Optical Biopsy Research Articles

Feasibility of new-generation endocytoscopy for the real-time diagnosis of ampullary lesions: A pilot study (with video).

An early and accurate diagnosis of ampullary neoplasia is crucial; however, sampling bias is still a major concern. New-generation endocytoscopy enables real-time visualization of cellular structures and enables an accurate pathological prediction; however, its feasibility for small ampullary lesions has never been investigated. We developed a novel endocytoscopic (EC) classification system for ampullary lesions after an expert review and agreement from five experienced endoscopists and one pathologist. We then consecutively enrolled a total of 43 patients with an enlarged ampulla (<3cm), all of whom received an endocytoscopic examination. The feasibility of endocytoscopy was evaluated, and the performance of the EC classification system was then correlated with the final histopathology. In five cases (11.6%), the endocytoscope could not approach the ampulla, and these cases were defined as technical failure. Among the remaining 38 patients, 8 had histopathology-confirmed adenocarcinoma, 15 had adenoma, and 15 had non-neoplastic lesions. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the EC classification system to diagnose ampullary neoplasias were 95.7%, 86.7%, 91.7%, 92.9%, and 92.1%, respectively. Moreover, the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the EC classification to diagnose ampullary cancer were 62.5%, 100%, 100%, 90.9%, and 92.1%, respectively. One case with intra-ampullary papillary-tubular carcinoma was classified as having a non-neoplastic lesion by endocytoscopy. Endocytoscopy and the novel EC classification system demonstrated good feasibility to discriminate ampullary neoplasias from non-neoplastic lesions and may be useful for optical biopsies of clinically suspicious ampullary lesions.

A Novel Flexible Endomicroscopic Scanning Instrument with Visual Servoing Control

Optical biopsy using probe‐based confocal laser endomicroscopy (pCLE) and optical coherence tomography (OCT) technologies performs in vivo tissue scanning of organ surfaces and plays a crucial role in early cancer diagnosis. Herein, a flexible endomicroscopic scanning instrument based on a 3‐degree‐of‐freedom flexible hinge structure and visual servoing control is presented. The instrument integrates OCT and pCLE. OCT information compensates for the imaging distance of pCLE, which can combine the advantages of the two technologies. The mechanism allows for tissue surface scanning with a wire‐driven active bending part and dynamic adjustment of the probe‐tissue distance using a combination of wire and spring‐driven, which satisfy large‐area scanning while maintaining consistence tissue contacts. Local optimization‐based visual servoing control is proposed to optimize the tissue scanning. Through the scanning experiments, high‐quality mosaics of uneven surfaces are obtained with an effective area that is larger than 4 mm2. In vivo animal trial further verifies the feasibility and clinical potential of the instrument.

Detection of NADH and NADPH levels in vivo identifies shift of glucose metabolism in cancer to energy production.

Profound changes in the metabolism of cancer cells have been known for almost 100 years, and many aspects of these changes have continued to be actively studied and discussed. Differences in the results of various studies can be explained by the diversity of tumours, which have differing processes of energy metabolism, and by limitations in the methods used. Here, using fluorescence lifetime needle optical biopsy in a hepatocellular carcinoma (HCC) mouse model and patients with HCC, we measured reduced nicotinamide adenine dinucleotide (NADH) and reduced nicotinamide adenine dinucleotide phosphate (NADPH) in control liver, and in HCC tumours and their adjacent regions. We found that NADH level (mostly responsible for energy metabolism) is increased in tumours but also in adjacent regions of the same liver. NADPH level is significantly decreased in the tumours of patients but increased in the HCC mouse model. However, in the ex vivo tumour slices of mouse HCC, reactive oxygen species production and glutathione level (both dependent on NADPH) were significantly suppressed. Thus, glucose-dependent NADH and NADPH production in tumours changed but with a more pronounced shift to energy production (NADH), rather than NADPH synthesis for redox balance.

Comprehensive advancement in endoscopy: optical design, algorithm enhancement, and clinical validation for merged WLI and CBI imaging.

As endoscopic imaging technology advances, there is a growing clinical demand for enhanced imaging capabilities. Although conventional white light imaging (WLI) endoscopy offers realistic images, it often cannot reveal detailed characteristics of the mucosa. On the other hand, optical staining endoscopy, such as Compound Band Imaging (CBI), can discern subtle structures, serving to some extent as an optical biopsy. However, its image brightness is low, and the colors can be abrupt. These two techniques, commonly used in clinical settings, have complementary advantages. Nonetheless, they require different lighting conditions, which makes it challenging to combine their imaging strengths on living tissues. In this study, we introduce a novel endoscopic imaging technique that effectively combines the advantages of both WLI and CBI. Doctors don't need to manually switch between these two observation modes, as they can obtain the image information of both modes in one image. We calibrated an appropriate proportion for simultaneous illumination with the light required for WLI and CBI. We designed a new illumination spectrum tailored for gastrointestinal examination, achieving their fusion at the optical level. Using a new algorithm that focuses on enhancing specific hemoglobin tissue features, we restored narrow-band image characteristics lost due to the introduction of white light. Our hardware and software innovations not only boost the illumination brightness of the endoscope but also ensure the narrow-band feature details of the image. To evaluate the reliability and safety of the new endoscopic system, we conducted a series of tests in line with relevant international standards and validated the design parameters. For clinical trials, we collected a total of 256 sets of images, each set comprising images of the same lesion location captured using WLI, CBI, and our proposed method. We recruited four experienced clinicians to conduct subjective evaluations of the collected images. The results affirmed the significant advantages of our method. We believe that the novel endoscopic system we introduced has vast potential for clinical application in the future.

Optical Biopsies Using Probe-Based Confocal Laser Endomicroscopy for Autoimmune Pulmonary Alveolar Proteinosis

Introduction: Increasing numbers of cases of mild asymptomatic pulmonary alveolar proteinosis (PAP) are being reported with the recent increase in chest computed tomography (CT). Bronchoscopic diagnosis of mild PAP is challenging because of the patchy distribution of lesions, which makes it difficult to obtain sufficient biopsy samples. Additionally, the pathological findings of mild PAP, particularly those that differ from severe PAP, have not been fully elucidated. This study aimed to clarify the pathological findings of mild PAP and the usefulness of optical biopsy using probe-based confocal laser endomicroscopy (pCLE). Methods: We performed bronchoscopic optical biopsy using pCLE and tissue biopsy in 5 consecutive patients with PAP (three with mild PAP and two with severe PAP). We compared the pCLE images of mild PAP with those of severe PAP by integrating clinical findings, tissue pathology, and chest CT images. Results: pCLE images of PAP showed giant cells with strong fluorescence, amorphous substances, and thin alveolar walls. Images of affected lesions in mild PAP were equivalent to those obtained in arbitrary lung lesions in severe cases. All 3 patients with mild PAP spontaneously improved or remained stable after ≥3 years of follow-up. Serum autoantibodies to granulocyte-macrophage colony-stimulating factor were detected in all 5 cases. Conclusion: Optical biopsy using pCLE can yield specific diagnostic findings, even in patients with mild PAP. pCLE images of affected areas in mild and severe PAP showed similar findings, indicating that the dysfunction level of pathogenic alveolar macrophages in affected areas is similar between both disease intensities.

Recent advances of biocompatible optical nanobiosensors in liquid biopsy: towards early non-invasive diagnosis.

Liquid biopsy is a non-invasive diagnostic method that can reduce the risk of complications and offers exceptional benefits in the dynamic monitoring and acquisition of heterogeneous cell population information. Optical nanomaterials with excellent light absorption, luminescence, and photoelectrochemical properties have accelerated the development of liquid biopsy technologies. Owing to the unique size effect of optical nanomaterials, their improved optical properties enable them to exhibit good sensitivity and specificity for mitigating signal interference from various molecules in body fluids. Nanomaterials with biocompatible and optical sensing properties play a crucial role in advancing the maturity and diversification of liquid biopsy technologies. This article offers a comprehensive review of recent advanced liquid biopsy technologies that utilize novel biocompatible optical nanomaterials, including fluorescence, colorimetric, photoelectrochemical, and Raman broad-spectrum-based biosensors. We focused on liquid biopsy for the most significant early biomarkers in clinical medicine, and specifically reviewed reports on the effectiveness of optical nanosensing technology in the detection of real patient samples, which may provide basic evidence for the transition of optical nanosensing technology from engineering design to clinical practice. Furthermore, we introduced the integration of optical nanosensing-based liquid biopsy with modern devices, such as smartphones, to demonstrate the potential of the technology in portable clinical diagnosis.

EARLY STAGES OF COLORECTAL CANCER CHARACTERIZATION BY AUTOFLUORESCENCE 3D MICROSCOPY: A PRELIMINARY STUDY.

Colorectal cancer is one of the most prevalent pathologies worldwide whose prognosis is linked to early detection. Colonoscopy is the gold standard for screening, and diagnosis is usually made histologically from biopsies. Aiming to reduce the inspection and diagnostic time as well as the biopsies and resources involved, other techniques are being promoted to conduct accurate in vivo colonoscopy assessments. Optical biopsy aims to detect normal and neoplastic tissues analysing the autofluorescence spectrum based on the changes in the distribution and concentration of autofluorescent molecules caused by colorectal cancer. Therefore, the autofluorescence contribution analysed by image processing techniques could be an approach to a faster characterization of the target tissue. Quantify intensity parameters through digital processing of two data sets of three-dimensional widefield autofluorescence microscopy images, acquired by fresh colon tissue samples from a colorectal cancer murine model. Additionally, analyse the autofluorescence data to provide a characterization over a volume of approximately 50 µm of the colon mucosa for each image, at second (2nd), fourth (4th) and eighth (8th) weeks after colorectal cancer induction. Development of a colorectal cancer murine model using azoxymethane/dextran sodium sulphate induction, and data sets acquisition of Z-stack images by widefield autofluorescence microscopy, from control and colorectal cancer induced animals. Pre-processing steps of intensity value adjustments followed by quantification and characterization procedures using image processing workflow automation by Fiji's macros, and statistical data analysis. The effectiveness of the colorectal cancer induction model was corroborated by a histological assessment to correlate and validate the link between histological and autofluorescence changes. The image digital processing methodology proposed was then performed on the three-dimensional images from control mice and from the 2nd, 4th, and 8th weeks after colorectal cancer chemical induction, for each data set. Statistical analyses found significant differences in the mean, standard deviation, and minimum parameters between control samples and those of the 2nd week after induction with respect to the 4th week of the first experimental study. This suggests that the characteristics of colorectal cancer can be detected after the 2nd week post-induction. The use of autofluorescence still exhibits levels of variability that prevent greater systematization of the data obtained during the progression of colorectal cancer. However, these preliminary outcomes could be considered an approach to the three-dimensional characterization of the autofluorescence of colorectal tissue, describing the autofluorescence features of samples coming from dysplasia to colorectal cancer. • A new digital image processing method was developed to measure intensity in 3D autofluorescence images of colorectal samples using a CRC mouse model. • This method showed that autofluorescence intensity in colon mucosa is similar in healthy tissue but changes significantly in tumor development. • Statistical analysis revealed CRC traits detectable from the second week post-induction, aiding in early CRC detection. • The study provides a basis for 3D autofluorescence characterization in colorectal tissue from dysplasia to cancer, although variability in autofluorescence limits data systematization during cancer progression.

Diagnostic accuracy of endocytoscopy via artificial intelligence in colorectal lesions: A systematic review and meta‑analysis.

Endocytoscopy (EC) is a nuclei and micro-vessels visualization in real-time and can facilitate "optical biopsy" and "virtual histology" of colorectal lesions. This study aimed to investigate the significance of employing artificial intelligence (AI) in the field of endoscopy, specifically in diagnosing colorectal lesions. The research was conducted under the supervision of experienced professionals and trainees. EMBASE, PubMed, Cochrane Library, Web of Science, Chinese National Knowledge Infrastructure (CNKI) database, and other potential databases were surveyed for articles related to the EC with AI published before September 2023. RevMan (5.40), Stata (14.0), and R software (4.1.0) were used for statistical assessment. Studies that measured the accuracy of EC using AI for colorectal lesions were included. Two authors independently assessed the selected studies and their extracted data. This included information such as the country, literature, total study population, study design, characteristics of the fundamental study and control groups, sensitivity, number of samples, assay methodology, specificity, true positives or negatives, and false positives or negatives. The diagnostic accuracy of EC by AI was determined by a bivariate random-effects model, avoiding a high heterogeneity effect. The ANOVA model was employed to determine the more effective approach. A total of 223 studies were reviewed; 8 articles were selected that included 2984 patients (4241 lesions) for systematic review and meta-analysis. AI assessed 4069 lesions; experts diagnosed 3165 and 5014 by trainees. AI demonstrated high accuracy, sensitivity, and specificity levels in detecting colorectal lesions, with values of 0.93 (95% CI: 0.90, 0.95) and 0.94 (95% CI: 0.73, 0.99). Expert diagnosis was 0.90 (95% CI: 0.85, 0.94), 0.87 (95% CI: 0.78, 0.93), and trainee diagnosis was 0.74 (95% CI: 0.67, 0.79), 0.72 (95% CI: 0.62, 0.80). With the EC by AI, the AUC from SROC was 0.95 (95% CI: 0.93, 0.97), therefore classified as excellent category, expert showed 0.95 (95% CI: 0.93, 0.97), and the trainee had 0.79 (95% CI: 0.75, 0.82). The superior index from the ANOVA model was 4.00 (1.15,5.00), 2.00 (1.15,5.00), and 0.20 (0.20,0.20), respectively. The examiners conducted meta-regression and subgroup analyses to evaluate the presence of heterogeneity. The findings of these investigations suggest that the utilization of NBI technology was correlated with variability in sensitivity and specificity. There was a lack of solid evidence indicating the presence of publishing bias. The present findings indicate that using AI in EC can potentially enhance the efficiency of diagnosing colorectal abnormalities. As a valuable instrument, it can enhance prognostic outcomes in ordinary EC procedures, exhibiting superior diagnostic accuracy compared to trainee-level endoscopists and demonstrating comparability to expert endoscopists. The research is subject to certain constraints, namely a limited number of clinical investigations and variations in the methodologies used for identification. Consequently, it is imperative to conduct comprehensive and extensive research to enhance the precision of diagnostic procedures.

Femtosecond optical Kerr effect in normal and grades of cancerous breast tissues as a new optical biopsy method.

This study reports on the first use of the optical Kerr effect (OKE) in breast cancer tissue. This proposed optical biopsy method utilizes a Femtosecond Optical Kerr Gate to detect changes in dielectric relaxation and conductivity created by a cancerous infection. Here, the temporal behavior of the OKE is tracked in normal and cancerous samples of human and mouse breast. These tissues display a double peaked temporal structure and its decay rate changes depending on the tissue's infection status. The decay of the secondary peak, attributed to ultrafast plasma response, indicates that the tissue's conductivity has doubled once infected. A slower molecular contribution to the Kerr effect can also be observed in healthy tissues. These findings suggest two possible biomarkers for the use of OKE in optical biopsy. Both markers arise from alterations in the infected tissue's cellular structure, which changes the rate at which electronic and molecular processes occur.

Use of Optical Coherence Tomography in Dentistry.

Optical coherence tomography (OCT) is an optics-based imaging technique, which may be called an "optical biopsy." It can be used to acquire structural information about a tissue at a resolution comparable to histopathology. OCT is based on the principle of low-coherence interferometry where near-infrared (NIR) light is shown on a tissue sample and then cross-sectional images are obtained based on backscattered light and echo time delay. Two main types of OCT are characterized as time-domain OCT (TD-OCT) and Fourier-domain OCT (FD-OCT). The applications of OCT in dentistry can be broadly divided into two groups, i.e., assessment of pathologies and assessment of surfaces and interfaces. Lately, OCT has made its transition from experimental laboratories to mainstream clinical applications. Starting from the short-term training courses, clinicians working in specialities like oral pathology, oral medicine, and oral implantology may find it a useful tool for their practices. It is now clear that OCT will be considered a gold standard diagnostic tool for the detection and characterization of several conditions and lesions of the orofacial region. However, the next challenge will be to incorporate it into the undergraduate and postgraduate curriculum and train dental healthcare staff in the use of these devices.

Contact Endoscopy – Narrow Band Imaging (CE-NBI) data set for laryngeal lesion assessment

The endoscopic examination of subepithelial vascular patterns within the vocal fold is crucial for clinicians seeking to distinguish between benign lesions and laryngeal cancer. Among innovative techniques, Contact Endoscopy combined with Narrow Band Imaging (CE-NBI) offers real-time visualization of these vascular structures. Despite the advent of CE-NBI, concerns have arisen regarding the subjective interpretation of its images. As a result, several computer-based solutions have been developed to address this issue. This study introduces the CE-NBI data set, the first publicly accessible data set that features enhanced and magnified visualizations of subepithelial blood vessels within the vocal fold. This data set encompasses 11144 images from 210 adult patients with pathological vocal fold conditions, where CE-NBI images are annotated using three distinct label categories. The data set has proven invaluable for numerous clinical assessments geared toward diagnosing laryngeal cancer using Optical Biopsy. Furthermore, given its versatility for various image analysis tasks, we have devised and implemented diverse image classification scenarios using Machine Learning (ML) approaches to address critical clinical challenges in assessing laryngeal lesions.

Articular Cartilage-From Basic Science Structural Imaging to Non-Invasive Clinical Quantitative Molecular Functional Information for AI Classification and Prediction.

This review presents the changes that the imaging of articular cartilage has undergone throughout the last decades. It highlights that the expectation is no longer to image the structure and associated functions of articular cartilage but, instead, to devise methods for generating non-invasive, function-depicting images with quantitative information that is useful for detecting the early, pre-clinical stage of diseases such as primary or post-traumatic osteoarthritis (OA/PTOA). In this context, this review summarizes (a) the structure and function of articular cartilage as a molecular imaging target, (b) quantitative MRI for non-invasive assessment of articular cartilage composition, microstructure, and function with the current state of medical diagnostic imaging, (c), non-destructive imaging methods, (c) non-destructive quantitative articular cartilage live-imaging methods, (d) artificial intelligence (AI) classification of degeneration and prediction of OA progression, and (e) our contribution to this field, which is an AI-supported, non-destructive quantitative optical biopsy for early disease detection that operates on a digital tissue architectural fingerprint. Collectively, this review shows that articular cartilage imaging has undergone profound changes in the purpose and expectations for which cartilage imaging is used; the image is becoming an AI-usable biomarker with non-invasive quantitative functional information. This may aid in the development of translational diagnostic applications and preventive or early therapeutic interventions that are yet beyond our reach.

Magnetic Nanoparticles Decorated with Gold Nanoclusters–Applications in Cancer Theranostics

AbstractNanomedicine presents exciting new opportunities for the detection and treatment of cancer. Current cancer imaging methods and treatment approaches in clinics frequently fall short of entirely curing cancer and can have severe side effects. Theranostic nanoparticles, however, have the potential to revolutionize effective cancer treatment and early cancer detection. The objective of this study is to show how magnetic iron oxide nanoparticles and photoluminescent gold nanoclusters (MN‐AuNCs) may be combined effectively to produce bimodal imaging nanoparticles that possess magnetic and optical properties and can be used for both magnetic resonance imaging and optical biopsy. These findings demonstrate that MN‐AuNCs, when exposed to visible light, also have the capability to produce singlet oxygen, which is necessary for photodynamic therapy of cancer. In addition, it shows that they are non‐toxic, accumulate inside the cells, and cause cell death during exposure to visible light. The creation of these MN‐AuNCs offers a novel remedy for the current shortcomings in cancer diagnosis and treatment. Since they have both therapeutic and imaging capabilities, MN‐AuNCs have the potential to improve patient outcomes while lowering the risk of negative side effects.

Femtosecond Optical Kerr Gate in tissues.

The Optical Kerr Effect is investigated for the first time in biological tissues. This nonlinear effect was explored in both human brain and avian breast tissues using a time-resolved femtosecond pump-probe Optical Kerr Gate that looks for phase changes that arise in the probe from the pump induced Kerr refractive index change. The tissue samples produced a unique ultrafast (700-800 fs) doubled peaked temporal signal, which is indicative of interplay between the different ultrafast mechanisms (electronic plasma and molecular) that make up the Kerr index. The unique profile was replicated in theoretical simulations. The properties of the temporal profile varied between samples suggesting that it could be used as a new diagnostic. Understanding this behavior can help improve the scientific understanding of nonlinear spectral diagnostic techniques and potentially create a new Kerr-based optical biopsy method.

Research progress of optical coherence tomography in the airway

Optical coherence tomography (OCT) is a specialized optical imaging technique with a history of more than 30 years, known as'optical biopsy' because of its high resolution and high sensitivity. OCT has been used in the airway for more than 20 years, and researchers have explored and improved the imaging methods of OCT in the airway, focusing mainly on expanding the imaging site and enriching the imaging content. In terms of broadening the imaging site, it covers the airway from generation 0 to 9. In terms of enriching imaging content, additional assessment of airway wall blood vessels, airway smooth muscle, fibrous tissue, and airway compliance can be performed. It plays an important role in the study of various respiratory diseases. Therefore, this paper mainly summarized the exploration of the imaging site and content of airway OCT as follows.

Artificial Intelligence Optical Biopsy for Evaluating the Functional State of Wounds

IntroductionThe clinical characterization of the functional status of active wounds in terms of their driving cellular and molecular biology remains a considerable challenge that currently requires excision via a tissue biopsy. In this pilot study, we use convolutional Siamese neural network (SNN) architecture to predict the functional state of a wound using digital photographs of wounds in a canine model of volumetric muscle loss (VML). MethodsDigital images of VML injuries and tissue biopsies were obtained in a standardized fashion from an established canine model of VML. Gene expression profiles for each biopsy site were obtained using RNA sequencing. These profiles were converted to functional profiles by a manual review of validated gene ontology databases in which we determined a hierarchical representation of gene functions based on functional specificity. An SNN was trained to regress functional profile expression values, informed by an image segment showing the surface of a small tissue biopsy. ResultsThe SNN was able to predict the functional expression of a range of functions based with error ranging from ∼5% to ∼30%, with functions that are most closely associated with the early state of wound healing to be those best-predicted. ConclusionsThese initial results suggest promise for further research regarding this novel use of machine learning regression on medical images. The regression of functional profiles, as opposed to specific genes, both addresses the challenge of genetic redundancy and gives a deeper insight into the mechanistic configuration of a region of tissue in wounds.

Schistosomiasis enteropathy diagnosed by real-time endocytoscopy.

Fourth-generation endocytoscopy (EC) integrates a variable-focus lens and provides up to 520× continuous zoom-focus magnification. A single endoscope enables white-light imaging, narrow-band imaging, and cellular-level observation. The so-called virtual histology or optical biopsy has shown promising diagnostic ability in GI malignancies or premalignant lesions. Here, we report unexpected findings in the diagnosis of a rare benign disease. A 43-year-old man without a significant medical history underwent a colonoscopy because of abdominal distension. The colonoscopy showed patchy areas of multifocal white miliary spots in the hyperemic mucosa of the descending colon, with no features of polypoid tissue (A). Endocytoscopic ultramagnified images were obtained after staining with 1% methylene blue and 0.05% crystal violet. The microsurface structure of the gland was obviously destroyed, and a large number of seedlike oval structures were notable under endocytoscopy (CF-H290ECI endocytoscope; Olympus, Tokyo, Japan) (B). The on-site pathologist confirmed these structures to be schistosome eggs. Histologic examination of the targeted biopsy specimen also revealed numerous eggs of schistosome organisms (C, H&E, orig. mag. ×200). We hope that this first reported endocytoscopic observation of schistosomiasis enteropathy may enrich the understanding and application of this novel technique, and we believe that maximum diagnostic yield can be achieved under the guidance of an on-site pathologist, although a trained endoscopist can make the diagnosis in most cases.

Contrastive Adversarial Learning for Endomicroscopy Imaging Super-Resolution.

Endomicroscopy is an emerging imaging modality for real-time optical biopsy. One limitation of existing endomicroscopy based on coherent fibre bundles is that the image resolution is intrinsically limited by the number of fibres that can be practically integrated within the small imaging probe. To improve the image resolution, Super-Resolution (SR) techniques combined with image priors can enhance the clinical utility of endomicroscopy whereas existing SR algorithms suffer from the lack of explicit guidance from ground truth high-resolution (HR) images. In this paper, we propose an unsupervised SR pipeline to allow stable offline and kernel-generic learning. Our method takes advantage of both internal statistics and external cross-modality priors. To improve the joint learning process, we present a Sharpness-aware Contrastive Generative Adversarial Network (SCGAN) with two dedicated modules, a sharpness-aware generator and a contrastive-learning discriminator. In the generator, an auxiliary task of sharpness discrimination is formulated to facilitate internal learning by considering the rankings of training instances in various sharpness levels. In the discriminator, we design a contrastive-learning module to mitigate the ill-posed nature of SR tasks via constraints from both positive and negative images. Experiments on multiple datasets demonstrate that SCGAN reduces the performance gap between previous unsupervised approaches and the upper bounds defined in supervised settings by more than 50%, delivering a new state-of-the-art performance score for endomicroscopy super-resolution. Further application on a realistic Voronoi-based pCLE downsampling kernel proves that SCGAN attains PSNR of 35.851dB, improving 5.23dB compared with the traditional Delaunay interpolation.

Impact of computer-aided characterization for diagnosis of colorectal lesions, including sessile serrated lesions: Multireader, multicase study.

Computer-aided characterization (CADx) may be used to implement optical biopsy strategies into colonoscopy practice; however, its impact on endoscopic diagnosis remains unknown. We aimed to evaluate the additional diagnostic value of CADx when used by endoscopists for assessing colorectal polyps. This was a single-center, multicase, multireader, image-reading study using randomly extracted images of pathologically confirmed polyps resected between July 2021 and January 2022. Approved CADx that could predict two-tier classification (neoplastic or nonneoplastic) by analyzing narrow-band images of the polyps was used to obtain a CADx diagnosis. Participating endoscopists determined if the polyps were neoplastic or not and noted their confidence level using a computer-based, image-reading test. The test was conducted twice with a 4-week interval: the first test was conducted without CADx prediction and the second test with CADx prediction. Diagnostic performances for neoplasms were calculated using the pathological diagnosis as reference and performances with and without CADx prediction were compared. Five hundred polyps were randomly extracted from 385 patients and diagnosed by 14 endoscopists (including seven experts). The sensitivity for neoplasia was significantly improved by referring to CADx (89.4% vs. 95.6%). CADx also had incremental effects on the negative predictive value (69.3% vs. 84.3%), overall accuracy (87.2% vs. 91.8%), and high-confidence diagnosis rate (77.4% vs. 85.8%). However, there was no significant difference in specificity (80.1% vs. 78.9%). Computer-aided characterization has added diagnostic value for differentiating colorectal neoplasms and may improve the high-confidence diagnosis rate.

Polarimetric imaging-based cancer bladder tissue's detection: A comparative study of bulk and formalin-fixed paraffin-embedded samples

The polarimetry imaging technique as a promising technique for pathological diagnosis provides a handy tool for identifying and discriminating cancerous tissues. In this paper, the optical polarization properties of bulk bladder tissues without any further processing and Formalin-Fixed Paraffin-Embedded (FFPE) blocks of bladder tissues have been measured. The images of the Muller matrix for both normal and cancerous samples have been obtained and for quantitative analysis and to provide a more precise comparison, two methods have been applied; the Mueller matrix polar decomposition (MMPD), and the Mueller matrix transformation (MMT). The results have shown that some of the extracted parameters from these methods can be used to identify the microstructural differentiations between normal and cancerous tissues. The results revealed a good accord between the obtained optical parameters for bulk and FFPE bladder tissues. By measuring the polarimetric properties of the tissue right after resection, and also in the early stages of pathology (FFPE tissues), this method can be applied in vivo to perform an optical biopsy; Furthermore, this method has the potential to significantly shortens the duration of pathological diagnosis. The approach seems remarkable, simple, precise, and economical compared to the existing techniques for the detection of cancerous samples.