Search Results (96)

Pathological analysis of tissue biopsies remains the gold standard for diagnosing cancer and other diseases. However, this is a time-intensive process that demands extensive training and expertise. Despite its importance, it is often subjective and not entirely error-free. Over the past decade, pathology has undergone two major transformations. First, the rise in whole slide imaging has enabled work in front of a computer screen and the integration of image processing tools to enhance diagnostics. Second, the rapid evolution of Artificial Intelligence has revolutionized numerous fields and has had a remarkable impact on humanity. The synergy of these two has paved the way for groundbreaking research aiming for advancements in digital pathology. Despite encouraging research outcomes, AI-based tools have yet to be actively incorporated into therapeutic protocols. This is primary due to the need for high reliability in medical therapy, necessitating a new approach that ensures greater robustness. Another approach for improving pathological diagnosis involves advanced optical methods such as spectral imaging, which reveals information from the tissue that is beyond human vision. We have recently developed a unique rapid spectral imaging system capable of scanning pathological slides, delivering a wealth of critical diagnostic information. Here, we present a novel application of spectral imaging (SI) for virtual Hematoxylin and Eosin (H&E) staining using a custom-built, rapid Fourier-based SI system. Unstained human biopsy samples are scanned, and a Pix2Pix-based neural network generates realistic H&E-equivalent images. Additionally, we applied Principal Component Analysis (PCA) to the spectral information to examine the effect of down sampling the data on the virtual staining process. To assess model performance, we trained and tested models using full spectral data, RGB, and PCA-reduced spectral inputs. The results demonstrate that PCA-reduced data preserved essential image features while enhancing statistical image quality, as indicated by FID and KID scores, and reducing computational complexity. These findings highlight the potential of integrating SI and AI to enable efficient, accurate, and stain-free digital pathology. Full article

Label-free, high-throughput, and 3D morphological analysis of blood cells remains a major challenge in biomedical optics. In this study, we investigate this issue using flow cytometry with digital holographic microscopy (DHM) to enable real-time, label-free imaging of red blood cells (RBCs) and blood coagulation structures (BCSs) without the need for staining or chemical pretreatment. We demonstrate an approach for the automated quantification and statistical characterization of these cells using quantitative phase information reconstructed from digital holograms. Although established image processing techniques such as phase unwrapping and segmentation are used, this study presents, to the best of our knowledge, the first statistical characterization of the 3D morphological features of BCSs. This is particularly useful in analyzing the heterogeneous and complex 3D structures of BCSs, which are difficult to assess using conventional microscopy. The results suggest that this DHM-based flow cytometry system provides a promising platform for non-invasive, real-time morphological evaluation of blood samples and has potential applications in hematological diagnostics and research related to blood coagulation. Full article

Histopathological staining remains the fibrosis diagnostic gold standard yet suffers from staining artifacts and variability. Nonlinear optical techniques (e.g., spontaneous fluorescence, Second Harmonic Generation) enhance accuracy but struggle with rapid trace-level detection of fibrosis. To address these limitations, a dual-channel nonlinear optical imaging system with excitation wavelengths at 780 nm and 820 nm was developed, enabling simultaneous spontaneous fluorescence and second-harmonic generation imaging through grid localization. This study applies dual-modality nonlinear imaging to achieve label-free, high-resolution visualization of pulmonary and renal fibrosis at the ECM microstructure scale. Through leveraging this system, it is demonstrated that collagen can be rapidly detected via spontaneous fluorescence at 780 nm, whereas the spatial distribution of collagen fibrils is precisely mapped using Second Harmonic Generation at 820 nm. This approach allows for the rapid and sensitive detection of trace fibrosis in a 5-day unilateral ureteral obstruction mouse model. Additionally, we identify that the elastic fibers, which can also be visualized, provide a foundation for staging diagnosis and delivering accurate and quantitative data for pathological studies and analysis. The research findings underscore the potential of this dual-channel nonlinear optical imaging system as a powerful tool for rapid, precise, and noninvasive fibrosis detection and staging. Full article

To overcome the limitations associated with chemically synthesized nanoparticles in cancer therapy, researchers have increasingly focused on developing nanoparticles with superior biocompatibility and prolonged tumor retention using biosynthetic methods. In this study, we first identified the presence of calcium peroxide nanoparticles (CaO₂ NPs) in the blood of individuals who had ingested calcium gluconate. Furthermore, the dropwise addition of calcium gluconate to human serum resulted in the spontaneous self-assembly of CaO₂ NPs. Next, following tail vein injection of fluorescently labeled CaO₂ NPs into subcutaneous tumor-bearing nude mice, we observed that the nanoparticles exhibited prolonged accumulation at the tumor sites compared to other organs through visible-light imaging. Immunofluorescence staining demonstrated that CaO₂ NPs co-localized with vesicular transport-associated proteins, such as PV-1 and Caveolin-1, as well as the albumin-binding-associated protein SPARC, suggesting that their transport from tumor blood vessels to the tumor site is mediated by Caveolin-1- and SPARC-dependent active transport pathways. Additionally, the analysis of various organs in normal mice injected with CaO₂ NPs at concentrations significantly higher than the experimental dose showed no apparent organ damage. Hemolysis assays indicated that hemolysis occurred only at calcium concentrations of 300 µg/mL, whereas the experimental concentration remained well below this threshold with no detectable hemolytic activity. In a subcutaneous tumor-bearing nude mouse model, treatment with docetaxel-loaded CaO₂ NPs showed a 68.5% reduction in tumor volume compared to free docetaxel (DTX) alone. These novel biosynthetic CaO₂ NPs demonstrated excellent biocompatibility, prolonged retention at the tumor site, safety, and drug-loading capability. Full article

Background: Accurate and rapid intraoperative tumor margin assessment remains a major challenge in surgical oncology. Current gold-standard methods, such as frozen section histology, are time-consuming, operator-dependent, and prone to misclassification, which limits their clinical utility. Objective: To develop and evaluate a novel hyperspectral imaging (HSI) workflow that integrates deep learning with three-dimensional (3D) tumor modeling for real-time, label-free tumor margin delineation in head and neck squamous cell carcinoma (HNSCC). Methods: Freshly resected HNSCC samples were snap-frozen and imaged ex vivo from multiple perspectives using a standardized HSI protocol, resulting in a 3D model derived from HSI. Each sample was serially sectioned, stained, and annotated by pathologists to create high-resolution 3D histological reconstructions. The volumetric histological models were co-registered with the HSI data (n = 712 Datacubes), enabling voxel-wise projection of tumor segmentation maps from the HSI-derived 3D model onto the corresponding histological ground truth. Three deep learning models were trained and validated on these datasets to differentiate tumor from non-tumor regions with high spatial precision. Results: This work demonstrates strong potential for the proposed HSI system, with an overall classification accuracy of 0.98 and a tumor sensitivity of 0.93, underscoring the system’s ability to reliably detect tumor regions and showing high concordance with histopathological findings. Conclusion: The integration of HSI with deep learning and 3D tumor modeling offers a promising approach for precise, real-time intraoperative tumor margin assessment in HNSCC. This novel workflow has the potential to improve surgical precision and patient outcomes by providing rapid, label-free tissue differentiation. Full article

Background/Objectives: Holotomography is an advanced imaging technique that enables high-resolution, three-dimensional visualization of microscopic specimens without the need for fixation or staining. Here we aim to apply holotomography technology to image live Hypsibius exemplaris in their native state, avoiding invasive sample preparation procedures and phototoxic effects associated with other imaging modalities. Methods: We use a low concentration of 7% ethanol for tardigrade sedation and sample preparation. Holotomographic images were obtained and reconstructed using the Tomocube HT-X1 system, enabling high-resolution visualization of tardigrade anatomical structures. Results: We captured detailed, label-free holotomography images of both external and internal structures of tardigrade, including the digestive tract, brain, ovary, claws, salivary glands, and musculature. Conclusions: Our findings highlight holotomography as a complementary high-resolution imaging modality that effectively addresses the challenges faced with traditional imaging techniques in tardigrade research. Full article

Hydrogels are promising scaffolds for tissue regeneration, and borosilicate glass particles have demonstrated potential in enhancing the biological behaviour of dental pulp cells. However, the specific morphological characteristics of dental lesions and the diverse requirements of dental tissues require biocompatible, bioactive, and shapeable scaffolds. This study aimed to evaluate the in vitro biological behaviour of human gingival fibroblasts (HGFs) in contact with an experimental aluminum-free borosilicate glass-functionalized hydrogel. Two types of experimental borosilicate glass particles were utilized, with Biodentine^® particles serving as a reference material. The hydrogel, based on poly(L-lysine) dendrimers (DGL) with or without borosilicate particles, was analyzed using micro-computed tomography (µCT) and scanning electron microscopy (SEM) coupled with energy-dispersive X-ray spectroscopy (EDX). Cytocompatibility was assessed using Live/Dead™ staining, and cell colonization was evaluated via confocal imaging. Additionally, Alizarin red staining was performed to assess mineralization potential after 7 and 14 days. Results indicated that the incorporation of borosilicate particles did not alter hydrogel porosity, while EDX confirmed particle presence on the hydrogel surfaces. Furthermore, the borosilicate-functionalized hydrogels significantly enhanced cell proliferation, colonization, and the content of calcium deposits. These findings highlight the potential of these hydrogels for future clinical applications in dental tissue regeneration, pending further development. Full article

In recent studies, it has been shown that fluorescence lifetime imaging (FLIM) may reveal intracellular structural details in unstained cytological preparations that are not revealed by standard staining procedures. The aim of our investigation was to examine whether FLIM images could reveal areas suggestive of polymerization in red blood cells (RBCs) of sickle cell disease (SCD) patients. We examined label-free blood films using auto-fluorescence FLIM images of 45 SCD patients and compared the results with those of 27 control persons without hematological disease. All control RBCs revealed homogeneous cytoplasm without any foci. Rounded non-sickled RBCs in SCD showed between zero and three small intensively fluorescent dots with higher lifetime values. In sickled RBCs, we found additionally larger irregularly shaped intensively fluorescent areas with increased FLIM values. These areas were interpreted as equivalent to polymerized hemoglobin. The rounded, non-sickled RBCs of SCD patients with homogeneous cytoplasm were not different from those of the erythrocytes of control patients in light microscopy. Yet, variables from the local binary pattern-transformed matrix of the FLIM values per pixel showed significant differences between non-sickled RBCs and those of control cells. In a linear discriminant analysis, using local binary pattern-transformed texture features (mean and entropy) of the erythrocyte cytoplasm of normal appearing cells, the final model could distinguish between SCD patients and control persons with an accuracy of 84.7% of the patients. When the classification was based on the examination of a single rounded erythrocyte, an accuracy of 68.5% was achieved. Employing the Linear Discriminant Analysis classifier method for machine learning, the accuracy was 68.1%. We believe that our study shows that FLIM is able to disclose the topography of the intracellular polymerization process of hemoglobin in sickle cell disease and that the images are compatible with the theory of the two-step nucleation. Furthermore, we think that the presented technique may be an interesting tool for the investigation of therapeutic inhibition of polymerization. Full article

Due to the possible coexistence of Klebsiella pneumoniae (KP) and Candida albicans (CA), strains of KP and CA with biofilm production properties clinically isolated from patients were tested. The production of biofilms from the combined organisms (KP+CA) was higher than the biofilms from each organism alone, as indicated by crystal violet and z-stack immunofluorescence. In parallel, the bacterial abundance in KP + CA was similar to KP, but the fungal abundance was higher than CA (culture method), implying that CA grows better in the presence of KP. Proteomic analysis was performed to compare KP + CA biofilm to KP biofilm alone. With isolated mouse neutrophils (thioglycolate induction), KP + CA biofilms induced less prominent responses than KP biofilms, as determined by (i) neutrophilic supernatant cytokines (ELISA) and (ii) neutrophil extracellular traps (NETs), using immunofluorescent images (neutrophil elastase, myeloperoxidase, and citrullinated histone 3), peptidyl arginine deiminase 4 (PAD4) expression, and cell-free DNA. Likewise, intratracheal KP + CA in C57BL/6 mice induces less severe pneumonia than KP alone, as indicated by organ injury (serum creatinine and alanine transaminase) (colorimetric assays), cytokines (ELISA), bronchoalveolar lavage fluid parameters (bacterial culture and neutrophil abundances using a hemocytometer), histology score (H&E stains), and NETs (immunofluorescence on the lung tissue). In conclusion, the biofilm biomass of KP + CA was mostly produced from CA with less potent neutrophil activation and less severe pneumonia than KP alone. Hence, fungi in the respiratory tract might benefit the host in some situations, despite the well-known adverse effects of fungi. Full article

With the recent surge in the development of highly selective probes, fluorescence microscopy has become one of the most widely used approaches to studying cellular properties and signaling in living cells and tissues. Traditionally, microscopy image analysis heavily relies on manufacturer-supplied software, which often demands extensive training and lacks automation capabilities for handling diverse datasets. A critical challenge arises if the fluorophores employed exhibit low brightness and a low signal-to-noise ratio (SNR). Consequently, manual intervention may become a necessity, introducing variability in the analysis outcomes even for identical samples when analyzed by different users. This leads to the incorporation of blinded analysis, which ensures that the outcome is free from user bias to a certain extent but is extremely time-consuming. To overcome these issues, we developed a tool called DL-SCAN that automatically segments and analyzes fluorophore-stained regions of interest such as cell bodies in fluorescence microscopy images using deep learning. We demonstrate the program’s ability to automate cell identification and study cellular ion dynamics using synthetic image stacks with varying SNR. This is followed by its application to experimental Na⁺ and Ca²⁺ imaging data from neurons and astrocytes in mouse brain tissue slices exposed to transient chemical ischemia. The results from DL-SCAN are consistent, reproducible, and free from user bias, allowing efficient and rapid analysis of experimental data in an objective manner. The open-source nature of the tool also provides room for modification and extension to analyze other forms of microscopy images specific to the dynamics of different ions in other cell types. Full article

Background: 25 to 50% of patients suffering from colorectal cancer develop liver metastases. The incidence of regional lymph node (LN) metastases within the liver is up to 14%. The need for perihilar lymph node dissection (LND) is still a controversial topic in patients with colorectal liver metastases (CRLM). This study investigates the role of perihilar LND in patients with CRLM. Methods: For this retrospective study, patients undergoing surgery for CRLM at the University Hospital Basel between May 2009 and December 2021 were included. In patients with perihilar LND, LN were stained for CK22 and examined for single tumour cells (<0.2 mm), micro- (0.2–2 mm), and macro-metastases (>2 mm). Results: 112 patients undergoing surgery for CRLM were included. 54 patients underwent LND, 58/112 underwent liver resection only (LR). 3/54 (5.6%) showed perihilar LN metastases in preoperative imaging, and in 10/54 (18.5%), micro-metastases could be proven after CK22 staining. Overall complications were similar in both groups (LND: 46, 85.2%; LR: 48, 79.3%; p = 0.800). The rate of major complications was higher in the LND group (LND: 22, 40.7%; LR: 18, 31%, p = 0.002). Median recurrence-free survival (RFS) (LND: 10 months; LR: 15 months, p = 0.076) and overall survival (OS) were similar (LND: 49 months; LR: 60 months, p = 0.959). Conclusion: Preoperative imaging is not sensitive enough to detect perihilar LN metastases. Perihilar LND enables precise tumour staging by detecting more lymph node metastases, especially through CK22 staining. However, perihilar LND does not influence oncologic outcomes in patients with CRLM. Full article

Deep learning has achieved remarkable progress in medical image analysis, but its effectiveness heavily relies on large-scale and well-annotated datasets. However, assembling a large-scale dataset of annotated histopathological images is challenging due to their unique characteristics, including various image sizes, multiple cancer types, and staining variations. Moreover, strict data privacy in medicine severely restricts data sharing and poses significant challenges in acquiring large-scale and well-annotated histopathological images. To tackle these constraints, Transfer Learning (TL) provides a promising solution by exploiting knowledge from another domain. This study proposes the Uncertainty-guided asymmetric Consistency Domain Adaptation (UCDA), which does not require accessing the source data and is composed of two essential components, e.g., Uncertainty-guided Source-free Transfer Learning (USTL) and Asymmetric Consistency Learning (ACL). In detail, USTL facilitates a secure mapping of the source domain model’s feature space onto the target domain, eliminating the dependency on source domain data to protect data privacy. At the same time, the ACL module measures the symmetry and asymmetry between the source and target domains, bridging the information gap and preserving inter-domain differences among medical images. We comprehensively evaluate the effectiveness of UCDA on three widely recognized and publicly available datasets, namely NCTCRC-HE-100K, PCam, and LC25000. Impressively, our proposed method achieves remarkable performance on accuracy and F1-scores. Additionally, feature visualizations effectively demonstrate the exceptional generalizability and discriminative power of the learned representations. These compelling results underscore the significant potential of UCDA in driving the advancement of deep learning techniques within the realm of histopathological image analysis. Full article

Oral potentially malignant disorders (OPMDs) are precursors to over 80% of oral cancers. Hematoxylin and eosin (H&E) staining, followed by pathologist interpretation of tissue and cellular morphology, is the current gold standard for diagnosis. However, this method is qualitative, can result in errors during the multi-step diagnostic process, and results may have significant inter-observer variability. Chemical imaging (CI) offers a promising alternative, wherein label-free imaging is used to record both the morphology and the composition of tissue and artificial intelligence (AI) is used to objectively assign histologic information. Here, we employ quantum cascade laser (QCL)-based discrete frequency infrared (DFIR) chemical imaging to record data from oral tissues. In this proof-of-concept study, we focused on achieving tissue segmentation into three classes (connective tissue, dysplastic epithelium, and normal epithelium) using a convolutional neural network (CNN) applied to three bands of label-free DFIR data with paired darkfield visible imaging. Using pathologist-annotated H&E images as the ground truth, we demonstrate results that are 94.5% accurate with the ground truth using combined information from IR and darkfield microscopy in a deep learning framework. This chemical-imaging-based workflow for OPMD classification has the potential to enhance the efficiency and accuracy of clinical oral precancer diagnosis. Full article

The assessment of programmed death-ligand 1 (PD-L1) expression in esophageal squamous cell carcinoma (ESCC) has become increasingly important with the rise of immune checkpoint inhibitors (ICIs). However, challenges persist, including subjective interpretation and the unclear significance of staining intensity, as well as contrasting roles in tumoral and stromal regions. Our study enhances the understanding of PD-L1 in ESCCs by analyzing its expression in tumors and stroma with H-scores, highlighting its distinct clinicopathological impacts. In a retrospective cohort of 194 ESCC specimens from surgical resection, we quantified PD-L1 expression in tumoral and stromal compartments using H-scores, analyzing whole slide images with digital pathology analysis software. Kaplan–Meier analysis demonstrated that higher PD-L1 expression is significantly associated with improved postoperative overall survival (OS) and recurrence-free survival (RFS) in both tumoral and stromal areas. Multivariable analysis identified high tumoral PD-L1 expression as an independent prognostic factor for prolonged OS and RFS (HR = 0.47, p = 0.007; HR = 0.54, p = 0.022, respectively). In a separate analysis, high stromal PD-L1 expression was found to correlate with less advanced pathological stages and a prolonged response to cytotoxic chemotherapy, with no similar correlation found for ICI treatment response. This study reveals PD-L1’s contrasting role in the ESCC tumor immune microenvironment, impacting prognosis, tumor stage, and treatment response. Full article

Nonlinear microscopy (NM) enables us to investigate the morphology or monitor the physiological processes of the skin through the use of ultrafast lasers. Fiber (or fiber-coupled) lasers are of great interest because they can easily be combined with a handheld, scanning nonlinear microscope. This latter feature greatly increases the utility of NM for pre-clinical applications and in vivo tissue imaging. Here, we present a fiber-coupled, sub-ps Ti–sapphire laser system being optimized for in vivo, stain-free, 3D imaging of skin alterations with a low thermal load of the skin. The laser is pumped by a low-cost, 2.1 W, 532 nm pump laser and delivers 0.5–1 ps, high-peak-power pulses at a ~20 MHz repetition rate. The spectral bandwidth of the laser is below 2 nm, which results in a low sensitivity for dispersion during fiber delivery. The reduction in the peak intensity due to the increased pulse duration is compensated by the lower repetition rate of our laser. In our proof-of-concept imaging experiments, a ~1.8 m long, commercial hollow-core photonic bandgap fiber was used for fiber delivery. Fresh and frozen skin biopsies of different skin alterations (e.g., adult hemangioma, basal cell cancer) and an unaffected control were used for high-quality, two-photon excitation fluorescence microscopy (2PEF) and second-harmonic generation (SHG) z-stack (3D) imaging. Full article