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

Towards next-generation diagnostic pathology: AI-empowered label-free multiphoton microscopy

Diagnostic pathology, historically dependent on visual scrutiny by experts, is essential for disease detection. Advances in digital pathology and developments in computer vision technology have led to the application of artificial intelligence (AI) in this field. Despite these advancements, the variability in pathologists' subjective interpretations of diagnostic criteria can lead to inconsistent outcomes. To meet the need for precision in cancer therapies, there is an increasing demand for accurate pathological diagnoses. Consequently, traditional diagnostic pathology is evolving towards "next-generation diagnostic pathology", prioritizing on the development of a multi-dimensional, intelligent diagnostic approach. Using nonlinear optical effects arising from the interaction of light with biological tissues, multiphoton microscopy (MPM) enables high-resolution label-free imaging of multiple intrinsic components across various human pathological tissues. AI-empowered MPM further improves the accuracy and efficiency of diagnosis, holding promise for providing auxiliary pathology diagnostic methods based on multiphoton diagnostic criteria. In this review, we systematically outline the applications of MPM in pathological diagnosis across various human diseases, and summarize common multiphoton diagnostic features. Moreover, we examine the significant role of AI in enhancing multiphoton pathological diagnosis, including aspects such as image preprocessing, refined differential diagnosis, and the prognostication of outcomes. We also discuss the challenges and perspectives faced by the integration of MPM and AI, encompassing equipment, datasets, analytical models, and integration into the existing clinical pathways. Finally, the review explores the synergy between AI and label-free MPM to forge novel diagnostic frameworks, aiming to accelerate the adoption and implementation of intelligent multiphoton pathology systems in clinical settings.

Self-Supervised Image Denoising of Third Harmonic Generation Microscopic Images of Human Glioma Tissue by Transformer-Based Blind Spot (TBS) Network

Third harmonic generation (THG) microscopy shows great potential for instant pathology of brain tumor tissue during surgery. However, due to the maximal permitted exposure of laser intensity and inherent noise of the imaging system, the noise level of THG images is relatively high, which affects subsequent feature extraction analysis. Denoising THG images is challenging for modern deep-learning based methods because of the rich morphologies contained and the difficulty in obtaining the noise-free counterparts. To address this, in this work, we propose an unsupervised deep-learning network for denoising of THG images which combines a self-supervised blind spot method and a U-shape Transformer using a dynamic sparse attention mechanism. The experimental results on THG images of human glioma tissue show that our approach exhibits superior denoising performance qualitatively and quantitatively compared with previous methods. Our model achieves an improvement of 2.47-9.50 dB in SNR and 0.37-7.40 dB in CNR, compared to six recent state-of-the-art unsupervised learning models including Neighbor2Neighbor, Blind2Unblind, Self2Self+, ZS-N2N, Noise2Info and SDAP. To achieve an objective evaluation of our model, we also validate our model on public datasets including natural and microscopic images, and our model shows a better denoising performance than several recent unsupervised models such as Neighbor2Neighbor, Blind2Unblind and ZS-N2N. In addition, our model is nearly instant in denoising a THG image, which has the potential for real-time applications of THG microscopy.

Inspiring a convergent engineering approach to measure and model the tissue microenvironment

Understanding the molecular and physical complexity of the tissue microenvironment (TiME) in the context of its spatiotemporal organization has remained an enduring challenge. Recent advances in engineering and data science are now promising the ability to study the structure, functions, and dynamics of the TiME in unprecedented detail; however, many advances still occur in silos that rarely integrate information to study the TiME in its full detail. This review provides an integrative overview of the engineering principles underlying chemical, optical, electrical, mechanical, and computational science to probe, sense, model, and fabricate the TiME. In individual sections, we first summarize the underlying principles, capabilities, and scope of emerging technologies, the breakthrough discoveries enabled by each technology and recent, promising innovations. We provide perspectives on the potential of these advances in answering critical questions about the TiME and its role in various disease and developmental processes. Finally, we present an integrative view that appreciates the major scientific and educational aspects in the study of the TiME.

Rapid and Precise Diagnosis of Retroperitoneal Liposarcoma with Deep-Learned Label-Free Molecular Microscopy

The retroperitoneal liposarcoma (RLPS) is a rare malignancy whose only curative therapy is surgical resection. However, well-differentiated liposarcomas (WDLPSs), one of its most common types, can hardly be distinguished from normal fat during operation without an effective margin assessment method, jeopardizing the prognosis severely with a high recurrence risk. Here, we combined dual label-free nonlinear optical modalities, stimulated Raman scattering (SRS) microscopy and second harmonic generation (SHG) microscopy, to image two predominant tissue biomolecules, lipids and collagen fibers, in 35 RLPSs and 34 normal fat samples collected from 35 patients. The produced dual-modal tissue images were used for RLPS diagnosis based on deep learning. Dramatically decreasing lipids and increasing collagen fibers during tumor progression were reflected. A ResNeXt101-based model achieved 94.7% overall accuracy and 0.987 mean area under the ROC curve (AUC) in differentiating among normal fat, WDLPSs, and dedifferentiated liposarcomas (DDLPSs). In particular, WDLPSs were detected with 94.1% precision and 84.6% sensitivity superior to existing methods. The ablation experiment showed that such performance was attributed to both SRS and SHG microscopies, which increased the sensitivity of recognizing WDLPS by 16.0 and 3.6%, respectively. Furthermore, we utilized this model on RLPS margins to identify the tumor infiltration. Our method holds great potential for accurate intraoperative liposarcoma detection.

Improving the diagnosis of ductal carcinoma in situ with microinvasion without immunohistochemistry: An innovative method with H&E-stained and multiphoton microscopy images

Ductal carcinoma in situ with microinvasion (DCISM) is a challenging subtype of breast cancer with controversial invasiveness and prognosis. Accurate diagnosis of DCISM from ductal carcinoma in situ (DCIS) is crucial for optimal treatment and improved clinical outcomes. However, there are often some suspicious small cancer nests in DCIS, and it is difficult to diagnose the presence of intact myoepithelium by conventional hematoxylin and eosin (H&E) stained images. Although a variety of biomarkers are available for immunohistochemical (IHC) staining of myoepithelial cells, no single biomarker is consistently sensitive to all tumor lesions. Here, we introduced a new diagnostic method that provides rapid and accurate diagnosis of DCISM using multiphoton microscopy (MPM). Suspicious foci in H&E-stained images were labeled as regions of interest (ROIs), and the nuclei within these ROIs were segmented using a deep learning model. MPM was used to capture images of the ROIs in H&E-stained sections. The intensity of two-photon excitation fluorescence (TPEF) in the myoepithelium was significantly different from that in tumor parenchyma and tumor stroma. Through the use of MPM, the myoepithelium and basement membrane can be easily observed via TPEF and second-harmonic generation (SHG), respectively. By fusing the nuclei in H&E-stained images with MPM images, DCISM can be differentiated from suspicious small cancer clusters in DCIS. The proposed method demonstrated good consistency with the cytokeratin 5/6 (CK5/6) myoepithelial staining method (kappa coefficient = 0.818).

Rapid, high-resolution, non-destructive assessments of metabolic and morphological homogeneity uniquely identify high-grade cervical precancerous lesions

Purpose

Two-photon microscopy (2PM) is an emerging clinical imaging modality with the potential to non-invasively assess tissue metabolism and morphology in high-resolution. This study aimed to assess the translational potential of 2PM for improved detection of high-grade cervical precancerous lesions.

Experimental Design

2P images attributed to reduced nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) and oxidized flavoproteins (FP) were acquired from the full epithelial thickness of freshly excised human cervical tissue biopsies (N = 62). Fifteen biopsies harbored high-grade squamous intraepithelial lesions (HSILs), 14 biopsies harbored low-grade SILs (LSILs), and 33 biopsies were benign. Quadratic discriminant analysis (QDA) leveraged morphological and metabolic functional metrics extracted from these images to predict the presence of HSILs. We performed gene set enrichment analysis (GSEA) using datasets available on the Gene Expression Omnibus (GEO) to validate the presence of metabolic reprogramming in HSILs.

Results

Integrating metabolic and morphological 2P-derived metrics from finely sampled, full-thickness epithelia achieved a high 90.8 ± 6.1% sensitivity and 72.3 ± 11.3% specificity of HSIL detection. Notably, sensitivity (91.4 ± 12.0%) and specificity (77.5 ± 12.6%) were maintained when utilizing metrics from only two images at 12- and 72-μm from the tissue surface. Upregulation of glycolysis, fatty acid metabolism, and oxidative phosphorylation in HSIL tissues validated the metabolic reprogramming captured by 2P biomarkers.

Conclusion

Label-free 2P images from as few as two epithelial depths enable rapid and robust HSIL detection through the quantitative characterization of metabolic and morphological reprogramming, underscoring the potential of this tool for clinical evaluation of cervical precancers.

Next-generation agents for fluorescence-guided glioblastoma surgery

Glioblastoma is a fast-growing and aggressive form of brain cancer. Even with maximal treatment, patients show a low median survival and are often subjected to a high recurrence incidence. The currently available treatments require multimodal management, including maximal safe surgical resection, followed by radiation and chemotherapy. Because of the infiltrative glioblastoma nature, intraoperative differentiation of cancer tissue from normal brain parenchyma is very challenging, and this accounts for the low rate of complete tumor resection. For these reasons, clinicians have increasingly used various intraoperative adjuncts to improve surgical results, such as fluorescent agents. However, most of the existing fluorophores show several limitations such as poor selectivity, photostability, photosensitization and high costs. This could limit their application to successfully improve glioblastoma resection. In the present perspective, we highlight the possibility to develop next-generation fluorescent tools able to more selectively label cancer cells during surgical resection.

Label-free nonlinear optical signatures of extracellular vesicles in liquid and tissue biopsies of human breast cancer

Extracellular vesicles (EVs) have been implicated in metastasis and proposed as cancer biomarkers. However, heterogeneity and small size makes assessments of EVs challenging. Often, EVs are isolated from biofluids, losing spatial and temporal context and thus lacking the ability to access EVs in situ in their native microenvironment. This work examines the capabilities of label-free nonlinear optical microscopy to extract biochemical optical metrics of EVs in ex vivo tissue and EVs isolated from biofluids in cases of human breast cancer, comparing these metrics within and between EV sources. Before surgery, fresh urine and blood serum samples were obtained from human participants scheduled for breast tumor surgery (24 malignant, 6 benign) or healthy participants scheduled for breast reduction surgery (4 control). EVs were directly imaged both in intact ex vivo tissue that was removed during surgery and in samples isolated from biofluids by differential ultracentrifugation. Isolated EVs and freshly excised ex vivo breast tissue samples were imaged with custom nonlinear optical microscopes to extract single-EV optical metabolic signatures of NAD(P)H and FAD autofluorescence. Optical metrics were significantly altered in cases of malignant breast cancer in biofluid-derived EVs and intact tissue EVs compared to control samples. Specifically, urinary isolated EVs showed elevated NAD(P)H fluorescence lifetime in cases of malignant cancer, serum-derived isolated EVs showed decreased optical redox ratio in stage II cancer, but not earlier stages, and ex vivo breast tissue showed an elevated number of EVs in cases of malignant cancer. Results further indicated significant differences in the measured optical metabolic signature based on EV source (urine, serum and tissue) within individuals.

Compact simultaneous label-free autofluorescence multi-harmonic microscopy for user-friendly photodamage-monitored imaging

Significance

Label-free nonlinear optical microscopy has become a powerful tool for biomedical research. However, the possible photodamage risk hinders further clinical applications.

Aim

To reduce these adverse effects, we constructed a new platform of simultaneous label-free autofluorescence multi-harmonic (SLAM) microscopy, featuring four-channel multimodal imaging, inline photodamage monitoring, and pulse repetition-rate tuning.

Approach

Using a large-core birefringent photonic crystal fiber for spectral broadening and a prism compressor for pulse pre-chirping, this system allows users to independently adjust pulse width, repetition rate, and energy, which is useful for optimizing imaging conditions towards no/minimal photodamage.

Results

It demonstrates label-free multichannel imaging at one excitation pulse per image pixel and thus paves the way for improving the imaging speed by a faster optical scanner with a low risk of nonlinear photodamage. Moreover, the system grants users the flexibility to autonomously fine-tune repetition rate, pulse width, and average power, free from interference, ensuring the discovery of optimal imaging conditions with high SNR and minimal phototoxicity across various applications.

Conclusions

The combination of a stable laser source, independently tunable ultrashort pulse, photodamage monitoring features, and a compact design makes this new system a robust, powerful, and user-friendly imaging platform.

Label-free biomedical optical imaging

Label-free optical imaging employs natural and nondestructive approaches for the visualisation of biomedical samples for both biological assays and clinical diagnosis. Currently, this field revolves around multiple broad technology-oriented communities, each with a specific focus on a particular modality despite the existence of shared challenges and applications. As a result, biologists or clinical researchers who require label-free imaging are often not aware of the most appropriate modality to use. This manuscript presents a comprehensive review of and comparison among different label-free imaging modalities and discusses common challenges and applications. We expect this review to facilitate collaborative interactions between imaging communities, push the field forward and foster technological advancements, biophysical discoveries, as well as clinical detection, diagnosis, and monitoring of disease.

Two-photon imaging reveals histopathological changes in the gastric tumor microenvironment induced by neoadjuvant treatment

There is a close association between tumor response and survival in gastric cancer patients after receiving neoadjuvant treatment. An accurate and rapid assessment of therapeutic efficacy would be helpful for subsequent treatments and individual prognosis. At present, pathological examination is the gold standard for evaluating treatment response, however, it requires additional staining and the process is tedious, labor-intensive, as well as time-consuming. Here, we introduce a label-free imaging technique, two-photon imaging, to evaluate histopathological changes induced by pre-operative therapy, with a focus on assessing tumor regression as well as stromal response. Imaging data show that two-photon imaging allows label-free, rapid visualization of various aspects of pathological alterations in tumor microenvironment such as fibrotic reaction, inflammatory cell infiltration, mucinous response, isolated residual tumor cells. Moreover, a semi-automatic image processing approach is developed to extract the collagen morphological features, and statistical results show that there are significant differences in collagen area, length, width, cross-link space between the gastric cancer tissues with and without treatment. With the advent of a portable, miniaturized two-photon imaging device, we have enough reason to believe that this technique will become as an important auxiliary diagnostic tool in assessing neoadjuvant treatment response and thereby tailoring the most appropriate therapy strategies for the patients.

In vivo label-free optical signatures of chemotherapy response in human pancreatic ductal adenocarcinoma patient-derived xenografts

Pancreatic cancer is a devastating disease often detected at later stages, necessitating swift and effective chemotherapy treatment. However, chemoresistance is common and its mechanisms are poorly understood. Here, label-free multi-modal nonlinear optical microscopy was applied to study microstructural and functional features of pancreatic tumors in vivo to monitor inter- and intra-tumor heterogeneity and treatment response. Patient-derived xenografts with human pancreatic ductal adenocarcinoma were implanted into mice and characterized over five weeks of intraperitoneal chemotherapy (FIRINOX or Gem/NabP) with known responsiveness/resistance. Resistant and responsive tumors exhibited a similar initial metabolic response, but by week 5 the resistant tumor deviated significantly from the responsive tumor, indicating that a representative response may take up to five weeks to appear. This biphasic metabolic response in a chemoresistant tumor reveals the possibility of intra-tumor spatiotemporal heterogeneity of drug responsiveness. These results, though limited by small sample size, suggest the possibility for further work characterizing chemoresistance mechanisms using nonlinear optical microscopy.

A Review of Labeling Approaches Used in Small Extracellular Vesicles Tracing and Imaging

Small extracellular vesicles (sEVs), a subset of extracellular vesicles (EVs) originating from the endosomal compartment, are a kind of lipid bilayer vesicles released by almost all types of cells, serving as natural carriers of nucleic acids, proteins, and lipids for intercellular communication and transfer of bioactive molecules. The current findings suggest their vital role in physiological and pathological processes. Various sEVs labeling techniques have been developed for the more advanced study of the function, mode of action, bio-distribution, and related information of sEVs. In this review, we summarize the existing and emerging sEVs labeling techniques, including fluorescent labeling, radioisotope labeling, nanoparticle labeling, chemical contrast agents labeling, and label-free technique. These approaches will pave the way for an in-depth study of sEVs. We present a systematic and comprehensive review of the principles, advantages, disadvantages, and applications of these techniques, to help promote applications of these labeling approaches in future research on sEVs.

Prognostic value of tumor necrosis based on the evaluation of frequency in invasive breast cancer

BACKGROUND

Tumor necrosis (TN) was associated with poor prognosis. However, the traditional classification of TN ignored spatial intratumor heterogeneity, which may be associated with important prognosis. The purpose of this study was to propose a new method to reveal the hidden prognostic value of spatial heterogeneity of TN in invasive breast cancer (IBC).

METHODS

Multiphoton microscopy (MPM) was used to obtain multiphoton images from 471 patients. According to the relative spatial positions of TN, tumor cells, collagen fibers and myoepithelium, four spatial heterogeneities of TN (TN1-4) were defined. Based on the frequency of individual TN, TN-score was obtained to investigate the prognostic value of TN.

RESULTS

Patients with high-risk TN had worse 5-year disease-free survival (DFS) than patients with no necrosis (32.5% vs. 64.7%; P < 0.0001 in training set; 45.8% vs. 70.8%; P = 0.017 in validation set), while patients with low-risk TN had a 5-year DFS comparable to patients with no necrosis (60.0% vs. 64.7%; P = 0.497 in training set; 59.8% vs. 70.8%; P = 0.121 in validation set). Furthermore, high-risk TN "up-staged" the patients with IBC. Patients with high-risk TN and stage I tumors had a 5-year DFS comparable to patients with stage II tumors (55.6% vs. 62.0%; P = 0.565 in training set; 62.5% vs. 66.3%; P = 0.856 in validation set), as well as patients with high-risk TN and stage II tumors had a 5-year DFS comparable to patients with stage III tumors (33.3% vs. 24.6%; P = 0.271 in training set; 44.4% vs. 39.3%; P = 0.519 in validation set).

CONCLUSIONS

TN-score was an independent prognostic factor for 5-year DFS. Only high-risk TN was associated with poor prognosis. High-risk TN "up-staged" the patients with IBC. Incorporating TN-score into staging category could improve its performance to stratify patients.

Weakly supervised identification of microscopic human breast cancer-related optical signatures from normal-appearing breast tissue

With the latest advancements in optical bioimaging, rich structural and functional information has been generated from biological samples, which calls for capable computational tools to identify patterns and uncover relationships between optical characteristics and various biomedical conditions. Constrained by the existing knowledge of the novel signals obtained by those bioimaging techniques, precise and accurate ground truth annotations can be difficult to obtain. Here we present a weakly supervised deep learning framework for optical signature discovery based on inexact and incomplete supervision. The framework consists of a multiple instance learning-based classifier for the identification of regions of interest in coarsely labeled images and model interpretation techniques for optical signature discovery. We applied this framework to investigate human breast cancer-related optical signatures based on virtual histopathology enabled by simultaneous label-free autofluorescence multiharmonic microscopy (SLAM), with the goal of exploring unconventional cancer-related optical signatures from normal-appearing breast tissues. The framework has achieved an average area under the curve (AUC) of 0.975 on the cancer diagnosis task. In addition to well-known cancer biomarkers, non-obvious cancer-related patterns were revealed by the framework, including NAD(P)H-rich extracellular vesicles observed in normal-appearing breast cancer tissue, which facilitate new insights into the tumor microenvironment and field cancerization. This framework can be further extended to diverse imaging modalities and optical signature discovery tasks.

Detection of pathological response of axillary lymph node metastasis after neoadjuvant chemotherapy in breast cancer using multiphoton microscopy

Neoadjuvant treatment is often considered in breast cancer patients with axillary lymph node involvement, but most of patients do not have a pathologic complete response to therapy. The detection of residual nodal disease has a significant impact on adjuvant therapy recommendations which may improve survival. Here, we investigate whether multiphoton microscopy (MPM) could identify the pathological changes of axillary lymphatic metastasis after neoadjuvant chemotherapy in breast cancer. And furthermore, we find that there are obvious differences in seven collagen morphological features between normal node and residual axillary disease by combining with a semi-automatic image processing method, and also find that there are significant differences in four collagen features between the effective and no-response treatment groups. These research results indicate that MPM may help estimate axillary treatment response in the neoadjuvant setting and thereby tailor more appropriate and personalized adjuvant treatments for breast cancer patients.

Rapid and label-free detection of gastrointestinal stromal tumor via a combination of two-photon microscopy and imaging analysis

BACKGROUND

Gastrointestinal stromal tumor (GIST) is currently regarded as a potentially malignant tumor, and early diagnosis is the best way to improve its prognosis. Therefore, it will be meaningful to develop a new method for auxiliary diagnosis of this disease.

METHODS

Here we try out a new means to detect GIST by combining two-photon imaging with automatic image processing strategy.

RESULTS

Experimental results show that two-photon microscopy has the ability to label-freely identify the structural characteristics of GIST such as tumor cells, desmoplastic reaction, which are entirely different from those from gastric adenocarcinoma. Moreover, an image processing approach is used to extract eight collagen morphological features from tumor microenvironment and normal muscularis, and statistical analysis demonstrates that there are significant differences in three features-fiber area, density and cross-link density. The three morphological characteristics may be considered as optical imaging biomarkers to differentiate between normal and abnormal tissues.

CONCLUSION

With continued improvement and refinement of this technology, we believe that two-photon microscopy will be an efficient surveillance tool for GIST and lead to better management of this disease.

Nonlinear optical imaging by detection with optical parametric amplification (invited paper)

Nonlinear optical imaging is a versatile tool that has been proven to be exceptionally useful in various research fields. However, due to the use of photomultiplier tubes (PMTs), the wide application of nonlinear optical imaging is limited by the incapability of imaging under ambient light. In this paper, we propose and demonstrate a new optical imaging detection method based on optical parametric amplification (OPA). As a nonlinear optical process, OPA intrinsically rejects ambient light photons by coherence gating. Periodical poled lithium niobate (PPLN) crystals are used in this study as the media for OPA. Compared to bulk nonlinear optical crystals, PPLN crystals support the generation of OPA signal with lower pump power. Therefore, this characteristic of PPLN crystals is particularly beneficial when using high-repetition-rate lasers, which facilitate high-speed optical signal detection, such as in spectroscopy and imaging. A PPLN-based OPA system was built to amplify the emitted imaging signal from second harmonic generation (SHG) and coherent anti-Stokes Raman scattering (CARS) microscopy imaging, and the amplified optical signal was strong enough to be detected by a biased photodiode under ordinary room light conditions. With OPA detection, ambient-light-on SHG and CARS imaging becomes possible, and achieves a similar result as PMT detection under strictly dark environments. These results demonstrate that OPA can be used as a substitute for PMTs in nonlinear optical imaging to adapt it to various applications with complex lighting conditions.

Rapid and label-free histological imaging of unprocessed surgical tissues via dark-field reflectance ultraviolet microscopy

Routine examination for intraoperative histopathologic assessment is lengthy and laborious. Here, we present the dark-field reflectance ultraviolet microscopy (DRUM) that enables label-free imaging of unprocessed and thick tissues with subcellular resolution and a high signal-to-background ratio. To the best of our knowledge, DRUM provides image results for pathological assessment with the shortest turnaround time (2-3 min in total from sample preparation to tissue imaging). We also proposed a virtual staining process to convert DRUM images into pseudo-colorized images and enhance the image familiarity of pathologists. By imaging various tissues, we found DRUM can resolve cell nuclei and some extranuclear features, which are comparable to standard H&E images. Furthermore, the essential diagnostic features of intraoperatively excised tumor tissues also can be revealed by DRUM, demonstrating its potential as an additional aid for intraoperative histopathology.

Label-free multimodal nonlinear optical imaging of needle biopsy cores for intraoperative cancer diagnosis

SIGNIFICANCE

Needle biopsy (NB) procedures are important for the initial diagnosis of many types of cancer. However, the possibility of NB specimens being unable to provide diagnostic information, (i.e., non-diagnostic sampling) and the time-consuming histological evaluation process can cause delays in diagnoses that affect patient care.

AIM

We aim to demonstrate the advantages of this label-free multimodal nonlinear optical imaging (NLOI) technique as a non-destructive point-of-procedure evaluation method for NB tissue cores, for the visualization and characterization of the tissue microenvironment.

APPROACH

A portable, label-free, multimodal NLOI system combined second-harmonic generation (SHG) and third-harmonic generation and two- and three-photon autofluorescence (2PF, 3PF) microscopy. It was used for intraoperative imaging of fresh NB tissue cores acquired during canine cancer surgeries, which involved liver, lung, and mammary tumors as well as soft-tissue sarcoma; in total, eight canine patients were recruited. An added tissue culture chamber enabled the use of this NLOI system for longitudinal imaging of fresh NB tissue cores taken from an induced rat mammary tumor and healthy mouse livers.

RESULTS

The intraoperative NLOI system was used to assess fresh canine NB specimens during veterinary cancer surgeries. Histology-like morphological features were visualized by the combination of four NLOI modalities at the point-of-procedure. The NLOI results provided quantitative information on the tissue microenvironment such as the collagen fiber orientation using Fourier-domain SHG analysis and metabolic profiling by optical redox ratio (ORR) defined by 2PF/(2PF + 3PF). The analyses showed that the canine mammary tumor had more randomly oriented collagen fibers compared to the tumor margin, and hepatocarcinoma had a wider distribution of ORR with a lower mean value compared to the liver fibrosis and the normal-appearing liver. Moreover, the loss of metabolic information during tissue degradation of fresh murine NB specimens was shown by overall intensity decreases in all channels and an increase of mean ORR from 0.94 (standard deviation 0.099) to 0.97 (standard deviation 0.077) during 1-h longitudinal imaging of a rat mammary tumor NB specimen. The tissue response to staurosporine (STS), an apoptotic inducer, from fresh murine liver NB specimens was also observed. The mean ORR decreased from 0.86 to 0.74 in the first 40 min and then increased to 0.8 during the rest of the hour of imaging, compared to the imaging results without the addition of STS, which showed a continuous increase of ORR from 0.72 to 0.75.

CONCLUSIONS

A label-free, multimodal NLOI platform reveals microstructural and metabolic information of the fresh NB cores during intraoperative cancer imaging. This system has been demonstrated on animal models to show its potential to provide a more comprehensive histological assessment and a better understanding of the unperturbed tumor microenvironment. Considering tissue degradation, or loss of viability upon fixation, this intraoperative NLOI system has the advantage of immediate assessment of freshly excised tissue specimens at the point of procedure.

Overview of extracellular vesicle characterization techniques and introduction to combined reflectance and fluorescence confocal microscopy to distinguish extracellular vesicle subpopulations

Extracellular vesicles (EVs) are nanoparticles (30 to 1000 nm in diameter) surrounded by a lipid-bilayer which carry bioactive molecules between local and distal cells and participate in intercellular communication. Because of their small size and heterogenous nature they are challenging to characterize. Here, we discuss commonly used techniques that have been employed to yield information about EV size, concentration, mechanical properties, and protein content. These include dynamic light scattering, nanoparticle tracking analysis, flow cytometry, transmission electron microscopy, atomic force microscopy, western blotting, and optical methods including super-resolution microscopy. We also introduce an innovative technique for EV characterization which involves immobilizing EVs on a microscope slide before staining them with antibodies targeting EV proteins, then using the reflectance mode on a confocal microscope to locate the EV plane. By then switching to the microscope's fluorescence mode, immunostained EVs bearing specific proteins can be identified and the heterogeneity of an EV preparation can be determined. This approach does not require specialist equipment beyond the confocal microscopes that are available in many cell biology laboratories, and because of this, it could become a complementary approach alongside the aforementioned techniques to identify molecular heterogeneity in an EV preparation before subsequent analysis requiring specialist apparatus.

Super-Multiplex Nonlinear Optical Imaging Unscrambles the Statistical Complexity of Cancer Subtypes and Tumor Microenvironment

Label-free nonlinear optical imaging (NLOI) has made tremendous inroads toward unscrambling the microcosmic complexity of cancers. However, harmonic and Raman microscopy offers throughput without redox information to reveal metabolic differentiation, and fluorescence lifetime microscopy lacks the vibrational response of molecules to visualize specific molecular constituents such as lipid. Here, a flexible, robust simultaneous multi-nonlinear imaging and cross-modality system that combines complementary imaging contrast mechanisms is demonstrated. This system, utilizing multiplexed ultrashort pulses, ingeniously integrates typical nonlinear processes, and high-dimension lifetime extension in a single setup to enhance the imaging dimensions and quality. Using this system, the authors perform label-free comprehensive evaluation of clinicopathological tissues of ovarian carcinoma due to its statistical complexity. The results show that the technology provides statistically rich, insightful information with high accuracy, sensitivity, and specificity, in contrast to standard histopathology, and can potentially be a powerful tool for fundamental cancer research and clinical applications.

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.

Proof of concept for the sapphire scalpel combining tissue dissection and optical diagnosis

OBJECTIVES

The development of compact diagnostic probes and instruments with an ability to direct access to organs and tissues and integration of these instruments into surgical workflows is an important task of modern physics and medicine. The need for such tools is essential for surgical oncology, where intraoperative visualization and demarcation of tumor margins define further prognosis and survival of patients. In this paper, the possible solution for this intraoperative imaging problem is proposed and its feasibility to detect tumorous tissue is studied experimentally.

METHODS

For this aim, the sapphire scalpel was developed and fabricated using the edge-defined film-fed growth technique aided by mechanical grinding, polishing, and chemical sharpening of the cutting edge. It possesses optical transparency, mechanical strength, chemical inertness, and thermal resistance alongside the presence of the as-grown hollow capillary channels in its volume for accommodating optical fibers. The rounding of the cutting edge exceeds the same for metal scalpels and can be as small as 110 nm. Thanks to these features, sapphire scalpel combines tissue dissection with light delivering and optical diagnosis. The feasibility for the tumor margin detection was studied, including both gelatin-based tissue phantoms and ex vivo freshly excised specimens of the basal cell carcinoma from humans and the glioma model 101.8 from rats. These tumors are commonly diagnosed either non-invasively or intraoperatively using different modalities of fluorescence spectroscopy and imaging, which makes them ideal candidates for our feasibility test. For this purpose, fiber-based spectroscopic measurements of the backscattered laser radiation and the fluorescence signals were carried out in the visible range.

RESULTS

Experimental studies show the feasibility of the proposed sapphire scalpel to provide a 2-mm-resolution of the tumor margins' detection, along with an ability to distinguish the tumor invasion region, which results from analysis of the backscattered optical fields and the endogenous or exogenous fluorescence data.

CONCLUSIONS

Our findings justified a strong potential of the sapphire scalpel for surgical oncology. However, further research and engineering efforts are required to optimize the sapphire scalpel geometry and the optical diagnosis protocols to meet the requirements of oncosurgery, including diagnosis and resection of neoplasms with different localizations and nosologies.

Accelerating precision anti-cancer therapy by time-lapse and label-free 3D tumor slice culture platform

The feasibility of personalized medicine for cancer treatment is largely hampered by costly, labor-intensive and time-consuming models for drug discovery. Herein, establishing new pre-clinical models to tackle these issues for personalized medicine is urgently demanded.

Methods: We established a three-dimensional tumor slice culture (3D-TSC) platform incorporating label-free techniques for time-course experiments to predict anti-cancer drug efficacy and validated the 3D-TSC model by multiphoton fluorescence microscopy, RNA sequence analysis, histochemical and histological analysis.

Results: Using time-lapse imaging of the apoptotic reporter sensor C3 (C3), we performed cell-based high-throughput drug screening and shortlisted high-efficacy drugs to screen murine and human 3D-TSCs, which validate effective candidates within 7 days of surgery. Histological and RNA sequence analyses demonstrated that 3D-TSCs accurately preserved immune components of the original tumor, which enables the successful achievement of immune checkpoint blockade assays with antibodies against PD-1 and/or PD-L1. Label-free multiphoton fluorescence imaging revealed that 3D-TSCs exhibit lipofuscin autofluorescence features in the time-course monitoring of drug response and efficacy.

Conclusion: This technology accelerates precision anti-cancer therapy by providing a cheap, fast, and easy platform for anti-cancer drug discovery.

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.

Collective Cell Migration in a Fibrous Environment: A Hybrid Multiscale Modelling Approach

The specific structure of the extracellular matrix (ECM), and in particular the density and orientation of collagen fibres, plays an important role in the evolution of solid cancers. While many experimental studies discussed the role of ECM in individual and collective cell migration, there are still unanswered questions about the impact of nonlocal cell sensing of other cells on the overall shape of tumour aggregation and its migration type. There are also unanswered questions about the migration and spread of tumour that arises at the boundary between different tissues with different collagen fibre orientations. To address these questions, in this study we develop a hybrid multi-scale model that considers the cells as individual entities and ECM as a continuous field. The numerical simulations obtained through this model match experimental observations, confirming that tumour aggregations are not moving if the ECM fibres are distributed randomly, and they only move when the ECM fibres are highly aligned. Moreover, the stationary tumour aggregations can have circular shapes or irregular shapes (with finger-like protrusions), while the moving tumour aggregations have elongate shapes (resembling to clusters, strands or files). We also show that the cell sensing radius impacts tumour shape only when there is a low ratio of fibre to non-fibre ECM components. Finally, we investigate the impact of different ECM fibre orientations corresponding to different tissues, on the overall tumour invasion of these neighbouring tissues.

Label-free imaging of human brain tissue at subcellular resolution for potential rapid intra-operative assessment of glioma surgery

Background: Frozen section and smear preparation are the current standard for intraoperative histopathology during cancer surgery. However, these methods are time-consuming and subject to limited sampling. Multiphoton microscopy (MPM) is a high-resolution non-destructive imaging technique capable of optical sectioning in real time with subcellular resolution. In this report, we systematically investigated the feasibility and translation potential of MPM for rapid histopathological assessment of label- and processing-free surgical specimens. Methods: We employed a customized MPM platform to capture architectural and cytological features of biological tissues based on two-photon excited NADH and FAD autofluorescence and second harmonic generation from collagen. Infiltrating glioma, an aggressive disease that requires subcellular resolution for definitive characterization during surgery, was chosen as an example for this validation study. MPM images were collected from resected brain specimens of 19 patients and correlated with histopathology. Deep learning was introduced to assist with image feature recognition. Results: MPM robustly captures diagnostic features of glioma including increased cellularity, cellular and nuclear pleomorphism, microvascular proliferation, necrosis, and collagen deposition. Preliminary application of deep learning to MPM images achieves high accuracy in distinguishing gray from white matter and cancer from non-cancer. We also demonstrate the ability to obtain such images from intact brain tissue with a multiphoton endomicroscope for intraoperative application. Conclusion: Multiphoton imaging correlates well with histopathology and is a promising tool for characterization of cancer and delineation of infiltration within seconds during brain surgery.

Multiphoton tomography in differentiation of morphological and molecular subtypes of breast cancer: A quantitative analysis

In this study multiphoton tomography, based on second harmonic generation (SHG), and two-photon-excited fluorescence (TPEF) was used to visualize both the extracellular matrix and tumor cells in different morphological and molecular subtypes of human breast cancer. It was shown, that quantified assessment of the SHG based imaging data has great potential to reveal differences of collagen quantity, organization and uniformity in both low- and highly- aggressive invasive breast cancers. The values of quantity and uniformity of the collagen fibers distribution were significantly higher in low-aggressive breast cancer compared to the highly-aggressive subtypes, while the value representing collagen organization was lower in the former type. Additionally, it was shown, that TPEF detection of elastin fibers and amyloid protein may be used as a biomarker of detection the low-aggressive breast cancer subtype. Thus, TPEF/SHG imaging offers the possibility of becoming a useful tool for the rapid diagnosis of various subtypes of breast cancer during biopsy as well as for the intraoperative determinination of tumor-positive resection margins.

Visualizing Extracellular Vesicles and Their Function in 3D Tumor Microenvironment Models

Extracellular vesicles (EVs) are cell-derived nanostructures that mediate intercellular communication by delivering complex signals in normal tissues and cancer. The cellular coordination required for tumor development and maintenance is mediated, in part, through EV transport of molecular cargo to resident and distant cells. Most studies on EV-mediated signaling have been performed in two-dimensional (2D) monolayer cell cultures, largely because of their simplicity and high-throughput screening capacity. Three-dimensional (3D) cell cultures can be used to study cell-to-cell and cell-to-matrix interactions, enabling the study of EV-mediated cellular communication. 3D cultures may best model the role of EVs in formation of the tumor microenvironment (TME) and cancer cell-stromal interactions that sustain tumor growth. In this review, we discuss EV biology in 3D culture correlates of the TME. This includes EV communication between cell types of the TME, differences in EV biogenesis and signaling associated with differing scaffold choices and in scaffold-free 3D cultures and cultivation of the premetastatic niche. An understanding of EV biogenesis and signaling within a 3D TME will improve culture correlates of oncogenesis, enable molecular control of the TME and aid development of drug delivery tools based on EV-mediated signaling.

Breast Cancer Microenvironment Cross Talk through Extracellular Vesicle RNAs

Exploration of extracellular communication has been at the forefront of research efforts in recent years. However, the mechanisms of cell-to-cell communication in complex tissues are poorly understood. What is clear is that cells do not exist in isolation, that they are constantly interacting and communicating with cells in the immediate vicinity and with cells at a distance. Intercellular communication by the release of small extracellular vesicles, called exosomes, loaded with RNAs is one mechanism by which cells communicate. In recent years, research has shown that exosomes, a class of extracellular vesicles, can play a major role in the pathogenesis of breast cancer. Specifically, exosomes have been demonstrated to play a role in promoting primary cancer development, invasion, metastasis, and chemotherapeutic resistance. This review summarizes what is known about the mechanisms of exosome-mediated transfer of RNAs among cells in the breast microenvironment and discusses outstanding questions and the potential for new therapeutic intervention targeted at these interactions.

Multi-omics characterization and validation of invasiveness-related molecular features across multiple cancer types

Background

Tumor invasiveness reflects many biological changes associated with tumorigenesis, progression, metastasis, and drug resistance. Therefore, we performed a systematic assessment of invasiveness-related molecular features across multiple human cancers.

Materials and methods

Multi-omics data, including gene expression, miRNA, DNA methylation, and somatic mutation, in approximately 10,000 patients across 30 cancer types from The Cancer Genome Atlas, Gene Expression Omnibus, PRECOG, and our institution were enrolled in this study.

Results

Based on a robust gene signature, we established an invasiveness score and found that the score was significantly associated with worse prognosis in almost all cancers. Then, we identified common invasiveness-associated dysregulated molecular features between high- and low-invasiveness score group across multiple cancers, as well as investigated their mutual interfering relationships thus determining whether the dysregulation of invasiveness-related genes was caused by abnormal promoter methylation or miRNA expression. We also analyzed the correlations between the drug sensitivity data from cancer cell lines and the expression level of 685 invasiveness-related genes differentially expressed in at least ten cancer types. An integrated analysis of the correlations among invasiveness-related genetic features and drug response were conducted in esophageal carcinoma patients to outline the complicated regulatory mechanism of tumor invasiveness status in multiple dimensions. Moreover, functional enrichment suggests the invasiveness score might serve as a predictive biomarker for cancer patients receiving immunotherapy.

Conclusion

Our pan-cancer study provides a comprehensive atlas of tumor invasiveness and may guide more precise therapeutic strategies for tumor patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-02773-x

Optical biopsy of laryngeal lesions using femtosecond multiphoton microscopy

Laryngeal squamous cell carcinoma (LSCC) is one of the most prevalent malignancy of the upper aerodigestive tract. Detection of early lesions in vivo could improve the survival rate significantly. In this study, we demonstrated that femtosecond multiphoton microscopy (MPM) is an effective tool to visualize the microscopic features within fixed laryngeal tissues, without sectioning, staining, or labeling. Accurate detection of lesions and determination of the tumor grading can be achieved, with excellent consistency with conventional histological examination. These results suggest that MPM may represent a powerful tool for in-vivo or fast ex-vivo diagnosis of laryngeal lesions at the point of care.

Label-free characterization of single extracellular vesicles using two-photon fluorescence lifetime imaging microscopy of NAD(P)H

The heterogeneous nature of extracellular vesicles (EVs) creates the need for single EV characterization techniques. However, many common biochemical and functional EV analysis techniques lack single EV resolution. Two-photon fluorescence lifetime imaging microscopy (FLIM) is widely used to functionally characterize the reduced form of nicotinamide adenine dinucleotide and nicotinamide adenine dinucleotide phosphate (NAD(P)H) in cells and tissues. Here, we demonstrate that FLIM can also be used to image and characterize NAD(P)H in single isolated EVs. EVs were isolated using standard differential ultracentrifugation techniques from multiple cell lines and imaged using a custom two-photon FLIM system. The presented data show that the NAD(P)H fluorescence lifetimes in isolated cell-derived EVs follow a wide Gaussian distribution, indicating the presence of a range of different protein-bound and free NAD(P)H species. EV NAD(P)H fluorescence lifetime distribution has a larger standard deviation than that of cells and a significantly different fluorescence lifetime distribution than the nuclei, mitochondria, and cytosol of cells. Additionally, changes in the metabolic conditions of cells were reflected in changes in the mean fluorescence lifetime of NAD(P)H in the produced EVs. These data suggest that FLIM of NAD(P)H could be a valuable tool for EV research.

3D microscopy and deep learning reveal the heterogeneity of crown-like structure microenvironments in intact adipose tissue

Crown-like structures (CLSs) are adipose microenvironments of macrophages engulfing adipocytes. Their histological density in visceral adipose tissue (VAT) predicts metabolic disorder progression in obesity and is believed to initiate obesity comorbidities. Here, we use three-dimensional (3D) light sheet microscopy and deep learning to quantify 3D features of VAT CLSs in lean and obese states. Obese CLS densities are significantly higher, composing 3.9% of tissue volume compared with 0.46% in lean tissue. Across the states, individual CLS structural characteristics span similar ranges; however, subpopulations are distinguishable. Obese VAT contains large CLSs absent from lean tissues, located near the tissue center, while lean CLSs have higher volumetric cell densities and prolate shapes. These features are consistent with inefficient adipocyte elimination in obesity that contributes to chronic inflammation, representing histological biomarkers to assess adipose pathogenesis. This tissue processing, imaging, and analysis pipeline can be applied to quantitatively classify 3D microenvironments across diverse tissues.

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.

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.

Compact portable multiphoton microscopy reveals histopathological hallmarks of unprocessed lung tumor tissue in real time

During lung cancer operations a rapid and reliable assessment of tumor tissue can reduce operation time and potentially improve patient outcomes. We show that third harmonic generation (THG), second harmonic generation (SHG) and two-photon excited autofluorescence (2PEF) microscopy reveals relevant, histopathological information within seconds in fresh unprocessed human lung samples. We used a compact, portable microscope and recorded images within 1 to 3 seconds using a power of 5 mW. The generated THG/SHG/2PEF images of tumorous and nontumorous tissues are compared with the corresponding standard histology images, to identify alveolar structures and histopathological hallmarks. Cellular structures (tumor cells, macrophages and lymphocytes) (THG), collagen (SHG) and elastin (2PEF) are differentiated and allowed for rapid identification of carcinoid with solid growth pattern, minimally enlarged monomorphic cell nuclei with salt-and-pepper chromatin pattern, and adenocarcinoma with lipidic and micropapillary growth patterns. THG/SHG/2PEF imaging is thus a promising tool for clinical intraoperative assessment of lung tumor tissue.

Therapy-Induced Modulation of the Tumor Microenvironment: New Opportunities for Cancer Therapies

Advances in immunotherapy have achieved remarkable clinical outcomes in tumors with low curability, but their effects are limited, and increasing evidence has implicated tumoral and non-tumoral components of the tumor microenvironment as critical mediators of cancer progression. At the same time, the clinical successes achieved with minimally invasive and optically-guided surgery and image-guided and ablative radiation strategies have been successfully implemented in clinical care. More effective, localized and safer treatments have fueled strong research interest in radioimmunotherapy, which has shown the potential immunomodulatory effects of ionizing radiation. However, increasingly more observations suggest that immunosuppressive changes, metabolic remodeling, and angiogenic responses in the local tumor microenvironment play a central role in tumor recurrence. In this review, we address challenges to identify responders vs. non-responders to the immune checkpoint blockade, discuss recent developments in combinations of immunotherapy and radiotherapy for clinical evaluation, and consider the clinical impact of immunosuppressive changes in the tumor microenvironment in the context of surgery and radiation. Since the therapy-induced modulation of the tumor microenvironment presents a multiplicity of forms, we propose that overcoming microenvironment related resistance can become clinically relevant and represents a novel strategy to optimize treatment immunogenicity and improve patient outcome.

Third Harmonic Generation microscopy distinguishes malignant cell grade in human breast tissue biopsies

The ability to distinguish and grade malignant cells during surgical procedures in a fast, non-invasive and staining-free manner is of high importance in tumor management. To this extend, Third Harmonic Generation (THG), Second Harmonic Generation (SHG) and Fourier-Transform Infrared (FTIR) spectroscopy were applied to discriminate malignant from healthy cells in human breast tissue biopsies. Indeed, integration of non-linear processes into a single, unified microscopy platform offered complementary structural information within individual cells at the submicron level. Using a single laser beam, label-free THG imaging techniques provided important morphological information as to the mean nuclear and cytoplasmic area, cell volume and tissue intensity, which upon quantification could not only distinguish cancerous from benign breast tissues but also define disease severity. Simultaneously, collagen fibers that could be detected by SHG imaging showed a well structured continuity in benign tumor tissues, which were gradually disoriented along with disease severity. Combination of THG imaging with FTIR spectroscopy could provide a clearer distinction among the different grades of breast cancer, since FTIR analysis showed increased lipid concentrations in malignant tissues. Thus, the use of non-linear optical microscopy can be considered as powerful and harmless tool for tumor cell diagnostics even during real time surgery procedures.

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, High-Resolution Optical Metabolic Imaging of Human Cervical Precancers Reveals Potential for Intraepithelial Neoplasia Diagnosis

While metabolic changes are considered a cancer hallmark, their assessment has not been incorporated in the detection of early or precancers, when treatment is most effective. Here, we demonstrate that metabolic changes are detected in freshly excised human cervical precancerous tissues using label-free, non-destructive imaging of the entire epithelium. The images rely on two-photon excited fluorescence from two metabolic co-enzymes, NAD(P)H and FAD, and have micron-level resolution, enabling sensitive assessments of the redox ratio and mitochondrial fragmentation, which yield metrics of metabolic function and heterogeneity. Simultaneous characterization of morphological features, such as the depth-dependent variation of the nuclear:cytoplasmic ratio, is demonstrated. Multi-parametric analysis combining several metabolic metrics with morphological ones enhances significantly the diagnostic accuracy of identifying high-grade squamous intraepithelial lesions. Our results motivate the translation of such functional metabolic imaging to in vivo studies, which may enable improved identification of cervical lesions, and other precancers, at the bedside.

[Progress in extracellular vesicle imaging methods]

Extracellular vesicles (EVs), including exosomes and microvesicles, are lipid bilayer-enclosed nanovesicles secreted by cells. These EVs are important mediators of intercellular communication by serving as vehicles for transfer of proteins, mRNA, miRNA and lipids between cells. Various visualization methods have been established to explore the characteristics of EVs and their role in physiological and pathological processes. The nanoscale size and high heterogeneity of EVs hamper the identification of their biological characteristics and functions. This review presents a comprehensive overview of EV imaging methods in light of the origin, separation and dynamic tracking of EVs, and the advantages and disadvantages of different imaging strategies are discussed. We believe that studies at the levels of single vesicles and single cells will become the frontier of future researches of EVs.

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.

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.

Evaluation of breast carcinoma regression after preoperative chemotherapy by label-free multiphoton imaging and image analysis

Neoadjuvant chemotherapy is increasingly being used in breast carcinoma as it significantly improves the prognosis and consistently leads to an increased rate of breast preservation. How to accurately assess tumor response after treatment is a crucial factor for developing reasonable therapeutic strategy. In this study, we were in an attempt to monitor tumor response by multimodal multiphoton imaging including two-photon excitation fluorescence and second-harmonic generation imaging. We found that multiphoton imaging can identify different degrees of tumor response such as a slight, significant, or complete response and can detect morphological alteration associated with extracellular matrix during the progression of breast carcinoma following preoperative chemotherapy. Two quantitative optical biomarkers including tumor cellularity and collagen content were extracted based on automatic image analysis to help monitor changes in tumor and its microenvironment. Furthermore, tumor regression grade diagnosis was tried to evaluate by multiphoton microscopy. These results may offer a basic framework for using multiphoton microscopic imaging techniques as a helpful diagnostic tool for assessing breast carcinoma response after presurgical treatment.

Label-Free Identification of Early Stages of Breast Ductal Carcinoma via Multiphoton Microscopy

Breast cancer can be cured by early diagnosis. Appropriate and effective clinical treatment benefits from accurate pathological diagnosis. However, due to the lack of effective screening and diagnostic imaging methods, early stages of breast cancer often progress to malignant breast cancer. In this study, multiphoton microscopy (MPM) via two-photon excited fluorescence combined with second-harmonic generation was used for identifying the early stages of breast ductal carcinoma. The results showed differences in both cytological features and collagen distribution among normal breast tissue, atypical ductal hyperplasia, low-grade ductal carcinoma in situ, and high-grade ductal carcinoma in situ with microinvasion. Furthermore, three features extracted from the MPM images were used to describe differences in cytological features, collagen density, and basement membrane circumference in the early stages of breast ductal carcinoma. They revealed that MPM has the ability to identify early stages of breast ductal carcinoma label-free, which would contribute to the early diagnosis and treatment of breast cancer. This study may provide the groundwork for the further application of MPM in the clinic.