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.

Suppressing Short-term Polarization Noise and Related Spectral Decoherence in All-normal Dispersion Fiber Supercontinuum Generation.

The supercontinuum generated exclusively in the normal dispersion regime of a nonlinear fiber is widely believed to possess low optical noise and high spectral coherence. The recent development of flattened all-normal dispersion fibers has been motivated by this belief to construct a general-purpose broadband coherent optical source. Somewhat surprisingly, we identify a large short-term polarization noise in this type of supercontinuum generation that has been masked by the total-intensity measurement in the past, but can be easily detected by filtering the supercontinuum with a linear polarizer. Fortunately, this hidden intrinsic noise and the accompanied spectral decoherence can be effectively suppressed by using a polarization-maintaining all-normal dispersion fiber. A polarization-maintaining coherent supercontinuum laser is thus built with a broad bandwidth (780-1300 nm) and high spectral power (~1 mW/nm).

High-fidelity and high-speed wavefront shaping by leveraging complex media.

High-precision light manipulation is crucial for delivering information through complex media. However, existing spatial light modulation devices face a fundamental speed-fidelity tradeoff. Digital micromirror devices have emerged as a promising candidate for high-speed wavefront shaping but at the cost of compromised fidelity due to the limited control degrees of freedom. Here, we leverage the sparse-to-random transformation through complex media to overcome the dimensionality limitation of spatial light modulation devices. We demonstrate that pattern compression by sparsity-constrained wavefront optimization allows sparse and robust wavefront representations in complex media, improving the projection fidelity without sacrificing frame rate, hardware complexity, or optimization time. Our method is generalizable to different pattern types and complex media, supporting consistent performance with up to 89% and 126% improvements in projection accuracy and speckle suppression, respectively. The proposed optimization framework could enable high-fidelity high-speed wavefront shaping through different scattering media and platforms without changes to the existing holographic setups, facilitating a wide range of physics and real-world applications.

Spectral-temporal-spatial customization via modulating multimodal nonlinear pulse propagation.

Multimode fibers (MMFs) are gaining renewed interest for nonlinear effects due to their high-dimensional spatiotemporal nonlinear dynamics and scalability for high power. High-brightness MMF sources with effective control of the nonlinear processes would offer possibilities in many areas from high-power fiber lasers, to bioimaging and chemical sensing, and to intriguing physics phenomena. Here we present a simple yet effective way of controlling nonlinear effects at high peak power levels. This is achieved by leveraging not only the spatial but also the temporal degrees of freedom during multimodal nonlinear pulse propagation in step-index MMFs, using a programmable fiber shaper that introduces time-dependent disorders. We achieve high tunability in MMF output fields, resulting in a broadband high-peak-power source. Its potential as a nonlinear imaging source is further demonstrated through widely tunable two-photon and three-photon microscopy. These demonstrations provide possibilities for technology advances in nonlinear optics, bioimaging, spectroscopy, optical computing, and material processing.

EventLFM: event camera integrated Fourier light field microscopy for ultrafast 3D imaging.

Ultrafast 3D imaging is indispensable for visualizing complex and dynamic biological processes. Conventional scanning-based techniques necessitate an inherent trade-off between acquisition speed and space-bandwidth product (SBP). Emerging single-shot 3D wide-field techniques offer a promising alternative but are bottlenecked by the synchronous readout constraints of conventional CMOS systems, thus restricting data throughput to maintain high SBP at limited frame rates. To address this, we introduce EventLFM, a straightforward and cost-effective system that overcomes these challenges by integrating an event camera with Fourier light field microscopy (LFM), a state-of-the-art single-shot 3D wide-field imaging technique. The event camera operates on a novel asynchronous readout architecture, thereby bypassing the frame rate limitations inherent to conventional CMOS systems. We further develop a simple and robust event-driven LFM reconstruction algorithm that can reliably reconstruct 3D dynamics from the unique spatiotemporal measurements captured by EventLFM. Experimental results demonstrate that EventLFM can robustly reconstruct fast-moving and rapidly blinking 3D fluorescent samples at kHz frame rates. Furthermore, we highlight EventLFM's capability for imaging of blinking neuronal signals in scattering mouse brain tissues and 3D tracking of GFP-labeled neurons in freely moving C. elegans. We believe that the combined ultrafast speed and large 3D SBP offered by EventLFM may open up new possibilities across many biomedical applications.

Roadmap on Deep Learning for Microscopy.

Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasing resolution and throughput. Artificial intelligence, deep neural networks, and machine learning are all niche terms describing computational methods that have gained a pivotal role in microscopy-based research over the past decade. This Roadmap is written collectively by prominent researchers and encompasses selected aspects of how machine learning is applied to microscopy image data, with the aim of gaining scientific knowledge by improved image quality, automated detection, segmentation, classification and tracking of objects, and efficient merging of information from multiple imaging modalities. We aim to give the reader an overview of the key developments and an understanding of possibilities and limitations of machine learning for microscopy. It will be of interest to a wide cross-disciplinary audience in the physical sciences and life sciences.

Label-free optical redox ratio from urinary extracellular vesicles as a screening biomarker for bladder cancer.

Extracellular vesicles (EVs) have been studied for their potential applications in cancer screening, diagnosis, and treatment monitoring. Most studies have focused on the bulk content of EVs; however, it is also informative to investigate their metabolic status, and changes under different physiological and environmental conditions. In this study, noninvasive, multimodal, label-free nonlinear optical microscopy was used to evaluate the optical redox ratio of large EVs (microvesicles) isolated from the urine of 11 dogs in three cohorts (4 healthy, 4 transitional cell carcinoma (TCC) of the bladder, and 3 prostate cancer). The optical redox ratio is a common metric comparing the autofluorescence intensities of metabolic cofactors FAD and NAD(P)H to characterize the metabolic profile of cells and tissues, and has recently been applied to EVs. The optical redox ratio revealed that dogs with TCC of the bladder had a more than 2-fold increase in NAD(P)H-rich urinary EVs (uEVs) when compared to healthy dogs, whereas dogs with prostate cancer had no significant difference. The optical redox ratio values of uEVs kept at -20°C for 48 hours were significantly different from those of freshly isolated uEVs, indicating that this parameter is more reliable when assessing freshly isolated uEVs. These results suggest that the label-free optical redox ratio of uEVs, indicating relative rates of glycolysis and oxidative phosphorylation of parent cells and tissues, may act as a potential screening biomarker for bladder cancer.

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.

The Cholesterol Metabolite 27HC Increases Secretion of Extracellular Vesicles Which Promote Breast Cancer Progression.

Cholesterol has been implicated in the clinical progression of breast cancer, a disease that continues to be the most commonly diagnosed cancer in women. Previous work has identified the cholesterol metabolite 27-hydroxycholesterol (27HC) as a major mediator of the effects of cholesterol on breast tumor growth and progression. 27HC can act as an estrogen receptor (ER) modulator to promote the growth of ERα+ tumors, and as a liver X receptor (LXR) ligand in myeloid immune cells to establish an immune-suppressive program. In fact, the metastatic properties of 27HC require the presence of myeloid cells with neutrophils (polymorphonuclear neutrophils; PMNs) being essential for the increase in lung metastasis in murine models. In an effort to further elucidate the mechanisms by which 27HC alters breast cancer progression, we made the striking finding that 27HC promoted the secretion of extracellular vesicles (EVs), a diverse assortment of membrane bound particles that includes exosomes. The resulting EVs had a size distribution that was skewed slightly larger than EVs generated by treating cells with vehicle. The increase in EV secretion and size was consistent across 3 different subtypes: primary murine PMNs, RAW264.7 monocytic cells, and 4T1 murine mammary cancer cells. Label-free analysis of 27HC-EVs indicated that they had a different metabolite composition to those from vehicle-treated cells. Importantly, 27HC-EVs from primary PMNs promoted tumor growth and metastasis in 2 different syngeneic models, demonstrating the potential role of 27HC-induced EVs in the progression of breast cancer. EVs from PMNs were taken up by cancer cells, macrophages, and PMNs, but not T cells. Since EVs did not alter proliferation of cancer cells, it is likely that their protumor effects are mediated through interactions with myeloid cells. Interestingly, RNA-seq analysis of tumors from 27HC-EV-treated mice do not display significantly altered transcriptomes, suggesting that the effects of 27HC-EVs occur early on in tumor establishment and growth. Future work will be required to elucidate the mechanisms by which 27HC increases EV secretion, and how these EVs promote breast cancer progression. Collectively, however, our data indicate that EV secretion and content can be regulated by a cholesterol metabolite, which may have detrimental effects in terms of disease progression, important findings given the prevalence of both breast cancer and hypercholesterolemia.

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.

Label-free molecular profiling for identification of biomarkers in carcinogenesis using multimodal multiphoton imaging.

BACKGROUND: Label-free molecular profiling, imaging, and analysis are of particular interest in cancer biology for detecting subtle biochemical changes during cancer progression and potentially during cancer treatment. Multimodal, multiphoton imaging that combines diverse molecular contrasts derived from different physical mechanisms can improve our understanding of the tumor microenvironment. METHODS: A label-free optical molecular profiling technique has been developed based on penta-modal multiphoton imaging to investigate mammary tumor progression in a pre-clinical rat model. Pulses from a coherent supercontinuum were tailored for two-photon (2PF) and three-photon fluorescence (3PF), second (SHG) and third harmonic generation (THG), and hyperspectral coherent anti-Stokes Raman scattering (CARS)-based imaging. A graphic multiphoton molecular profiling model was constructed to intuitively combine the co-registered quantitative, chemical, functional, and structural tissue information, enabling longitudinal in situ biomolecular analysis. RESULTS: Over a 9-week period of tumor progression, and even before the formation of solid tumor, we observed lipid-protein transitions, microenvironmental reorganization, and a shift from FAD to NAD(P)H fluorescence, which reflects the reprogramming of cellular metabolism in carcinogenesis. CONCLUSIONS: Multimodal multiphoton imaging reveals and interrelates diverse carcinogenic signatures, identifying biomarkers that could serve as early molecular indicators for breast cancer diagnosis. This quantitative multimodal imaging methodology for molecular profiling of associated cancer biomarkers may have a broader impact in fundamental cancer research and future clinical applications.

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.

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.

Slide-free virtual histochemistry (Part I): development via nonlinear optics.

Histochemistry is a microscopy-based technology widely used to visualize the molecular distribution in biological tissue. Recent developments in label-free optical imaging has demonstrated the potential to replace the conventional histochemical labels/markers (fluorescent antibodies, organic dyes, nucleic acid probes, and other contrast agents) with diverse optical interactions to generate histochemical contrasts, allowing "virtual" histochemistry in three spatial dimensions without preparing a microscope slide (i.e. labor-intensive sample preparation). However, the histochemical information in a label-free optical image has often been rather limited due to the difficulty in simultaneously generating multiple histochemical contrasts with strict spatial co-registration. Here, in the first part (Part I) of this two-part series study, we develop a technique of slide-free virtual histochemistry based on label-free multimodal multiphoton microscopy, and simultaneously generate up to four histochemical contrasts from in vivo animal and ex vivo human tissue. To enable this functionality, we construct and demonstrate a robust fiber-based laser source for clinical translation and phenotype a wide variety of vital cells in unperturbed mammary tissue.

Slide-free virtual histochemistry (Part II): detection of field cancerization.

Tumor-adjacent "normal" tissue constitutes a peri-tumoral field that affects early cancer detection, risk assessment, surgical decision, and postoperative surveillance. Modern genetic analysis has revealed valuable information from this field, but without the spatial resolution of optical microscopy to understand the vital microenvironments that surround individual cells. Rapidly advanced optical imaging techniques free of labor-intensive sample preparation, despite great promise to perform slide-free imaging of cell structure and shift the histology-centered cancer diagnostic paradigm, have lacked compatible and complementary histochemical imaging of cell function or phenotype to interrogate the peri-tumoral field. In the first part (Part I) of this two-part series study, we developed a technique of slide-free virtual histochemistry to phenotype various cells in in vivo animal and ex vivo human tissue. Here, in the second part (Part II) of this two-part series study, we employ this technique to examine various peri-tumoral fields and produce the volumetric histochemical evidence of field cancerization consistent with the structural changes at larger spatial scales. We also link the field cancerization with cancer dormancy in a significant portion of breast cancer patients.

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.

Intraoperative visualization of the tumor microenvironment and quantification of extracellular vesicles by label-free nonlinear imaging.

Characterization of the tumor microenvironment, including extracellular vesicles (EVs), is important for understanding cancer progression. EV studies have traditionally been performed on dissociated cells, lacking spatial information. Since the distribution of EVs in the tumor microenvironment is associated with cellular function, there is a strong need for visualizing EVs in freshly resected tissues. We intraoperatively imaged untreated human breast tissues using a custom nonlinear imaging system. Label-free optical contrasts of the tissue, correlated with histological findings, enabled point-of-procedure characterization of the tumor microenvironment. EV densities from 29 patients with breast cancer were found to increase with higher histologic grade and shorter tumor-to-margin distance and were significantly higher than those from 7 cancer-free patients undergoing breast reduction surgery. Acquisition and interpretation of these intraoperative images not only provide real-time visualization of the tumor microenvironment but also offer the potential to use EVs as a label-free biomarker for cancer diagnosis and prognosis.

Intracellular imaging of docosanol in living cells by coherent anti-Stokes Raman scattering microscopy.

Docosanol is an over-the-counter topical agent that has proved to be one of the most effective therapies for treating herpes simplex labialis. However, the mechanism by which docosanol suppresses lesion formation remains poorly understood. To elucidate its mechanism of action, we investigated the uptake of docosanol in living cells using coherent anti-Stokes Raman scattering microscopy. Based on direct visualization of the deuterated docosanol, we observed highly concentrated docosanol inside living cells 24 h after drug treatment. In addition, different spatial patterns of drug accumulation were observed in different cell lines. In keratinocytes, which are the targeted cells of docosanol, the drug molecules appeared to be docking at the periphery of the cell membrane. In contrast, the drug molecules in fibroblasts appeared to accumulate in densely packed punctate regions throughout the cytoplasm. These results suggest that this molecular imaging approach is suitable for the longitudinal tracking of drug molecules in living cells to identify cell-specific trafficking and may also have implications for elucidating the mechanism by which docosanol suppresses lesion formation.