the proposed method are demonstrated in a variety of human tissue preparations including formalin-fixed paraffin-embedded tissue blocks and unstained slides sectioned from these blocks, including normal and neoplastic human brain, and breast epithelium involved with breast cancer. Similarly, PARS images of human skin prepared by frozen section clearly demonstrated basal cell carcinoma and normal human skin tissue. Finally, we imaged unprocessed murine kidney and achieved histologically relevant subcellular morphology in fresh tissue. This represents a vital step towards an effective real-time clinical microscope that overcomes the limitations of standard histopathologic tissue preparations and enables real-time pathology assessment.

Real-time three-dimensional histology-like imaging by label-free nonlinear optical microscopy

Background

The current gold-standard formalin-fixed and paraffin-embedded (FFPE) histology typically requires several days for tissue fixing, embedding, sectioning, and staining to provide depth-resolved tissue feature visualization. During these time- and labor- intense processes, the in vivo tissue dynamics and three-dimensional structures undergo inevitable loss and distortion.

Methods

A simultaneous label-free autofluorescence multiharmonic (SLAM) microscope is used to conduct ex vivo and in vivo imaging of fresh human and rat tissues. Four nonlinear optical imaging modalities are integrated into this SLAM microscope, including second harmonic generation (SHG), two-photon fluorescence (2PF), third harmonic generation (THG), and three-photon fluorescence (3PF). By imaging fresh human and rat tissues without any tissue processing or staining, various biological tissue features are effectively visualized by one or multiple imaging modalities of the SLAM microscope. In particular, some of the most essential features in hematoxylin and eosin (H&E)-stained histology, such as collagen fibers and nuclei, are also present in the SLAM microscopy images with good contrast. Because nuclei are evident from negative contrast, the nuclei are segmented from the SLAM images using deep learning. Finally, a color-transforming algorithm is developed to convert the grey-scale images acquired by the SLAM microscope to the virtually H&E-stained histology-like images. The converted histology-like images are later compared with the FFPE histology at the same tissue site. In addition, the nuclear-to-cytoplasmic ratios (N/C ratios) of the cells in the SLAM image are quantified, which has diagnostic relevance for cancer.

Results

Various histological correlations are identified with high similarities for the color-converted histology-like SLAM microscopy images. By applying the color transforming algorithm on real-time SLAM image sequences and 3D SLAM image stacks, we report, for the first time and to the best our knowledge, real-time 3D histology-like imaging. Furthermore, the quantified N/C ratio of the cells in the SLAM image are overlaid on the converted histology-like image as a new image contrast.

Conclusions

We demonstrated real-time 3D histology-like imaging and its future potential using SLAM microscopy aided by color remapping and deep-learning-based feature segmentation.

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.

Emerging Advances to Transform Histopathology Using Virtual Staining

In an age where digitization is widespread in clinical and preclinical workflows, pathology is still predominantly practiced by microscopic evaluation of stained tissue specimens affixed on glass slides. Over the last decade, new high throughput digital scanning microscopes have ushered in the era of digital pathology that, along with recent advances in machine vision, have opened up new possibilities for Computer-Aided-Diagnoses. Despite these advances, the high infrastructural costs related to digital pathology and the perception that the digitization process is an additional and nondirectly reimbursable step have challenged its widespread adoption. Here, we discuss how emerging virtual staining technologies and machine learning can help to disrupt the standard histopathology workflow and create new avenues for the diagnostic paradigm that will benefit patients and healthcare systems alike via digital pathology.

Mid-infrared frequency combs at 10 GHz

We demonstrate mid-infrared (MIR) frequency combs at 10 GHz repetition rate via intra-pulse difference-frequency generation (DFG) in quasi-phase-matched nonlinear media. Few-cycle pump pulses (≲15fs, 100 pJ) from a near-infrared electro-optic frequency comb are provided via nonlinear soliton-like compression in photonic-chip silicon-nitride waveguides. Subsequent intra-pulse DFG in periodically poled lithium niobate waveguides yields MIR frequency combs in the 3.1-4.8 µm region, while orientation-patterned gallium phosphide provides coverage across 7-11 µm. Cascaded second-order nonlinearities simultaneously provide access to the carrier-envelope-offset frequency of the pump source via in-line f-2f nonlinear interferometry. The high-repetition rate MIR frequency combs introduced here can be used for condensed phase spectroscopy and applications such as laser heterodyne radiometry.

K-means clustering of coherent Raman spectra from extracellular vesicles visualized by label-free multiphoton imaging

Extracellular vesicles (EVs) have emerged as potential biomarkers in cancer research and for clinical diagnosis. Little is known, however, about their spatial distributions in tissue and the different subpopulations that may exist. Here we report the use of label-free nonlinear optical imaging techniques to provide spatially resolved chemical information of EVs within untreated tissues. A multimodal nonlinear optical imaging system incorporating multiphoton autofluorescence and hyperspectral coherent anti-Stokes Raman scattering (CARS) imaging was built to visualize the spatial tissue distribution and probe the spectra of EVs. K-means clustering is performed on the CARS spectra from EVs in rat mammary tissues and human breast tumor tissue to reveal both the spatial distribution of EV clusters and their different chemical signatures. Correlations are identified between EV clusters and metabolic information.

Label-free identification of early gastrointestinal neuroendocrine tumors via biomedical multiphoton microscopy and automatic image analysis

At present, early diagnosis and treatment is the most effective way to treat early gastrointestinal neuroendocrine tumors. Therefore, we attempted to carry out multiphoton imaging of early neuroendocrine tumors because of its ability to label-free image tissue microstructure at the cellular level. Imaging results show that this imaging technique can quickly identify the histopathological changes in mucosa and submucosa caused by tumor invasion. Furthermore, we performed automatic image analysis on SHG images and extracted two optical diagnostic features-collagen density and average intensity, and also found obvious differences in the density as well as average intensity of collagen fibers in tumor microenvironment using a series of quantitative analysis. These findings may further facilitate the development of multiphoton microscopic imaging technique for clinical use.

Digital synthesis of histological stains using micro-structured and multiplexed virtual staining of label-free tissue

Histological staining is a vital step in diagnosing various diseases and has been used for more than a century to provide contrast in tissue sections, rendering the tissue constituents visible for microscopic analysis by medical experts. However, this process is time consuming, labour intensive, expensive and destructive to the specimen. Recently, the ability to virtually stain unlabelled tissue sections, entirely avoiding the histochemical staining step, has been demonstrated using tissue-stain-specific deep neural networks. Here, we present a new deep-learning-based framework that generates virtually stained images using label-free tissue images, in which different stains are merged following a micro-structure map defined by the user. This approach uses a single deep neural network that receives two different sources of information as its input: (1) autofluorescence images of the label-free tissue sample and (2) a "digital staining matrix", which represents the desired microscopic map of the different stains to be virtually generated in the same tissue section. This digital staining matrix is also used to virtually blend existing stains, digitally synthesizing new histological stains. We trained and blindly tested this virtual-staining network using unlabelled kidney tissue sections to generate micro-structured combinations of haematoxylin and eosin (H&E), Jones' silver stain, and Masson's trichrome stain. Using a single network, this approach multiplexes the virtual staining of label-free tissue images with multiple types of stains and paves the way for synthesizing new digital histological stains that can be created in the same tissue cross section, which is currently not feasible with standard histochemical staining methods.

Use of Deep Learning to Develop and Analyze Computational Hematoxylin and Eosin Staining of Prostate Core Biopsy Images for Tumor Diagnosis

IMPORTANCE

Histopathological diagnoses of tumors from tissue biopsy after hematoxylin and eosin (H&E) dye staining is the criterion standard for oncological care, but H&E staining requires trained operators, dyes and reagents, and precious tissue samples that cannot be reused.

OBJECTIVES

To use deep learning algorithms to develop models that perform accurate computational H&E staining of native nonstained prostate core biopsy images and to develop methods for interpretation of H&E staining deep learning models and analysis of computationally stained images by computer vision and clinical approaches.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study used hundreds of thousands of native nonstained RGB (red, green, and blue channel) whole slide image (WSI) patches of prostate core tissue biopsies obtained from excess tissue material from prostate core biopsies performed in the course of routine clinical care between January 7, 2014, and January 7, 2017, at Brigham and Women's Hospital, Boston, Massachusetts. Biopsies were registered with their H&E-stained versions. Conditional generative adversarial neural networks (cGANs) that automate conversion of native nonstained RGB WSI to computational H&E-stained images were then trained. Deidentified whole slide images of prostate core biopsy and medical record data were transferred to Massachusetts Institute of Technology, Cambridge, for computational research. Results were shared with physicians for clinical evaluations. Data were analyzed from July 2018 to February 2019.

MAIN OUTCOMES AND MEASURES

Methods for detailed computer vision image analytics, visualization of trained cGAN model outputs, and clinical evaluation of virtually stained images were developed. The main outcome was interpretable deep learning models and computational H&E-stained images that achieved high performance in these metrics.

RESULTS

Among 38 patients who provided samples, single core biopsy images were extracted from each whole slide, resulting in 102 individual nonstained and H&E dye-stained image pairs that were compared with matched computationally stained and unstained images. Calculations showed high similarities between computationally and H&E dye-stained images, with a mean (SD) structural similarity index (SSIM) of 0.902 (0.026), Pearson correlation coefficient (PCC) of 0.962 (0.096), and peak signal to noise ratio (PSNR) of 22.821 (1.232) dB. A second cGAN performed accurate computational destaining of H&E-stained images back to their native nonstained form, with a mean (SD) SSIM of 0.900 (0.030), PCC of 0.963 (0.011), and PSNR of 25.646 (1.943) dB compared with native nonstained images. A single blind prospective study computed approximately 95% pixel-by-pixel overlap among prostate tumor annotations provided by 5 board certified pathologists on computationally stained images, compared with those on H&E dye-stained images. This study also used the first visualization and explanation of neural network kernel activation maps during H&E staining and destaining of RGB images by cGANs. High similarities between kernel activation maps of computationally and H&E-stained images (mean-squared errors <0.0005) provide additional mathematical and mechanistic validation of the staining system.

CONCLUSIONS AND RELEVANCE

These findings suggest that computational H&E staining of native unlabeled RGB images of prostate core biopsy could reproduce Gleason grade tumor signatures that were easily assessed and validated by clinicians. Methods for benchmarking, visualization, and clinical validation of deep learning models and virtually H&E-stained images communicated in this study have wide applications in clinical informatics and oncology research. Clinical researchers may use these systems for early indications of possible abnormalities in native nonstained tissue biopsies prior to histopathological workflows.

Passively synchronized mode-locked fiber lasers for coherent anti-Stokes Raman imaging

We have proposed and implemented a polarization-maintaining passively synchronized fiber laser system, which could deliver tunable dual-color picosecond pulses by including a frequency-doubling module and a spectral broadening module. Specifically, the output from the involved Er-doped fiber laser were used to generate second-harmonic pulses at 790 nm with a quadratic nonlinear crystal. In parallel, the amplified pulses from the synchronized Yb-doped fiber laser were launched into a 150-m single mode fiber, which resulted in not only substantial spectral bandwidth broadening from 0.1 to 20.1 nm, but also a significant Raman-induced signal around 1080 nm. Consequently, narrow spectra from 1018-1051 nm and 1070-1095 nm could be continuously tuned via a tunable bandpass filter, corresponding to Raman bonds from 2835-3143 cm^-1 and 3312-3525 cm^-1. Finally, the achieved tunable synchronized pulses enabled us to microscopically examine mouse ear samples based on coherent anti-Stokes Raman and second harmonic generation imaging. Therefore, our tunable passively-synchronized fiber laser system would be promising to provide a simple and compact laser source for subsequent coherent Raman microscopy.

Serial optical coherence microscopy for label-free volumetric histopathology

The observation of histopathology using optical microscope is an essential procedure for examination of tissue biopsies or surgically excised specimens in biological and clinical laboratories. However, slide-based microscopic pathology is not suitable for visualizing the large-scale tissue and native 3D organ structure due to its sampling limitation and shallow imaging depth. Here, we demonstrate serial optical coherence microscopy (SOCM) technique that offers label-free, high-throughput, and large-volume imaging of ex vivo mouse organs. A 3D histopathology of whole mouse brain and kidney including blood vessel structure is reconstructed by deep tissue optical imaging in serial sectioning techniques. Our results demonstrate that SOCM has unique advantages as it can visualize both native 3D structures and quantitative regional volume without introduction of any contrast agents.

High-contrast, fast chemical imaging by coherent Raman scattering using a self-synchronized two-colour fibre laser

Coherent Raman scattering (CRS) microscopy is widely recognized as a powerful tool for tackling biomedical problems based on its chemically specific label-free contrast, high spatial and spectral resolution, and high sensitivity. However, the clinical translation of CRS imaging technologies has long been hindered by traditional solid-state lasers with environmentally sensitive operations and large footprints. Ultrafast fibre lasers can potentially overcome these shortcomings but have not yet been fully exploited for CRS imaging, as previous implementations have suffered from high intensity noise, a narrow tuning range and low power, resulting in low image qualities and slow imaging speeds. Here, we present a novel high-power self-synchronized two-colour pulsed fibre laser that achieves excellent performance in terms of intensity stability (improved by 50 dB), timing jitter (24.3 fs), average power fluctuation (<0.5%), modulation depth (>20 dB) and pulse width variation (<1.8%) over an extended wavenumber range (2700-3550 cm-1). The versatility of the laser source enables, for the first time, high-contrast, fast CRS imaging without complicated noise reduction via balanced detection schemes. These capabilities are demonstrated in this work by imaging a wide range of species such as living human cells and mouse arterial tissues and performing multimodal nonlinear imaging of mouse tail, kidney and brain tissue sections by utilizing second-harmonic generation and two-photon excited fluorescence, which provides multiple optical contrast mechanisms simultaneously and maximizes the gathered information content for biological visualization and medical diagnosis. This work also establishes a general scenario for remodelling existing lasers into synchronized two-colour lasers and thus promotes a wider popularization and application of CRS imaging technologies.

Label-free multiphoton imaging to assess neoadjuvant therapy responses in breast carcinoma

Neoadjuvant chemotherapy has been used increasingly in patients with early-stage or locally advanced breast carcinoma, and has been recommended as a general approach in locally advanced-stage diseases. Assessing therapy response could offer prognostic information to help determine subsequent nursing plan; particularly it is essential to identify responders and non-responders for the sake of helping develop follow-up treatment strategies. However, at present, diagnostic accuracy of preoperative clinical examination are still not satisfactory. Here we presented an alternate approach to monitor tumor and stroma changes associated with neoadjuvant therapy responses in breast carcinoma, with a great potential for becoming a new diagnostic tool—multiphoton microscopy. Imaging results showed that multiphoton imaging techniques have the ability to label-freely visualize tumor response such as tumor necrosis, and stromal response including fibrosis, mucinous response, inflammatory response as well as vascular hyperplasia in situ at cellular and subcellular levels. Moreover, using automated image analysis and a set of scoring methods, we found significant differences in the area of cell nucleus and in the content of collagen fibers between the pre-treatment and post-treatment breast carcinoma tissues. In summary, this study was conducted to pathologically evaluate the response of breast carcinoma to preoperative chemotherapy as well as to assess the efficacy of multiphoton microscopy in detecting these pathological changes, and experimental results demonstrated that this microscope may be a promising tool for label-free, real-time assessment of treatment response without the use of any exogenous contrast agents.

Epithelium segmentation and automated Gleason grading of prostate cancer via deep learning in label-free multiphoton microscopic images

In the current clinical care practice, Gleason grading system is one of the most powerful prognostic predictors for prostate cancer (PCa). The grading system is based on the architectural pattern of cancerous epithelium in histological images. However, the standard procedure of histological examination often involves complicated tissue fixation and staining, which are time-consuming and may delay the diagnosis and surgery. In this study, label-free multiphoton microscopy (MPM) was used to acquire subcellular-resolution images of unstained prostate tissues. Then, a deep learning architecture (U-net) was introduced for epithelium segmentation of prostate tissues in MPM images. The obtained segmentation results were then merged with the original MPM images to train a classification network (AlexNet) for automated Gleason grading. The developed method achieved an overall pixel accuracy of 92.3% with a mean F1 score of 0.839 for epithelium segmentation. By merging the segmentation results with the MPM images, the accuracy of Gleason grading was improved from 72.42% to 81.13% in hold-out test set. Our results suggest that MPM in combination with deep learning holds the potential to be used as a fast and powerful clinical tool for PCa diagnosis.

Automated label-free detection of injured neuron with deep learning by two-photon microscopy

Stroke is a significant cause of morbidity and long-term disability globally. Detection of injured neuron is a prerequisite for defining the degree of focal ischemic brain injury, which can be used to guide further therapy. Here, we demonstrate the capability of two-photon microscopy (TPM) to label-freely identify injured neurons on unstained thin section and fresh tissue of rat cerebral ischemia-reperfusion model, revealing definite diagnostic features compared with conventional staining images. Moreover, a deep learning model based on convolutional neural network is developed to automatically detect the location of injured neurons on TPM images. We then apply deep learning-assisted TPM to evaluate the ischemic regions based on tissue edema, two-photon excited fluorescence signal intensity, as well as neuronal injury, presenting a novel manner for identifying the infarct core, peri-infarct area, and remote area. These results propose an automated and label-free method that could provide supplementary information to augment the diagnostic accuracy, as well as hold the potential to be used as an intravital diagnostic tool for evaluating the effectiveness of drug interventions and predicting potential therapeutics.

Design guidelines for normal-dispersion fiber optical parametric chirped-pulse amplifiers

We theoretically investigate methods of controlling pulse generation in normal-dispersion fiber optical parametric chirped-pulse amplifiers. We focus on high-energy, ultrashort pulses at wavelengths widely separated from that of the pump, and find that within this regime, a number of simple properties describe the essential phase and gain dynamics. Of primary importance are the relationships between the chirps of the pump, seed, and parametric gain, which we theoretically predict and then experimentally validate. By properly arranging these parameters, the signal and idler waves can be widely customized to fulfill a remarkable range of application requirements, spanning from narrowband to few-cycle.

Label-free whole-colony imaging and metabolic analysis of metastatic pancreatic cancer by an autoregulating flexible optical system

Cancer metastasis is a Gordian knot for tumor diagnosis and therapy. Many studies have demonstrated that metastatic processes are inevitably affected by the tumor microenvironment. Histopathology is used universally as the gold standard for cancer diagnosis despite the lengthy preparation process and invasiveness.

Methods: Here, we introduced a supercontinuum and super-wide-tuning integrated multimodal platform, which combines the confocal, nonlinear and fluorescence lifetime microscopy with autoregulations, for label-free evaluation of fresh tissue and pathological sections. Based on various automated tunable lasers, synchronized and self-adjusting components and eight fast switching detection channels, the system features fast, large-field and subcellular-scale imaging of exogenous and endogenous fluorophores, nonlinear coherent scattering and lifetime contrast.

Results: With such an integrated multi-dimensional system, we searched the metastatic region by two-photon and three-photon excited autofluorescence, analyzed the cancer invasion by second harmonic generation and revealed the affected cellular metabolism by phasor-lifetime. We demonstrated the flexible measurement of multiple nonlinear modalities at NIR I and II excitation with a pre-compensation for group delay dispersion of ~7,000 fs² and low power of <40 mW, and of dual autofluorescence lifetime decays for phasor approach to decompose cancer-associated and disassociated components. This significantly revealed the metastatic and metabolic optical signatures of the whole colony of pancreatic cancers.

Conclusion: The synergistic effect of the system demonstrates the great potential to translate this technique into routine clinical applications, particularly for large-scale and quantitative studies of metastatic colonization.

Real-time intraoperative diagnosis by deep neural network driven multiphoton virtual histology

Recent advances in label-free virtual histology promise a new era for real-time molecular diagnosis in the operating room and during biopsy procedures. To take full advantage of the rich, multidimensional information provided by these technologies, reproducible and reliable computational tools that could facilitate the diagnosis are in great demand. In this study, we developed a deep-learning-based framework to recognize cancer versus normal human breast tissue from real-time label-free virtual histology images, with a tile-level AUC (area under receiver operating curve) of 95% and slide-level AUC of 100% on unseen samples. Furthermore, models trained on a high-quality laboratory-generated dataset can generalize to independent datasets acquired from a portable intraoperative version of the imaging technology with a physics-based adapted design. Classification activation maps and final feature visualization revealed discriminative patterns, such as tumor cells and tumor-associated vesicles, that are highly associated with cancer status. These results demonstrate that through the combination of real-time virtual histopathology and a deep-learning framework, accurate real-time diagnosis could be achieved in point-of-procedure clinical applications.

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.

Multiphoton microscopy in surgical oncology- a systematic review and guide for clinical translatability

BACKGROUND

Multiphoton microscopy (MPM) facilitates three-dimensional, high-resolution functional imaging of unlabeled tissues in vivo and ex vivo. This systematic review discusses the diagnostic value, advantages and challenges in the practical use of MPM in surgical oncology.

METHOD AND FINDINGS

A Medline search was conducted in April 2019. Fifty-three original research papers investigating MPM compared to standard histology in human patients with solid tumors were identified. A qualitative synopsis and meta-analysis of 14 blinded studies was performed. Risk of bias and applicability were evaluated. MPM can image fresh, frozen or fixed tissues up to a depth 1000 μm in the z-plane. Best results including functional imaging and virtual histochemistry are obtained by in vivo imaging or scanning fresh tissue immediately after excision. Two-photon excited fluorescence by natural fluorophores of the cytoplasm and second harmonic generation signals by fluorophores of the extracellular matrix can be scanned simultaneously, providing high resolution optical histochemistry comparable to standard histology. Functional parameters like fluorescence lifetime imaging or optical redox ratio provide additional objective information. A major concern is inability to visualize the nucleus. However, in a subpopulation analysis of 440 specimens, MPM yielded a sensitivity of 94%, specificity of 96% and accuracy of 95% for the detection of malignant tissue.

CONCLUSION

MPM is a promising emerging technique in surgical oncology. Ex vivo imaging has high sensitivity, specificity and accuracy for the detection of tumor cells. For broad clinical application in vivo, technical challenges need to be resolved.

Optimal compressive multiphoton imaging at depth using single-pixel detection

Compressive sensing can overcome the Nyquist criterion and record images with a fraction of the usual number of measurements required. However, conventional measurement bases are susceptible to diffraction and scattering, prevalent in high-resolution microscopy. In this Letter, we explore the random Morlet basis as an optimal set for compressive multiphoton imaging, based on its ability to minimize the space-frequency uncertainty. We implement this approach for wide-field multiphoton microscopy with single-pixel detection, which allows imaging through turbid media without correction. The Morlet basis promises a route for rapid acquisition with lower photodamage.

Quantitative assessment of microenvironment characteristics and metabolic activity in glioma via multiphoton microscopy

Tumor microenvironment and metabolic activity in gliomas are the important biomarkers to evaluate the progression of gliomas. Many evidences have suggested that the targeting of metabolic activity and tumor microenvironment simultaneously can be more effective to take the tumor therapy. Therefore, the noninvasive, accurate assessment of tumor microenvironment and metabolic activity is quite important in clinical practice. Multiphoton microscopy (MPM), based on two-photon-excited fluorescence and second harmonic generation was performed on unstained glioma tissues. With our combined image analysis approaches, our research findings indicate that MPM is able to qualitatively and quantitatively describe the microenvironment characteristics in gliomas, such as collage deposition in extracellular matrix, lymphocyte infiltration and tumor angiogenesis, etc. Meanwhile, the metabolic activity can also be quantitatively evaluated by optical redox ratio, NADH and FAD intensity. With the microendoscope and fiberscope are portable, MPM technique can be used to perform in-vivo studies and clinical examinations in gliomas.

Simultaneous label-free autofluorescence-multiharmonic microscopy and beyond

Without sophisticated data inversion algorithms, nonlinear optical microscopy can acquire images at subcellular resolution and relatively large depth, with plausible endogenous contrasts indicative of authentic biological and pathological states. Although independent contrasts have been derived by sequentially imaging the same sample plane or volume under different and often optimized excitation conditions, new laser source engineering with inputs from key biomolecules surprisingly enable real-time simultaneous acquisition of multiple endogenous molecular contrasts to segment a rich set of cellular and extracellular components. Since this development allows simple single-beam single-shot excitation and simultaneous multicontrast epidirected signal detection, the resulting platform avoids perturbative sample pretreatments such as fluorescent labeling, mechanical sectioning, scarce or interdependent contrast generation, constraints to the sample or imaging geometry, and intraimaging motion artifacts that have limited in vivo nonlinear optical molecular imaging.

Glutathione-Priming Nanoreactors Enable Fluorophore Core/Shell Transition for Precision Cancer Imaging

In an attempt to develop an imaging probe with ultra-high sensitivity for a broad range of tumors in vivo and inspired by the concept of chemical synthetic nanoreactors, we designed a type of glutathione-priming fluorescent nanoreactor (GPN) with an albumin-coating shell and hydrophobic polymer core containing disulfide bonds, protonatable blocks, and indocyanine green (ICG), a near-infrared fluorophore. The albumin played multiple roles including biocompatible carriers, hydrophilic stabilizer, "receptor" of the fluorophores, and even targeting molecules. The protonation of the hydrophobic core triggered the outside-to-core transport of acidic glutathione (GSH), as well as the core-to-shell transference of ICGs after the disulfide bond cleavage by GSH, which induced strong binding of fluorophores with albumins on the GPN shell, initiating intensive fluorescence signals. As a result, the GPNs demonstrated extremely high response sensitivity and imaging contrast, proper time window, and broad cancer specificity. In fact, an orthogonal activation pattern was found in vitro with an ON/OFF ratio up to 24.7-fold. Furthermore, the nanoprobes specifically amplified the tumor signals in five cancer-bearing mouse models and actualized tumor margin delineation with a contrast up to 20-fold, demonstrating much better imaging efficacy than the other four commercially available probes. Therefore, the GPNs provide a new paradigm in developing high-performance bioresponsive nanoprobes.

All-optical Reflection-mode Microscopic Histology of Unstained Human Tissues

Surgical oncologists depend heavily on visual field acuity during cancer resection surgeries for in-situ margin assessment. Clinicians must wait up to two weeks for results from a pathology lab to confirm a post-operative diagnosis, potentially resulting in subsequent treatments. Currently, there are no clinical tools that can visualize diagnostically pertinent tissue information in-situ. Here, we present the first microscopy capable of non-contact label-free visualization of human cellular morphology in a reflection-mode apparatus. This is possible with the recently reported imaging modality called photoacoustic remote sensing microscopy which enables non-contact detection of optical absorption contrast. By taking advantage of the 266-nanometer optical absorption peak of DNA, photoacoustic remote sensing is efficacious in recovering qualitatively similar nuclear information in comparison to that provided by the hematoxylin stain in the gold-standard hematoxylin and eosin (H&E) prepared samples. A photoacoustic remote sensing system was employed utilizing a 266-nanometer pulsed excitation beam to induce photoacoustic pressures within the sample resulting in refractive index modulation of the optical absorber. A 1310-nanometer continuous-wave interrogation beam detects these perturbed regions as back reflected intensity variations due to the changes in the local optical properties. Using this technique, clinically useful histologic images of human tissue samples including breast cancer (invasive ductal carcinoma), tonsil, gastrointestinal, and pancreatic tissue images were formed. These were qualitatively comparable to standard H&E prepared samples.

Portable all-fiber dual-output widely tunable light source for coherent Raman imaging

We present a rapidly tunable dual-output all-fiber light source for coherent Raman imaging, based on a dispersively matched mode-locked laser pumping a parametric oscillator. Output pump and Stokes pulses with a maximal power of 170 and 400 mW, respectively, and equal durations of 7 ps could be generated. The tuning mechanism required no mechanical delay line, enabling all-electronic arbitrary wavelength switching across more than 2700  cm - 1 in less than 5 ms. The compact setup showed a reliable operation despite mechanical shocks of more than 25  m / s 2 and is, thus, well suited for operation in a mobile cart. Imaging mouse and human skin tissue with both the portable light source and a commercial laboratory-bound reference system yielded qualitatively equal results and verified the portable light source being well suited for coherent Raman microscopy.