Probe-based Confocal Laser Endomicroscopy Research Articles

Distance Regression Enhanced with Temporal Information Fusion and Adversarial Training for Robot-Assisted Endomicroscopy.

Probe-based confocal laser endomicroscopy (pCLE) has a role in characterising tissue intraoperatively to guide tumour resection during surgery. To capture good quality pCLE data which is important for diagnosis, the probe-tissue contact needs to be maintained within a working range of micrometre scale. This can be achieved through micro-surgical robotic manipulation which requires the automatic estimation of the probe-tissue distance. In this paper, we propose a novel deep regression framework composed of the Deep Regression Generative Adversarial Network (DR-GAN) and a Sequence Attention (SA) module. The aim of DR-GAN is to train the network using an enhanced image-based supervision approach. It extents the standard generator by using a well-defined function for image generation, instead of a learnable decoder. Also, DR-GAN uses a novel learnable neural perceptual loss which combines for the first time spatial and frequency domain features. This effectively suppresses the adverse effects of noise in the pCLE data. To incorporate temporal information, we've designed the SA module which is a cross-attention module, enhanced with Radial Basis Function based encoding (SA-RBF). Furthermore, to train the regression framework, we designed a multi-step training mechanism. During inference, the trained network is used to generate data representations which are fused along time in the SA-RBF module to boost the regression stability. Our proposed network advances SOTA networks by addressing the challenge of excessive noise in the pCLE data and enhancing regression stability. It outperforms SOTA networks applied on the pCLE Regression dataset (PRD) in terms of accuracy, data quality and stability.

Resolution of Acute Lung Allograft Rejection Detected by Probe-based Confocal Laser Endomicroscopy.

Resolution of Acute Lung Allograft Rejection Detected by Probe-based Confocal Laser Endomicroscopy.

The value of assessing deep disease healing by probe-based confocal laser endomicroscopy and histology for long-term prognosis of ulcerative colitis.

The benefits of deep disease healing need evaluation by long-term clinical research in different populations. Confocal laser endomicroscopy (CLE) is a superior method for evaluating deep disease healing. This prospective study enrolled ulcerative colitis (UC) patients in clinical remission who underwent colonoscopy, CLE, and histological assessment. Patients were monitored for relapse by patient-reported outcomes and colonoscopy evaluation of mucosal healing. The ability of different methods of mucosal healing to predict long-term disease recurrence was assessed using Kaplan-Meier estimation and Cox proportional hazard regression. Forty-two patients in clinical remission were assessed by colonoscopy. Those with Mayo endoscopic subscores (MES)≤1 were enrolled. The 48-month recurrence rates in present healing group, assessed by CLE (colonic barrier assessment and ENHANCE index) and by histological examination (Geboes scale), were 20.0%, 26.7%, and 11.1%, respectively, and were significantly lower than absent healing group (P<0.05). Univariate Cox proportional risk regression analysis in absent of healing disease, determined by the ENHANCE index and Geboes scale, indicated an increased risk of recurrent events, with hazard ratios (HR) of 3.87 (95% CI: 1.18, 12.62) and 8.20 (95% CI: 1.06, 63.30), respectively. Multivariate Cox proportional hazard regression analysis adjusted for the extent of inflammation (E3 or not) showed a significant difference only for the ENHANCE index, with an HR of 3.53 (95% CI: 1.03, 12.10), P=0.045. Deep disease healing has a lower recurrence rate. The colonic barrier healing assessment, ENHANCE index, and histological Geboes scale have superior long-term prognostic value for UC patients.

Confocal Laser Endomicroscopy as a method for assessing endometriosis: A pilot study

ObjectivesTo validate probe-based Confocal Laser Endomicroscopy (pCLE) as a method in assessing endometriosis during conventional and robot-assisted laparoscopy. Study DesignPilot study, including five women in Hospital Moriah, São Paulo, Brazil. During laparoscopic procedures, pCLE was used to assess endometriosis lesions, complemented by subsequent histological evaluations. 214 optical biopsies were performed. These assessments contributed to the development of a comparative atlas, which was used by surgeons to respond to a questionnaire to identify specific cellular structures related to endometriosis in selected confocal images. ResultsThe patients had an average age of 35, exhibiting predominant symptoms like dysmenorrhea and dyspareunia. Despite varied familiarity with pCLE, surgeons demonstrated positive acceptance of the method, with 63.1% recommending its use for intraoperative diagnosis. The technique was particularly noted for its ability to provide real-time, detailed images aiding the identification of endometriosis and associated structures like adipocytes and vascularization, with average evaluation scores exceeding 8 of 10. ConclusionsThis study underscores pCLE’s potential as a transformative diagnostic tool in minimally invasive gynecological surgery. It highlights the feasibility and initial acceptance among surgeons, emphasizing the need for further improvements in device durability and cost-effectiveness. pCLE promises significant advancements in the diagnosis and management of endometriosis, suggesting a future direction for clinical applications and technological refinement.

Grading urothelial carcinoma with probe-based confocal laser endomicroscopy during flexible cystoscopy

PurposeUrothelial bladder cancer (UCB) care requires frequent follow-up cystoscopy and surgery. Confocal laser endomicroscopy (CLE) is a probe-based optical technique that can provide real-time microscopic evaluation with the potential for outpatient grading of UCB. This study aims to investigate the diagnostic accuracy and interobserver variability for the grading of UCB with CLE during flexible cystoscopy (fCLE).MethodsParticipants scheduled for transurethral resection of papillary bladder tumors were prospectively included for intra-operative fCLE. Exclusion criteria were flat lesions, fluorescein allergy or pregnancy. Two independent observers evaluated fCLE, classifying tumors as low- or high-grade urothelial carcinoma (LGUC/HGUC) or benign. Interobserver agreement was calculated with Cohens kappa (κ) and diagnostic accuracy with 2 × 2 tables. Histopathology was the reference test.ResultsHistopathology of 34 lesions revealed 14 HGUC, 14 LGUC and 6 benign tumors. Diagnostic yield for fCLE was 80–85% with a κ of 0.75. Respectively, sensitivity, specificity, NPV and PPV were: for benign tumors 0–20%, 96–100%, unmeasureable-50% and 87%, for LGUC 57–64%, 41–58%, 44–53% and 54–69% and for HGUC 38–57%, 56–68%, 38–57% and 56–68%, with an interobserver agreement of κ 0.61.ConclusionfCLE is currently insufficient to grade UCB.

A novel contact optimization algorithm for endomicroscopic surface scanning.

Probe-based confocal laser endomicroscopy (pCLE) offers real-time, cell-level imaging and holds promise for early cancer diagnosis. However, a large area surface scanning for image acquisition is needed to overcome the limitation of field-of-view. Obtaining high-quality images during scanning requires maintaining a stable contact distance between the tissue and probe. This work presents a novel contact optimization algorithm to acquire high-quality pCLE images. The contact optimization algorithm, based on swarm intelligence of whale optimization algorithm, is designed to optimize the probe position, according to the quality of the image acquired by probe. An accurate image quality assessment of total co-occurrence entropy is introduced to evaluate the pCLE image quality. The algorithm aims to maintain a consistent probe-tissue contact, resulting in high-quality images acquisition. Scanning experiments on sponge, ex vivo swine skin tissue and stomach tissue demonstrate the effectiveness of the contact optimization algorithm. Scanning results of the sponge with three different trajectories (spiral trajectory, circle trajectory, and raster trajectory) reveal high-quality mosaics with clear details in every part of the image and no blurred sections. The contact optimization algorithm successfully identifies the optimal distance between probe and tissue, improving the quality of pCLE images. Experimental results confirm the high potential of this method in endomicroscopic surface scanning.

Clustering-Guided Twin Contrastive Learning for Endomicroscopy Image Classification.

Learning better representations is essential in medical image analysis for computer-aided diagnosis. However, learning discriminative semantic features is a major challenge due to the lack of large-scale well-annotated datasets. Thus, how can we learn a well-structured categorizable embedding space in limited-scale and unlabeled datasets? In this paper, we proposed a novel clustering-guided twin-contrastive learning framework (CTCL) that learns the discriminative representations of probe-based confocal laser endomicroscopy (pCLE) images for gastrointestinal (GI) tumor classification. Compared with traditional contrastive learning, in which only two randomly augmented views of the same instance are considered, the proposed CTCL aligns more semantically related and class-consistent samples by clustering, which improved intra-class tightness and inter-class variability to produce more informative representations. Furthermore, based on the inherent properties of CLE (geometric invariance and intrinsic noise), we proposed to regard CLE images with any angle rotation and CLE images with different noises as the same instance, respectively, for increased variability and diversity of samples. By optimizing CTCL in an end-to-end expectation-maximization framework, comprehensive experimental results demonstrated that CTCL-based visual representations achieved competitive performance on each downstream task as well as more robustness and transferability compared with existing state-of-the-art SSL and supervised methods. Notably, CTCL achieved 75.60%/78.45% and 64.12%/77.37% top-1 accuracy on the linear evaluation protocol and few-shot classification downstream tasks, respectively, which outperformed the previous best results by 1.27%/1.63% and 0.5%/3%, respectively. The proposed method holds great potential to assist pathologists in achieving an automated, fast, and high-precision diagnosis of GI tumors and accurately determining different stages of tumor development based on CLE images.

XRelevanceCAM: towards explainable tissue characterization with improved localisation of pathological structures in probe-based confocal laser endomicroscopy

PurposeProbe-based confocal laser endomicroscopy (pCLE) enables intraoperative tissue characterization with improved resection rates of brain tumours. Although a plethora of deep learning models have been developed for automating tissue characterization, their lack of transparency is a concern. To tackle this issue, techniques like Class Activation Map (CAM) and its variations highlight image regions related to model decisions. However, they often fall short of providing human-interpretable visual explanations for surgical decision support, primarily due to the shattered gradient problem or insufficient theoretical underpinning.MethodsIn this paper, we introduce XRelevanceCAM, an explanation method rooted in a better backpropagation approach, incorporating sensitivity and conservation axioms. This enhanced method offers greater theoretical foundation and effectively mitigates the shattered gradient issue when compared to other CAM variants.ResultsQualitative and quantitative evaluations are based on ex vivo pCLE data of brain tumours. XRelevanceCAM effectively highlights clinically relevant areas that characterize the tissue type. Specifically, it yields a remarkable 56% improvement over our closest baseline, RelevanceCAM, in the network’s shallowest layer as measured by the mean Intersection over Union (mIoU) metric based on ground-truth annotations (from 18 to 28.07%). Furthermore, a 6% improvement in mIoU is observed when generating the final saliency map from all network layers.ConclusionWe introduce a new CAM variation, XRelevanceCAM, for precise identification of clinically important structures in pCLE data. This can aid introperative decision support in brain tumour resection surgery, as validated in our performance study.

High-Resolution Image Processing of Probe-Based Confocal Laser Endomicroscopy Based on Multistage Neural Networks and Cross-Channel Attention Module

Probe-based confocal laser endomicroscopy (pCLE) is a subcellular in vivo imaging technique that generates diagnostic images revealing malignant structural modifications in epithelial tissues. In the clinical diagnosis of probe confocal laser endomicroscopy (pCLE), the image background generally has the problems of dynamic blur or information loss, which is not conducive to achieving high-resolution and clear pCLE imaging. In recent years, deep learning technology has achieved remarkable results in image deblurring. For the task of recovering high-resolution pCLE images, the current methods still suffer from the following drawbacks: it is difficult to choose a strategy to make CNN converge at a deeper level and mainstream methods cannot handle the complex balance between spatial details and high-level feature information well when reconstructing clear images. In order to solve the problem, we propose a new cross-channel attention, multistage, high-resolution pCLE image deblurring structure. This methodology improves the supervised attention mechanism, enhances the ability of feature extraction and fusion capabilities, and improves the quality of image deblurring by adding cross-channel attention module (CAM) into the multistage neural networks’ architecture. The experimental results show that the average peak signal-to-noise ratio (PSNR) of the proposed model on the dataset is as high as 29.643 dB, and the structural similarity (SSIM) reaches 0.855. This method is superior to the prior algorithms in the visualization of recovered images, and the edge and texture details of the restored pCLE images are clearer.

Machine Learning-Based Prediction of Responsiveness to Neoadjuvant Chemoradiotheapy in Locally Advanced Rectal Cancer Patients from Endomicroscopy.

The protocol for treating locally advanced rectal cancer consists of the application of chemoradiotherapy (neoCRT) followed by surgical intervention. One issue for clinical oncologists is predicting the efficacy of neoCRT in order to adjust the dosage and avoid treatment toxicity in cases when surgery should be conducted promptly. Biomarkers may be used for this purpose along with in vivo cell-level images of the colorectal mucosa obtained by probe-based confocal laser endomicroscopy (pCLE) during colonoscopy. The aim of this article is to report our experience with Motiro, a computational framework that we developed for machine learning (ML) based analysis of pCLE videos for predicting neoCRT response in locally advanced rectal cancer patients. pCLE videos were collected from 47 patients who were diagnosed with locally advanced rectal cancer (T3/T4, or N+). The patients received neoCRT. Response to treatment by all patients was assessed by endoscopy along with biopsy and magnetic resonance imaging (MRI). Thirty-seven patients were classified as non-responsive to neoCRT because they presented a visible macroscopic neoplastic lesion, as confirmed by pCLE examination. Ten remaining patients were considered responsive to neoCRT because they presented lesions as a scar or small ulcer with negative biopsy, at post-treatment follow-up. Motiro was used for batch mode analysis of pCLE videos. It automatically characterized the tumoral region and its surroundings. That enabled classifying a patient as responsive or non-responsive to neoCRT based on pre-neoCRT pCLE videos. Motiro classified patients as responsive or non-responsive to neoCRT with an accuracy of ~ 0.62 when using images of the tumor. When using images of regions surrounding the tumor, it reached an accuracy of ~ 0.70. Feature analysis showed that spatial heterogeneity in fluorescence distribution within regions surrounding the tumor was the main contributor to predicting response to neoCRT. We developed a computational framework to predict response to neoCRT by locally advanced rectal cancer patients based on pCLE images acquired pre-neoCRT. We demonstrate that the analysis of the mucosa of the region surrounding the tumor provides stronger predictive power.

Vaporization of perfluorocarbon attenuates sea-water-drowning-induced acute lung injury by deactivating the NLRP3 inflammasomes in canines.

Seawater-drowning-induced acute lung injury (SD-ALI) is a life-threatening disorder characterized by increased alveolar-capillary permeability, an excessive inflammatory response, and refractory hypoxemia. Perfluorocarbons (PFCs) are biocompatible compounds that are chemically and biologically inert and lack toxicity as oxygen carriers, which could reduce lung injury in vitro and in vivo. The aim of our study was to explore whether the vaporization of PFCs could reduce the severity of SD-ALI in canines and investigate the underlying mechanisms. Eighteen beagle dogs were randomly divided into three groups: the seawater drowning (SW), perfluorocarbon (PFC), and control groups. The dogs in the SW group were intratracheally administered seawater to establish the animal model. The dogs in the PFC group were treated with vaporized PFCs. Probe-based confocal laser endomicroscopy (pCLE) was performed at 3h. The blood gas, volume air index (VAI), pathological changes, and wet-to-dry (W/D) lung tissue ratios were assessed. The expression of heme oxygenase-1 (HO-1), nuclear respiratory factor-1 (NRF1), and NOD-like receptor family pyrin domain containing-3 (NLRP3) inflammasomes was determined by means of quantitative real-time polymerase chain reaction (qRT-PCR) and immunological histological chemistry. The SW group showed higher lung injury scores and W/D ratios, and lower VAI compared to the control group, and treatment with PFCs could reverse the change of lung injury score, W/D ratio and VAI. PFCs deactivated NLRP3 inflammasomes and reduced the release of caspase-1, interleukin-1β (IL-1β), and interleukin-18 (IL-18) by enhancing the expression of HO-1 and NRF1. Our results suggest that the vaporization of PFCs could attenuate SD-ALI by deactivating NLRP3 inflammasomes via the HO-1/NRF1 pathway.

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.

Probe-based confocal laser endomicroscopy for evaluating high-altitude pulmonary edema in canines

BackgroundReal-time assessment of high-altitude pulmonary edema (HAPE) remains a challenge. Probe-based confocal laser microscopy (pCLE) allows a real-time in vivo visualization of the alveoli. This study aimed to develop a new non-invasive method for analyzing microscopic images in a canine model of HAPE using pCLE. Materials and methodsThis was a prospective, controlled animal study in adult male beagle dogs randomized to control and HAPE groups. The HAPE group was exposed to a high altitude of 6000 m for 48 h. The blood gas levels, lung morphological changes, infectious factors, and lung wet-to-dry ratio were analyzed in different groups. The pCLE images were described based on the volume air index (VAI), which applies an integral over specific signal intensities. ResultsThe lung wet-to-dry weight ratio and injury scores in the HAPE group were significantly increased compared with those of the control group. The levels of infectious factors interleukin-1 beta, tumor necrosis factor-alpha, and interleukin-6 were significantly increased in the HAPE group compared with those in the control group. VAI was significantly decreased in the HAPE group. ConclusionpCLE is a potential adjudicative bronchoscopic imaging technique for assessing HAPE. VAI may be acquired from quantitative parameters in the analysis of images.

The Endoscopic Retrograde Cholangiopancreatography and Endoscopic Ultrasound Connection: Unity Is Strength, or the Endoscopic Ultrasonography Retrograde Cholangiopancreatography Concept.

Endoscopic ultrasound (EUS) and endoscopic retrograde cholangiopancreatography (ERCP) are both crucial for the endoscopic management of biliopancreatic diseases: the combination of their diagnostic and therapeutic potential is useful in many clinical scenarios, such as indeterminate biliary stenosis, biliary stones, chronic pancreatitis and biliary and pancreatic malignancies. This natural and evident convergence between EUS and ERCP, which by 2006 we were calling the "Endoscopic ultrasonography retrograde colangiopancreatography (EURCP) concept", has become a hot topic in the last years, together with the implementation of the therapeutic possibilities of EUS (from EUS-guided necrosectomy to gastro-entero anastomoses) and with the return of ERCP to its original diagnostic purpose thanks to ancillary techniques (extraductal ultrasound (EDUS), intraductal ultrasound (IDUS), cholangiopancreatoscopy with biopsies and probe-based confocal laser endomicroscopy (pCLE)). In this literary review, we retraced the recent history of EUS and ERCP, reported examples of the clinical applicability of the EURCP concept and explored the option of performing the two procedures in only one endoscopic session, with its positive implications for the patient, the endoscopist and the health care system. In the last few years, we also evaluated the possibility of combining EUS and ERCP into a single endoscopic instrument in a single step, but certain obstacles surrounding this approach remain.

Present and future of endoscopy precision for inflammatory bowel disease.

Several advanced imaging techniques are now available for endoscopists managing inflammatory bowel disease (IBD) patients. These tools, including dye-based and virtual chromoendoscopy, probe-based confocal laser endomicroscopy and endocytoscopy, are increasingly innovative applications in clinical practice. They allow for a more in-depth and refined evaluation of the mucosal and vascular bowel surface, getting closer to histology. They have demonstrated a remarkable ability in assessing intestinal inflammation, histologic remission, and predicting relapse and favorable long-term outcomes. In addition, the future application of molecular endoscopy to predict biological drug responses has yielded preliminary but encouraging results. Furthermore, these techniques are crucial in detecting and characterizing IBD-related dysplasia, assisting endoscopic mucosal resection and submucosal dissection towards a surgery-sparing approach. Artificial intelligence (AI) holds great potential in this promising landscape, as it can provide an objective and reproducible assessment of inflammation and dysplasia. Moreover, it can improve the prediction of outcomes and aid in subsequent therapeutic decision-making. This review aims to summarize the promising role of state-of-the-art advanced endoscopic techniques and related AI-enabled models for managing IBD, paving the way for precision medicine.

Probe-based confocal laser endomicroscopy in the diagnosis of diffuse cystic lung disease in Sjögren's syndrome.

Sjögren's syndrome is a systemic autoimmune disease characterized by lymphocytic infiltration of various organs with a wide frequency of pulmonary involvement. Diffuse cystic lung disease in Sjögren's syndrome is a rare condition and requires differential diagnosis with other cystic pathologies such as lymphangioleyomiomatosis or Langerhans cell histiocytosis. Probe-based confocal laser endomicroscopy (pCLE) is a method of in vivo investigation of airways and lung tissue at a microscopic level during bronchoscopy. We used this method in diffuse cystic lung disease caused by Sjögren's syndrome. The pCLE image showed a large number of fluorescent cells, presumably lymphocytes, in bronchioles, dilated alveolar spaces with fluid, and thin alveolar walls. We think that the presence of the bronchiolar cell pattern can be used to differentiate between the pulmonary manifestations of Sjögren's disease and other cystic lung diseases.

Probe-based confocal laser endomicroscopy for real-time evaluation of colorectal liver metastasis in resected surgical specimens

Probe-based confocal laser endomicroscopy (pCLE) enables real-time examination of tissue structure. This study investigated pCLE with or without fluorescein sodium for the intraoperative diagnosis of colorectal liver metastasis (CLM) and detection of surgical margins. Thirty-four specimens of CLM and adjacent noncancerous tissue were obtained from 21 patients and examined by pCLE between May 2017 and March 2018. Images were obtained both without and with fluorescein sodium applied to the cut surface and compared with hematoxylin and eosin-stained tissue. Fluorescence intensity (FI) was measured by luminance-analysis software. Without external fluorophores, pCLE visualized 91.2% of CLM tissues as an irregular structure with low autofluorescence and 90.5% of noncancerous liver tissues as a regular structure with high autofluorescence. The median FI was significantly lower in cancer than in benign tissue in patients without chemotherapy [70.4 (51.6–110) vs. 48.3 (39.0–59.4), p = 0.002] and with chemotherapy [67.9 (54.6–89.2) vs. 48.6 (28.8–82.1), p < 0.001]. The border was clearly visible; pCLE with fluorescein sodium clearly showed their morphologies. In summary, our study demonstrated real-time pCLE distinguished CLM and noncancerous tissue by differences in structure and FI regardless of prehepatectomy chemotherapy. Fluorescein spray facilitated clear visualization of differences in the morphology.

Next-Generation Endoscopy in Inflammatory Bowel Disease.

Endoscopic healing is recognized as a primary treatment goal in Inflammatory Bowel Disease (IBD). However, endoscopic remission may not reflect histological remission, which is crucial to achieving favorable long-term outcomes. The development of new advanced techniques has revolutionized the field of IBD assessment and management. These tools can accurately assess vascular and mucosal features, drawing endoscopy closer to histology. Moreover, they can enhance the detection and characterization of IBD-related dysplasia. Given the persistent challenge of interobserver variability, a more standardized approach to endoscopy is warranted, and the integration of artificial intelligence (AI) holds promise for addressing this limitation. Additionally, although molecular endoscopy is still in its infancy, it is a promising tool to forecast response to therapy. This review provides an overview of advanced endoscopic techniques, including dye-based and dye-less chromoendoscopy, and in vivo histological examinations with probe-based confocal laser endomicroscopy and endocytoscopy. The remarkable contribution of these tools to IBD management, especially when integrated with AI, is discussed. Specific attention is given to their role in improving disease assessment, detection, and characterization of IBD-associated lesions, and predicting disease-related outcomes.

Using Endoscopy in the Diagnosis of Pancreato-Biliary Cancers

Pancreatic cancer and cholangiocarcinoma are life threatening oncological conditions with poor prognosis and outcome. Pancreatic cystic lesions are considered precursors of pancreatic cancer as some of them have the potential to progress to malignancy. Therefore, accurate identification and classification of these lesions is important to prevent the development of invasive cancer. In the biliary tract, the accurate characterization of biliary strictures is essential for providing appropriate management and avoiding unnecessary surgery. Techniques have been developed to improve the diagnosis, risk stratification, and management of pancreato-biliary lesions. Endoscopic ultrasound (EUS) and associated techniques, such as elastography, contrasted-enhanced EUS, and EUS-guided needle confocal laser endomicroscopy, may improve diagnostic accuracy. In addition, intraductal techniques applied during endoscopic retrograde cholangiopancreatography (ERCP), such as new generation cholangioscopy and in vivo cellular evaluation through probe-based confocal laser endomicroscopy, can increase the diagnostic yield in characterizing indeterminate biliary strictures. Both EUS-guided and intraductal approaches can provide the possibility for tissue sampling with new tools, such as needles, biopsies forceps, and brushes. At the molecular level, novel biomarkers have been explored that provide new insights into diagnosis, risk stratification, and management of these lesions.

Advanced diagnostic endoscopy in the upper gastrointestinal tract: Review of the Japan Gastroenterological Endoscopy Society core sessions.

We held four upper gastrointestinal tract advanced diagnostic endoscopy sessions from the 89th to the 92nd Congress of the Japan Gastroenterological Endoscopy Society. The most common region addressed was the stomach in 25 presentations, followed by the esophagus in 23, duodenum in five, and other in one. Looking at techniques discussed, the most common image enhancement method discussed was narrowband imaging in 29 presentations, blue laser imaging, and linked color imaging (LCI) in 10 each, dual red imaging in three, and autofluorescence imaging in one. Furthermore, there were presentations of new techniques such as M-Chromo-LCI and acetic acid-indigo carmine mixture LCI. There were also six presentations regarding probe-based confocal laser endomicroscopy, and one of endocytoscopy techniques. We also saw presentations of images of gastric subepithelial tumors within the submucosa, 3D endoscopy, the development of computer-aided detection systems for early cancers, and fluorescent imaging.