Unstained Samples Research Articles

Differential phase contrast intensity diffraction tomography.

Intensity diffraction tomography (IDT) is a label-free computational microscopy technique that infers 3D refractive index (RI) and absorption distributions of objects from intensity-only measurements. Nevertheless, the inherent coherent image formation model requires sequential intensity measurements under various plane wave illuminations, resulting in time-consuming data acquisition and low imaging speed. In this Letter, we propose differential phase contrast intensity diffraction tomography (DPC-IDT), which leverages partially coherent illumination to extend the accessible spectrum range, thereby achieving high-speed, motion-free 3D tomographic microscopy. DPC-IDT integrates DPC illumination within the IDT framework, allowing 3D RI tomogram reconstruction from only four intensity images under matched asymmetric annular illumination. The effectiveness of DPC-IDT is experimentally validated by RI measurements of standard microspheres. We also demonstrate dynamic 3D imaging results of living PLC cells at a 25 Hz volume rate, highlighting its potential for high-speed biological imaging of unstained samples.

A Planar Darkfield Illuminator for Wide‐Field High‐Contrast Imaging of Specimens in Microfluidic Chips

AbstractDarkfield microscopy is an effective technique and well suited for use involving live and unstained biological samples, where a bulky condenser should be precisely aligned in the optical path to produce a cone of illumination light. Here, a compact darkfield illuminator is invented that has a planar shape and can work at broadband wavelengths. It can be easily incorporated into a conventional microscope as a substrate to produce hollow cones of light for large‐area darkfield illumination, resulting in a high‐contrast high‐sensitivity widefield microscopy images. Taking advantages of its planar and compact structure, this darkfield illuminator is successfully integrated with a microfluidic chip; thus, the actions and reactions of biological and chemical specimens flowing inside micrometer‐sized channels, can be real‐time imaged with high contrast and sensitivity in a large field‐of‐view (FoV). For the first time, the work integrates a compact darkfield illuminator with microfluidic chips, which produces a new platform for applications in biology, chemistry, and biomedical engineering.

Autofluorescence-based tissue characterization enhances clinical prospects of light-sheet-microscopy

Light sheet fluorescence microscopy (LSFM) is a transformative imaging method that enables the visualization of non-dissected specimen in real-time 3D. Optical clearing of tissues is essential for LSFM, typically employing toxic solvents. Here, we test the applicability of a non-hazardous alternative, ethyl cinnamate (ECi). We comprehensively characterized autofluorescence (AF) spectra in diverse murine tissues—ocular globe, knee, and liver—employing LSFM under various excitation wavelengths (405–785 nm) to test the feasibility of unstained samples for diagnostic purposes, in particular regarding percutaneous biopsies, as they constitute to most harvested type of tissue sample in clinical routine. Ocular globe structures were best discerned with 640 nm excitation. Knee tissue showed complex variation in AF spectra variation influenced by tissue depth and structure. Liver exhibited a unique AF pattern, likely linked to vasculature. Hepatic tissue samples were used to demonstrate the compatibility of our protocol for antibody staining. Furthermore, we employed machine learning to augment raw images and segment liver structures based on AF spectra. Radiologists rated representative samples transferred to the clinical assessment software. Learning-generated images scored highest in quality. Additionally, we investigated an actual murine biopsy. Our study pioneers the application of AF spectra for tissue characterization and diagnostic potential of optically cleared unstained percutaneous biopsies, contributing to the clinical translation of LSFM.

Deep learning-based virtual H& E staining from label-free autofluorescence lifetime images

Label-free autofluorescence lifetime is a unique feature of the inherent fluorescence signals emitted by natural fluorophores in biological samples. Fluorescence lifetime imaging microscopy (FLIM) can capture these signals enabling comprehensive analyses of biological samples. Despite the fundamental importance and wide application of FLIM in biomedical and clinical sciences, existing methods for analysing FLIM images often struggle to provide rapid and precise interpretations without reliable references, such as histology images, which are usually unavailable alongside FLIM images. To address this issue, we propose a deep learning (DL)-based approach for generating virtual Hematoxylin and Eosin (H&E) staining. By combining an advanced DL model with a contemporary image quality metric, we can generate clinical-grade virtual H&E-stained images from label-free FLIM images acquired on unstained tissue samples. Our experiments also show that the inclusion of lifetime information, an extra dimension beyond intensity, results in more accurate reconstructions of virtual staining when compared to using intensity-only images. This advancement allows for the instant and accurate interpretation of FLIM images at the cellular level without the complexities associated with co-registering FLIM and histology images. Consequently, we are able to identify distinct lifetime signatures of seven different cell types commonly found in the tumour microenvironment, opening up new opportunities towards biomarker-free tissue histology using FLIM across multiple cancer types.

Unbiased method for spectral analysis of cells with great diversity of autofluorescence spectra.

Autofluorescence is an intrinsic feature of cells, caused by the natural emission of light by photo-excitatory molecular content, which can complicate analysis of flow cytometry data. Different cell types have different autofluorescence spectra and, even within one cell type, heterogeneity of autofluorescence spectra can be present, for example, as a consequence of activation status or metabolic changes. By using full spectrum flow cytometry, the emission spectrum of a fluorochrome is captured by a set of photo detectors across a range of wavelengths, creating an unique signature for that fluorochrome. This signature is then used to identify, or unmix, that fluorochrome's unique spectrum from a multicolor sample containing different fluorescent molecules. Importantly, this means that this technology can also be used to identify intrinsic autofluorescence signal of an unstained sample, which can be used for unmixing purposes and to separate the autofluorescence signal from the fluorophore signals. However, this only works if the sample has a singular, relatively homogeneous and bright autofluorescence spectrum. To analyze samples with heterogeneous autofluorescence spectral profiles, we setup an unbiased workflow to more quickly identify differing autofluorescence spectra present in a sample to include as "autofluorescence signatures" during the unmixing of the full stained samples. First, clusters of cells with similar autofluorescence spectra are identified by unbiased dimensional reduction and clustering of unstained cells. Then, unique autofluorescence clusters are determined and are used to improve the unmixing accuracy of the full stained sample. Independent of the intensity of the autofluorescence and immunophenotyping of cell subsets, this unbiased method allows for the identification of most of the distinct autofluorescence spectra present in a sample, leading to less confounding autofluorescence spillover and spread into extrinsic phenotyping markers. Furthermore, this method is equally useful for spectral analysis of different biological samples, including tissue cell suspensions, peripheral blood mononuclear cells, and in vitro cultures of (primary) cells.

Interlaboratory comparison of high-throughput protein biomarker assay quantifications for radiation exposure classification.

In the event of a widespread radiological incident, thousands of individuals will require rapid assessment of exposure using validated biodosimetry assays to inform clinical triage. In this scenario, multiple biodosimetry laboratories may be necessary for large-volume sample processing. To meet this need, we have developed a high-throughput assay for the rapid measurement of intracellular protein biomarkers in human peripheral blood samples using an Imaging Flow Cytometry (IFC) platform. The objective of this work was to harmonize and validate the reproducibility of our blood biomarker assay for radiation exposure across three IFC instruments, two located at Columbia University (CU) and the third at Health Canada. The Center for Radiological Research (CRR) at CU served as the central laboratory and reference instrument, where samples were prepared in triplicate, labeled with two radiation responsive leukocyte biomarkers (BAX and phosphor-p53 (Ser37)), and distributed for simultaneous interrogation by each IFC. Initial tests showed that significantly different baseline biomarker measurements were generated on each instrument when using the same acquisition settings, suggesting that harmonization of signal intensities is necessary. Subsequent tests harmonized biomarker measurements after irradiation by modulating laser intensity using two reference materials: unstained samples and standardized rainbow beads. Both methods generated measurements on each instrument without significant differences between the new and references instruments, allowing for the use of one master template to quantify biomarker expression across multiple instruments. Deming regression analyses of 0-5 Gy dose-response curves showed overall good correlation of BAX and p53 values across new and reference instruments. While Bland-Altman analyses indicated low to moderate instrument biases, ROC Curve analyses ultimately show successful discrimination between exposed and unexposed samples on each instrument (AUC values > 0.85).

Single-shot differential phase contrast microscopy using ring-shaped polarisation multiplexing illumination.

We propose a differential phase contrast microscopy that enables single-shot phase imaging for unstained biological samples. The proposed approach employs a ring-shaped LED array for polarisation multiplexing illumination and a polarisation camera for image acquisition. As such, multiple images of different polarisation angles can be simultaneously captured with a single shot. Through polarisation demultiplexing, the sample phase can therefore be recovered from the single-shot measurement. Both simulations and experiments demonstrate the effectiveness of the approach. We also demonstrate that ring-shaped illumination enables higher contrast and lower-distortion imaging results than disk-shaped illumination does. The proposed single-shot approach potentially enables phase contrast imaging for live cell samples in vitro. Lay Description: We propose a microscopy that enables imaging of transparent samples, unstained cells, etc. We demonstrate that the proposed method enables higher contrast and lower-distortion imaging results than conventional methods, and significantly improves imaging efficiency. The proposed method potentially enables dynamic imaging for live cell samples in vitro.

Grading of glioma tumors using digital holographic microscopy

Gliomas are the most common type of cerebral tumors; they occur with increasing incidence in the last decade and have a high rate of mortality. For efficient treatment, fast accurate diagnostic and grading of tumors are imperative. Presently, the grading of tumors is established by histopathological evaluation, which is a time-consuming procedure and relies on the pathologists’ experience. Here we propose a supervised machine learning procedure for tumor grading which uses quantitative phase images of unstained tissue samples acquired by digital holographic microscopy. The algorithm is using an extensive set of statistical and texture parameters computed from these images. The procedure has been able to classify six classes of images (normal tissue and five glioma subtypes) and to distinguish between gliomas types from grades II to IV (with the highest sensitivity and specificity for grade II astrocytoma and grade III oligodendroglioma and very good scores in recognizing grade III anaplastic astrocytoma and grade IV glioblastoma). The procedure bolsters clinical diagnostic accuracy, offering a swift and reliable means of tumor characterization and grading, ultimately the enhancing treatment decision-making process.

Multi-wavelength interference phase imaging for automatic breast cancer detection and delineation using diffuse reflection imaging

Millions of women globally are impacted by the major health problem of breast cancer (BC). Early detection of BC is critical for successful treatment and improved survival rates. In this study, we provide a progressive approach for BC detection using multi-wavelength interference (MWI) phase imaging based on diffuse reflection hyperspectral (HS) imaging. The proposed findings are based on the measurement of the interference pattern between the blue (446.6 nm) and red (632 nm) wavelengths. We consider implementing a comprehensive image processing and categorization method based on the use of Fast Fourier (FF) transform analysis pertaining to a change in the refractive index between tumor and normal tissue. We observed that cancer growth affects tissue organization dramatically, as seen by persistently increased refractive index variance in tumors compared normal areas. Both malignant and normal tissue had different depth data collected from it that was analyzed. To enhance the categorization of ex-vivo BC tissue, we developed and validated a training classifier algorithm specifically designed for categorizing HS cube data. Following the application of signal normalization with the FF transform algorithm, our methodology achieved a high level of performance with a specificity (Spec) of 94% and a sensitivity (Sen) of 90.9% for the 632 nm acquired image categorization, based on preliminary findings from breast specimens under investigation. Notably, we successfully leveraged unstained tissue samples to create 3D phase-resolved images that effectively highlight the distinctions in diffuse reflectance features between cancerous and healthy tissue. Preliminary data revealed that our imaging method might be able to assist specialists in safely excising malignant areas and assessing the tumor bed following resection automatically at different depths. This preliminary investigation might result in an effective "in-vivo" disease description utilizing optical technology using a typical RGB camera with wavelength-specific operation with our quantitative phase MWI imaging methodology.

Imaging of excised cochleae by micro-CT: staining, liquid embedding, and image modalities.

Assessing the complex three-dimensional (3D) structure of the cochlea is crucial to understanding the fundamental aspects of signal transduction in the inner ear and is a prerequisite for the development of novel cochlear implants. X-ray phase-contrast computed tomography offers destruction-free 3D imaging with little sample preparation, thus preserving the delicate structure of the cochlea. The use of heavy metal stains enables higher contrast and resolution and facilitates segmentation of the cochlea. For μ-CT of small animal and human cochlea, we explore the heavy metal osmium tetroxide (OTO) as a radiocontrast agent and delineate laboratory from synchrotron CT. We investigate how phase retrieval can be used to improve the image quality of the reconstructions, both for stained and unstained specimens. Image contrast for soft tissue in an aqueous solution is insufficient under the in-house conditions, whereas the OTO stain increases contrast for lipid-rich tissue components, such as the myelin sheaths in nervous tissue, enabling contrast-based rendering of the different components of the auditory nervous system. The overall morphology of the cochlea with the three scalae and membranes is very well represented. Further, the image quality of the reconstructions improves significantly when a phase retrieval scheme is used, which is also suitable for non-ideal laboratory settings. With highly brilliant synchrotron radiation (SR), we achieve high contrast for unstained whole cochleae at the cellular level. The OTO stain is suitable for 3D imaging of small animal and human cochlea with laboratory , and relevant pathologies, such as a loss of sensory cells and neurons, can be visualized. With SR and optimized phase retrieval, the cellular level can be reached even for unstained samples in aqueous solution, as demonstrated by the high visibility of single hair cells and spiral ganglion neurons.

Screening adequacy of unstained thyroid fine needle aspiration samples using a deep learning-based classifier

Fine needle aspiration (FNA) biopsy of thyroid nodules is a safe, cost-effective, and accurate diagnostic method for detecting thyroid cancer. However, about 10% of initial FNA biopsy samples from patients are non-diagnostic and require repeated FNA, which delays the diagnosis and appropriate care. On-site evaluation of the FNA sample can be performed to filter out non-diagnostic FNA samples. Unfortunately, it involves a time-consuming staining process, and a cytopathologist has to be present at the time of FNA. To bypass the staining process and expert interpretation of FNA specimens at the clinics, we developed a deep learning-based ensemble model termed FNA-Net that allows in situ screening of adequacy of unstained thyroid FNA samples smeared on a glass slide which can decrease the non-diagnostic rate in thyroid FNA. FNA-Net combines two deep learning models, a patch-based whole slide image classifier and Faster R-CNN, to detect follicular clusters with high precision. Then, FNA-Net classifies sample slides to be non-diagnostic if the total number of detected follicular clusters is less than a predetermined threshold. With bootstrapped sampling, FNA-Net achieved a 0.81 F1 score and 0.84 AUC in the precision-recall curve for detecting the non-diagnostic slides whose follicular clusters are less than six. We expect that FNA-Net can dramatically reduce the diagnostic cost associated with FNA biopsy and improve the quality of patient care.

Meta-Surface Slide for High-Contrast Dark-Field Imaging

A label-free microscopy technology, dark-field microscopy, is widely used for providing high-contrast imaging for weakly scattering materials and unstained samples. However, traditional dark-field microscopes often require additional components and larger condensers as the numerical aperture increases. A solution to this is the use of a meta-surface slide. This slide utilizes a multilayer meta-surface and quantum dots to convert incident white light into a red glow cone emitted at a larger angle. This enables the slide to be used directly with conventional biological microscopy to achieve dark-field imaging. This paper focuses on the design and preparation of the meta-surface and demonstrates that using the meta-surface in a standard transmission optical microscope results in a dark-field image with higher contrast than a bright-field image, especially when observing samples with micron-sized structures.

Stimulated Raman histology as a method to determine the adequacy of renal mass biopsy and identify malignant subtypes of renal cell carcinoma.

Renal tumor biopsy requires adequate tissue sampling to aid in the investigation of small renal masses. In some centers the contemporary nondiagnostic renal mass biopsy rate may be as high as 22% and may be as high as 42% in challenging cases. Stimulated Raman Histology (SRH) is a novel microscopic technique which has created the possibility for rapid, label-free, high-resolution images of unprocessed tissue which may beviewed onstandard radiology viewing platforms. The application of SRH to renal biopsy may provide the benefits of routine pathologic evaluation during the procedure, thereby reducing nondiagnostic results. We conducted a pilot feasibility study, to assess if renal cell carcinoma (RCC) subtypes may be imaged and to see if high-quality hematoxylin and eosin (H&E) could subsequently be generated. An 18-gauge core needle biopsy was taken from a series of 25 ex vivo radical or partial nephrectomy specimens. Histologic images of the fresh, unstained biopsy samples were obtained using a SRH microscope using 2 Raman shifts: 2,845 cm-1and 2,930 cm-1. The cores were then processed as per routine pathologic protocols. The SRH images and hematoxylin and eosin (H&E) slides were then viewed by a genitourinary pathologist. The SRH microscope took 8 to 11 minutes to produce high-quality images of the renal biopsies. Total of 25 renal tumors including 1 oncocytoma, 3 chromophobe RCC, 16 clear cells RCC, 4 papillary RCC, and 1 medullary RCC were included. All renal tumor subtypes were captured, and the SRH images were easily differentiated from adjacent normal renal parenchyma. High quality H&E slides were produced from each of the renal biopsies after SRH was completed. Immunostains were performed on selected cases and the staining was not affected by the SRH image process. SRH produces high quality images of all renal cell subtypes that can be rapidly produced and easily interpreted to determine renal mass biopsy adequacy, and on occasion, may allow renal tumor subtype identification. Renal biopsies remained available to produce high quality H&E slides and immunostains for confirmation of diagnosis. Procedural application has promise to decrease the known rate of renal mass nondiagnostic biopsies, and application of convolutional neural network methodology may further improve diagnostic capability and increase utilization of renal mass biopsy among urologists.

Epididymal stallion sperm quality improves with single layer centrifugation prior to cryopreservation or post-thawing

Cryopreservation of epididymal spermatozoa is the last method for preserving gametes of valuable stallions in case of sudden death, severe injuries, or orchiectomy. Due to harvesting methods, sperm is unavoidably contaminated with epithelial and red blood cells, leukocytes, debris, and bacteria. These contaminants and dead spermatozoa can cause detrimental effects on sperm quality. Colloid centrifugation can reduce the load of these contaminants and select a subpopulation of motile spermatozoa. The objective of this experiment was to evaluate whether single layer centrifugation (SLC) prior to cryopreservation or post-thawing improves the quality of stallion epididymal sperm. Ten stallions were submitted to bilateral orchiectomy and harvesting of epididymal cauda spermatozoa (n=20) was performed by retrograde flushing with an extender. Epididymal sperm samples were subjected to conventional centrifugation (no colloid - 600xg for 20 minutes), and SLC prior to cryopreservation (SLC-PC) or SLC post-thaw (SLC+). SLC was performed at 300 x g for 10 minutes (Androcoll-Equine, Minitube, Tiefenbach, Germany). All samples were cryopreserved, thawed, and evaluated. The post-thaw group (SLC+) was thawed, centrifuged by SLC, and resuspended in freezing extender (SLC+F) or cooling extender (SLC+C). Total motility and progressive motility were evaluated with computer-assisted semen analyses (CASA). Sperm morphology was evaluated by examining a wetmount preparation of unstained samples fixed in formol saline. Mitochondrial functionality, membrane integrity, and DNA integrity were evaluated in a fluorescence microscope with specific fluorescent dyes. All variables were normally distributed according to the Shapiro–Wilk test. Data were evaluated by descriptive statistics, one-way analysis of variance, and Tukey's test. Significance was set at p <0.05. SLC-PC (24.6 ± 3.6%) and SLC+F (26.2 ± 4%) treatments yielded significantly higher total sperm motility than SLC+C (16.7 ± 1.7%) and conventional (16 ± 3.5%) treatment. SLC+F (17.5 ± 3.8%) yielded significantly higher progressive motility than the conventional (8.8 ± 2%), SLC+C (9.8 ± 1.3%), and SLC-PC (12.9 ± 4.1%) treatments. The mitochondrial functionality of all SLC groups was significantly higher (SLC-PC 72 ± 2%; SLC+C 74.6 ± 1.8%; SLC+F 82.5 ± 1.9%), than that of the conventional group (25.2 ± 2.1%). Plasma membrane integrity was higher in SLC-PC (48.6 ± 4%) than in SLC+F (30 ± 6.5%), SLC+C (36 ± 4.8%), and conventional (22.8 ± 4.5%) samples. DNA integrity and percentage of morphologically normal samples were unaffected by treatment. SLC is a simple procedure that can be performed prior to cryopreservation or post-thawing and that can improve stallion epididymal sperm quality. Epididymal spermatozoa submitted to SLC only after thawing is best extended using freezing extender than cooling extender.

Linear polarimetry for analysis of skin degenerative alterations

Investigation and characterization of the basic polarimetric characteristics on different cutaneous degenerative conditions (Syndrome of Raynaud, lupus, and psoriasis) histological samples was carried out to evaluate the potential for analysis of skin degenerative alterations. Stained and unstained histological samples from the different groups of degenerative conditions of the skin were histologically addressed and were used for polarimetric measurements. Diode laser linearly polarized beam at 635 nm was used for irradiation of the samples and polarimeter, working in the visible spectral range 400-700 nm was applied for polarimetric measurements. We will present the results of histology tissue slides evaluation through Stokes polarimetry in transmission geometry. These studies allow analysis of skin degenerative alterations in collagen anisotropic structuration in extracellular matrix and could be used as indicators of the tissue condition. Therefore, the present work would make possible the establishment of database with polarimetric features of degenerative skin conditions.

Urany-Less Low Voltage Transmission Electron Microscopy: A Powerful Tool for Ultrastructural Studying of Cyanobacterial Cells.

Sample preparation protocols for conventional high voltage transmission electron microscopy (TEM) heavily rely on the usage of staining agents containing various heavy metals, most commonly uranyl acetate and lead citrate. However high toxicity, rising legal regulations, and problematic waste disposal of uranyl acetate have increased calls for the reduction or even complete replacement of this staining agent. One of the strategies for uranyless imaging is the employment of low-voltage transmission electron microscopy. To investigate the influence of different imaging and staining strategies on the final image of cyanobacterial cells, samples stained by uranyl acetate with lead citrate, as well as unstained samples, were observed using TEM and accelerating voltages of 200 kV or 25 kV. Moreover, to examine the possibilities of reducing chromatic aberration, which often causes issues when imaging using electrons of lower energies, samples were also imaged using a scanning transmission electron microscopy at 15 kV accelerating voltages. The results of this study demonstrate that low-voltage electron microscopy offers great potential for uranyless electron microscopy.

Laser ablation tomography (LATscan) as a new tool for anatomical studies of woody plants.

Traditionally, botanists study plant anatomy by carefully sectioning samples, histological staining to highlight tissues of interests, then imaging slides under light microscopy. This approach generates significant details; however, this workflow is laborious, particularly in woody vines (lianas) with heterogeneous anatomies, and ultimately yields two-dimensional (2D) images. Laser ablation tomography (LATscan) is a high-throughput imaging system that yields hundreds of images per minute. This method has proven useful for studying the structure of delicate plant tissues; however, its utility in understanding the structure of woody tissues is underexplored. We report LATscan-derived anatomical data from several stems of lianas (c. 20 mm) of seven species and compare these results with those obtained through traditional anatomical techniques. LATscan successfully allows the description of tissue composition by differentiating cell type, size, and shape, but also permits the recognition of distinct cell wall composition (e.g. lignin, suberin, cellulose) based on differential fluorescent signals on unstained samples. LATscan generate high-quality 2D images and 3D reconstructions of woody plant samples; therefore, this new technology is useful for both qualitative and quantitative analyses. This high-throughput imaging technology has the potential to bolster phenotyping of vegetative and reproductive anatomy, wood anatomy, and other biological systems.

Emerging technology for intraoperative margin assessment and post-operative tissue diagnosis for breast-conserving surgery

IntroductionTissue-preserving surgery is utilized progressively in cancer therapy, where a clear surgical margin is critical to avoid cancer recurrence, specifically in breast cancer (BC) surgery. The Intraoperative pathologic approaches that rely on tissue segmenting and staining have been recognized as the ground truth for BC diagnosis. Nevertheless, these methods are constrained by its complication and timewasting for tissue preparation. ObjectiveWe present a non-invasive optical imaging system incorporating a hyperspectral (HS) camera to discriminate between cancerous and non-cancerous tissues in ex-vivo breast specimens, which could be an intraoperative diagnostic technique to aid surgeons during surgery and later a valuable tool to assist pathologists. MethodsWe have established a hyperspectral Imaging (HSI) system comprising a push-broom HS camera at wavelength 380∼1050 nm with source light 390∼980 nm. We have measured the investigated samples' diffuse reflectance (Rd), fixed on slides from 30 distinct patients incorporating mutually normal and ductal carcinoma tissue. The samples were divided into two groups, stained tissues during the surgery (control group) and unstained samples (test group), both captured with the HSI system in the visible and near-infrared (VIS-NIR) range. Then, to address the problem of the spectral nonuniformity of the illumination device and the influence of the dark current, the radiance data were normalized to yield the radiance of the specimen and neutralize the intensity effect to focus on the spectral reflectance shift for each tissue. The selection of the threshold window from the measured Rd is carried out by exploiting the statistical analysis by calculating each region's mean and standard deviation. Afterward, we selected the optimum spectral images from the HS data cube to apply a custom K-means algorithm and contour delineation to identify the regular districts from the BC regions. ResultsWe noticed that the measured spectral Rd for the malignant tissues of the investigated case studies versus the reference source light varies regarding the cancer stage, as sometimes the Rd is higher for the tumor or vice versa for the normal tissue. Later, from the analysis of the whole samples, we found that the most appropriate wavelength for the BC tissues was 447 nm, which was highly reflected versus the normal tissue. However, the most convenient one for the normal tissue was at 545 nm with high reflection versus the BC tissue. Finally, we implement a moving average filter for noise reduction and a custom K-means clustering algorithm on the selected two spectral images (447, 551 nm) to identify the various regions and effectively-identified spectral tissue variations with a sensitivity of 98.95%, and specificity of 98.44%. A pathologist later confirmed these outcomes as the ground truth for the tissue sample investigations. ConclusionsThe proposed system could help the surgeon and the pathologist identify the cancerous tissue margins from the non-cancerous tissue with a non-invasive, rapid, and minimum time method achieving high sensitivity up to 98.95%.

Cleaning iron rust compounds from cotton textiles: application to Qing Dynasty armor

A composite structure consisting of cotton fabric and iron sheet was widely used in Qing Dynasty armor. Due to iron sheet corroding easily, the surfaces of cotton fabric were covered with numerous rust compounds, which has a significant negative impact on the relics. In this paper, by taking Qing Dynasty armor relics as the research object, the cleaning process was reported for cotton fabrics stained with corrosion products. Using an orthogonal experiment, rust stained model samples were used to explore a specialized and efficient cleaning process. Results show that the cleaning reagents, including ascorbic acid (mass fraction 10.0 g/L), ethylenediaminetetraacetic acid disodium salt (EDTA-2Na, mass fraction 10.0 g/L), and the surfactant composed of 70% rhamnolipid and 30% alkyl glycoside (mass fraction 8.0 g/L), could fully exert a synergistic effect. After treatment, the color difference (ΔE) value between the cleaned sample and the unstained sample is only 3.81. A series of comprehensive experimental results demonstrate that the cleaning procedure is effective and safe. There are almost no rust compounds and cleaning reagent residues, and no damage to cotton fiber. The reported wet cleaning process, aided by soft bristle brush, achieved good cleaning results, indicating that the process can be used to clean rust stain pollutants in Qing dynasty cotton armor.

Terahertz imaging of human skin pathologies using laser feedback interferometry with quantum cascade lasers.

Early detection of skin pathologies with current clinical diagnostic tools is challenging, particularly when there are no visible colour changes or morphological cues present on the skin. In this study, we present a terahertz (THz) imaging technology based on a narrow band quantum cascade laser (QCL) at 2.8 THz for human skin pathology detection with diffraction limited spatial resolution. THz imaging was conducted for three different groups of unstained human skin samples (benign naevus, dysplastic naevus, and melanoma) and compared to the corresponding traditional histopathologic stained images. The minimum thickness of dehydrated human skin that can provide THz contrast was determined to be 50 µm, which is approximately one half-wavelength of the THz wave used. The THz images from different types of 50 µm-thick skin samples were well correlated with the histological findings. The per-sample locations of pathology vs healthy skin can be separated from the density distribution of the corresponding pixels in the THz amplitude-phase map. The possible THz contrast mechanisms relating to the origin of image contrast in addition to water content were analyzed from these dehydrated samples. Our findings suggest that THz imaging could provide a feasible imaging modality for skin cancer detection that is beyond the visible.