Discordance Among Pathologists in the United States and Europe in Diagnosis of Low-Grade Dysplasia for Patients With Barrett's Esophagus

AGA Clinical Practice Guideline on Endoscopic Eradication Therapy of Barrett's Esophagus and Related Neoplasia

BACKGROUND & AIMS

Barrett's esophagus (BE) is the precursor to esophageal adenocarcinoma (EAC). Endoscopic eradication therapy (EET) can be effective in eradicating BE and related neoplasia and has greater risk of harms and resource use than surveillance endoscopy. This clinical practice guideline aims to inform clinicians and patients by providing evidence-based practice recommendations for the use of EET in BE and related neoplasia.

METHODS

The Grading of Recommendations Assessment, Development and Evaluation framework was used to assess evidence and make recommendations. The panel prioritized clinical questions and outcomes according to their importance for clinicians and patients, conducted an evidence review, and used the Evidence-to-Decision Framework to develop recommendations regarding the use of EET in patients with BE under the following scenarios: presence of (1) high-grade dysplasia, (2) low-grade dysplasia, (3) no dysplasia, and (4) choice of stepwise endoscopic mucosal resection (EMR) or focal EMR plus ablation, and (5) endoscopic submucosal dissection vs EMR. Clinical recommendations were based on the balance between desirable and undesirable effects, patient values, costs, and health equity considerations.

RESULTS

The panel agreed on 5 recommendations for the use of EET in BE and related neoplasia. Based on the available evidence, the panel made a strong recommendation in favor of EET in patients with BE high-grade dysplasia and conditional recommendation against EET in BE without dysplasia. The panel made a conditional recommendation in favor of EET in BE low-grade dysplasia; patients with BE low-grade dysplasia who place a higher value on the potential harms and lower value on the benefits (which are uncertain) regarding reduction of esophageal cancer mortality could reasonably select surveillance endoscopy. In patients with visible lesions, a conditional recommendation was made in favor of focal EMR plus ablation over stepwise EMR. In patients with visible neoplastic lesions undergoing resection, the use of either endoscopic mucosal resection or endoscopic submucosal dissection was suggested based on lesion characteristics.

CONCLUSIONS

This document provides a comprehensive outline of the indications for EET in the management of BE and related neoplasia. Guidance is also provided regarding the considerations surrounding implementation of EET. Providers should engage in shared decision making based on patient preferences. Limitations and gaps in the evidence are highlighted to guide future research opportunities.

The Role of Screening and Early Detection in Upper Gastrointestinal Cancers

Upper gastrointestinal cancers are among the leading causes of cancer deaths worldwide with exceptionally poor prognosis, which is largely attributable to frequently delayed diagnosis. Although effective screening is critical for early detection, the highly variable incidence of upper gastrointestinal cancers presents challenges, rendering universal screening programs suboptimal in most populations globally. Optimal strategies in regions of modest incidence, such as the United States, require a targeted approach, focused on high-risk individuals based on demographic, familial, and clinicopathologic risk factors. Assessment of underlying precancerous lesions has key implications for risk stratification and informing clinical decisions to improve patient outcomes.

The Evolving Role of Artificial Intelligence in Gastrointestinal Histopathology: An Update

Significant advances in artificial intelligence (AI) over the past decade potentially may lead to dramatic effects on clinical practice. Digitized histology represents an area ripe for AI implementation. We describe several current needs within the world of gastrointestinal histopathology, and outline, using currently studied models, how AI potentially can address them. We also highlight pitfalls as AI makes inroads into clinical practice.

Advancing Artificial Intelligence Integration Into the Pathology Workflow: Exploring Opportunities in Gastrointestinal Tract Biopsies

This review aims to present a comprehensive overview of the current landscape of artificial intelligence (AI) applications in the analysis of tubular gastrointestinal biopsies. These publications cover a spectrum of conditions, ranging from inflammatory ailments to malignancies. Moving beyond the conventional diagnosis based on hematoxylin and eosin-stained whole-slide images, the review explores additional implications of AI, including its involvement in interpreting immunohistochemical results, molecular subtyping, and the identification of cellular spatial biomarkers. Furthermore, the review examines how AI can contribute to enhancing the quality and control of diagnostic processes, introducing new workflow options, and addressing the limitations and caveats associated with current AI platforms in this context.

The Salivary Microbiome and Predicted Metabolite Production Are Associated with Barrett's Esophagus and High-Grade Dysplasia or Adenocarcinoma

BACKGROUND

Esophageal adenocarcinoma (EAC) is rising in incidence, and established risk factors do not explain this trend. Esophageal microbiome alterations have been associated with Barrett's esophagus (BE) and dysplasia and EAC. The oral microbiome is tightly linked to the esophageal microbiome; this study aimed to identify salivary microbiome-related factors associated with BE, dysplasia, and EAC.

METHODS

Clinical data and oral health history were collected from patients with and without BE. The salivary microbiome was characterized, assessing differential relative abundance of taxa by 16S rRNA gene sequencing and associations between microbiome composition and clinical features. Microbiome metabolic modeling was used to predict metabolite production.

RESULTS

A total of 244 patients (125 non-BE and 119 BE) were analyzed. Patients with high-grade dysplasia (HGD)/EAC had a significantly higher prevalence of tooth loss (P = 0.001). There were significant shifts with increased dysbiosis associated with HGD/EAC, independent of tooth loss, with the largest shifts within the genus Streptococcus. Modeling predicted significant shifts in the microbiome metabolic capacities, including increases in L-lactic acid and decreases in butyric acid and L-tryptophan production in HGD/EAC.

CONCLUSIONS

Marked dysbiosis in the salivary microbiome is associated with HGD and EAC, with notable increases within the genus Streptococcus and accompanying changes in predicted metabolite production. Further work is warranted to identify the biological significance of these alterations and to validate metabolic shifts.

IMPACT

There is an association between oral dysbiosis and HGD/EAC. Further work is needed to establish the diagnostic, predictive, and causal potential of this relationship.

OralEpitheliumDB: A Dataset for Oral Epithelial Dysplasia Image Segmentation and Classification

Early diagnosis of potentially malignant disorders, such as oral epithelial dysplasia, is the most reliable way to prevent oral cancer. Computational algorithms have been used as an auxiliary tool to aid specialists in this process. Usually, experiments are performed on private data, making it difficult to reproduce the results. There are several public datasets of histological images, but studies focused on oral dysplasia images use inaccessible datasets. This prevents the improvement of algorithms aimed at this lesion. This study introduces an annotated public dataset of oral epithelial dysplasia tissue images. The dataset includes 456 images acquired from 30 mouse tongues. The images were categorized among the lesion grades, with nuclear structures manually marked by a trained specialist and validated by a pathologist. Also, experiments were carried out in order to illustrate the potential of the proposed dataset in classification and segmentation processes commonly explored in the literature. Convolutional neural network (CNN) models for semantic and instance segmentation were employed on the images, which were pre-processed with stain normalization methods. Then, the segmented and non-segmented images were classified with CNN architectures and machine learning algorithms. The data obtained through these processes is available in the dataset. The segmentation stage showed the F1-score value of 0.83, obtained with the U-Net model using the ResNet-50 as a backbone. At the classification stage, the most expressive result was achieved with the Random Forest method, with an accuracy value of 94.22%. The results show that the segmentation contributed to the classification results, but studies are needed for the improvement of these stages of automated diagnosis. The original, gold standard, normalized, and segmented images are publicly available and may be used for the improvement of clinical applications of CAD methods on oral epithelial dysplasia tissue images.

Gastro-Esophageal Junction Precancerosis: Histological Diagnostic Approach and Pathogenetic Insights

Barrett's esophagus (BE) was initially defined in the 1950s as the visualization of gastric-like mucosa in the esophagus. Over time, the definition has evolved to include the identification of goblet cells, which confirm the presence of intestinal metaplasia within the esophagus. Chronic gastro-esophageal reflux disease (GERD) is a significant risk factor for adenocarcinoma of the esophagus, as intestinal metaplasia can develop due to GERD. The development of adenocarcinomas related to BE progresses in sequence from inflammation to metaplasia, dysplasia, and ultimately carcinoma. In the presence of GERD, the squamous epithelium changes to columnar epithelium, which initially lacks goblet cells, but later develops goblet cell metaplasia and eventually dysplasia. The accumulation of multiple genetic and epigenetic alterations leads to the development and progression of dysplasia. The diagnosis of BE requires the identification of intestinal metaplasia on histologic examination, which has thus become an essential tool both in the diagnosis and in the assessment of dysplasia's presence and degree. The histologic diagnosis of BE dysplasia can be challenging due to sampling error, pathologists' experience, interobserver variation, and difficulty in histologic interpretation: all these problems complicate patient management. The development and progression of Barrett's esophagus (BE) depend on various molecular events that involve changes in cell-cycle regulatory genes, apoptosis, cell signaling, and adhesion pathways. In advanced stages, there are widespread genomic abnormalities with losses and gains in chromosome function, and DNA instability. This review aims to provide an updated and comprehensible diagnostic approach to BE based on the most recent guidelines available in the literature, and an overview of the pathogenetic and molecular mechanisms of its development.

An Automated Tissue Systems Pathology Test Can Standardize the Management and Improve Health Outcomes for Patients With Barrett's Esophagus

INTRODUCTION

Low-grade dysplasia (LGD) in Barrett's esophagus (BE) is associated with an increased risk of progression to high-grade dysplasia or esophageal adenocarcinoma. However, because of substantial interobserver variability in the diagnosis of LGD, a patient's management plan and health outcome depend largely on which pathologist reviews their case. This study evaluated the ability of a tissue systems pathology test that objectively risk stratifies patients with BE (TissueCypher, TSP-9) to standardize management in a manner consistent with improved health outcomes for patients with BE.

METHODS

A total of 154 patients with BE with community-based LGD from the prospectively followed screening cohort of the SURF trial were studied. Management decisions were simulated 500 times with varying generalist (n = 16) and expert (n = 14) pathology reviewers to determine the most likely care plan with or without use of the TSP-9 test for guidance. The percentage of patients receiving appropriate management based on the known progression/nonprogression outcomes was calculated.

RESULTS

The percentage of patients with 100% of simulations resulting in appropriate management significantly increased from 9.1% for pathology alone, to 58.4% when TSP-9 results were used with pathology, and further increased to 77.3% of patients receiving appropriate management when only TSP-9 results were used. Use of the test results also significantly increased the consistency of management decisions for patients when their slides were reviewed by different pathologists ( P < 0.0001).

DISCUSSION

Management guided by the TSP-9 test can standardize care plans by increasing the early detection of progressors who can receive therapeutic interventions, while also increasing the percentage of nonprogressors who can avoid unnecessary therapy and be managed by surveillance alone.

A Tissue Systems Pathology Test Outperforms the Standard-of-Care Variables in Predicting Progression in Patients With Barrett's Esophagus

INTRODUCTION

Objective risk stratification is needed for patients with Barrett's esophagus (BE) to enable risk-aligned management to improve health outcomes. This study evaluated the predictive performance of a tissue systems pathology [TSP-9] test (TissueCypher) vs current clinicopathologic variables in a multicenter cohort of patients with BE.

METHODS

Data from 699 patients with BE from 5 published studies on the TSP-9 test were evaluated. Five hundred nine patients did not progress during surveillance, 40 were diagnosed with high-grade dysplasia/esophageal adenocarcinoma (HGD/EAC) within 12 months, and 150 progressed to HGD/EAC after 12 months. Age, sex, segment length, hiatal hernia, original and expert pathology review diagnoses, and TSP-9 risk classes were collected. The predictive performance of clinicopathologic variables and the TSP-9 test was compared, and the TSP-9 test was evaluated in clinically relevant patient subsets.

RESULTS

The sensitivity of the TSP-9 test in detecting progressors was 62.3% compared with 28.3% for expert-confirmed low-grade dysplasia (LGD), while the original diagnosis abstracted from medical records did not provide any significant risk stratification. The TSP-9 test identified 57% of progressors with nondysplastic Barrett's esophagus (NDBE) ( P < 0.0001). Patients with NDBE who scored TSP-9 high risk progressed at a similar rate (3.2%/yr) to patients with expert-confirmed LGD (3.7%/yr). The TSP-9 test provided significant risk stratification in clinically low-risk patients (NDBE, female, short-segment BE) and clinically high-risk patients (IND/LGD, male, long-segment BE) ( P < 0.0001 for comparison of high-risk classes vs low-risk classes).

DISCUSSION

The TSP-9 test predicts risk of progression to HGD/EAC independently of current clinicopathologic variables in patients with BE. The test provides objective risk stratification results that may guide management decisions to improve health outcomes for patients with BE.

Real-world implementation of non-endoscopic triage testing for Barrett's oesophagus during COVID-19

BACKGROUND

The Coronavirus pandemic (COVID-19) curtailed endoscopy services, adding to diagnostic backlogs. Building on trial evidence for a non-endoscopic oesophageal cell collection device coupled with biomarkers (Cytosponge), an implementation pilot was launched for patients on waiting lists for reflux and Barrett's oesophagus surveillance.

AIMS

(i) To review reflux referral patterns and Barrett's surveillance practices. (ii) To evaluate the range of Cytosponge findings and impact on endoscopy services.

DESIGN AND METHODS

Cytosponge data from centralized laboratory processing (trefoil factor 3 (TFF3) for intestinal metaplasia (IM), haematoxylin & eosin for cellular atypia and p53 for dysplasia) over a 2-year period were included.

RESULTS

A total of 10 577 procedures were performed in 61 hospitals in England and Scotland, of which 92.5% (N = 9784/10 577) were sufficient for analysis. In the reflux cohort (N = 4074 with gastro-oesophageal junction sampling), 14.7% had one or more positive biomarkers (TFF3: 13.6% (N = 550/4056), p53: 0.5% (21/3974), atypia: 1.5% (N = 63/4071)), requiring endoscopy. Among samples from individuals undergoing Barrett's surveillance (N = 5710 with sufficient gland groups), TFF3-positivity increased with segment length (odds ratio = 1.37 per cm (95% confidence interval: 1.33-1.41, P < 0.001)). Some surveillance referrals (21.5%, N = 1175/5471) had ≤1 cm segment length, of which 65.9% (707/1073) were TFF3 negative. Of all surveillance procedures, 8.3% had dysplastic biomarkers (4.0% (N = 225/5630) for p53 and 7.6% (N = 430/5694) for atypia), increasing to 11.8% (N = 420/3552) in TFF3+ cases with confirmed IM and 19.7% (N = 58/294) in ultra-long segments.

CONCLUSIONS

Cytosponge-biomarker tests enabled targeting of endoscopy services to higher-risk individuals, whereas those with TFF3 negative ultra-short segments could be reconsidered regarding their Barrett's oesophagus status and surveillance requirements. Long-term follow-up will be important in these cohorts.

Endoscopic features of low-grade dysplastic Barrett's

Background and study aims Barrett's esophagus (BE) with low-grade dysplasia (LGD) is considered usually endoscopically invisible and the endoscopic features are not well described. This study aimed to: 1) evaluate the frequency of visible BE-LGD; 2) compare rates of BE-LGD detection in the community versus a Barrett's referral unit (BRU); and 3) evaluate the endoscopic features of BE-LGD. Patients and methods This was a retrospective analysis of a prospectively observed cohort of 497 patients referred to a BRU with dysplastic BE between 2008 and 2022. BE-LGD was defined as confirmation of LGD by expert gastrointestinal pathologist(s). Endoscopy reports, images and histology reports were reviewed to evaluate the frequency of endoscopically identifiable BE-LGD and their endoscopic features. Results A total of 135 patients (27.2%) had confirmed BE-LGD, of whom 15 (11.1%) had visible LGD identified in the community. After BRU assessment, visible LGD was detected in 68 patients (50.4%). Three phenotypes were observed: (A) Non-visible LGD; (B) Elevated (Paris 0-IIa) lesions; and (C) Flat (Paris 0-IIb) lesions with abnormal mucosal and/or vascular patterns with clear demarcation from regular flat BE. The majority (64.7%) of visible LGD was flat lesions with abnormal mucosal and vascular patterns. Endoscopic detection of BE-LGD increased over time (38.7% (2009-2012) vs. 54.3% (2018-2022)). Conclusions In this cohort, 50.4% of true BE-LGD was endoscopically visible, with increased recognition endoscopically over time and a higher rate of visible LGD detected at a BRU when compared with the community. BRU assessment of BE-LGD remains crucial; however, improving endoscopy surveillance quality in the community is equally important.

The Salivary Microbiome and Predicted Metabolite Production are Associated with Progression from Barrett's Esophagus to Esophageal Adenocarcinoma

Esophageal adenocarcinoma (EAC) is rising in incidence and associated with poor survival, and established risk factors do not explain this trend. Microbiome alterations have been associated with progression from the precursor Barrett's esophagus (BE) to EAC, yet the oral microbiome, tightly linked to the esophageal microbiome and easier to sample, has not been extensively studied in this context. We aimed to assess the relationship between the salivary microbiome and neoplastic progression in BE to identify microbiome-related factors that may drive EAC development. We collected clinical data and oral health and hygiene history and characterized the salivary microbiome from 250 patients with and without BE, including 78 with advanced neoplasia (high grade dysplasia or early adenocarcinoma). We assessed differential relative abundance of taxa by 16S rRNA gene sequencing and associations between microbiome composition and clinical features and used microbiome metabolic modeling to predict metabolite production. We found significant shifts and increased dysbiosis associated with progression to advanced neoplasia, with these associations occurring independent of tooth loss, and the largest shifts were with the genus Streptococcus. Microbiome metabolic models predicted significant shifts in the metabolic capacities of the salivary microbiome in patients with advanced neoplasia, including increases in L-lactic acid and decreases in butyric acid and L-tryptophan production. Our results suggest both a mechanistic and predictive role for the oral microbiome in esophageal adenocarcinoma. Further work is warranted to identify the biological significance of these alterations, to validate metabolic shifts, and to determine whether they represent viable therapeutic targets for prevention of progression in BE.

Defining an abnormal p53 immunohistochemical stain in Barrett's oesophagus-related dysplasia: a single-positive crypt is a sensitive and specific marker of dysplasia

AIMS

p53 is an independent risk stratification marker in Barrett's oesophagus (BE), but no universally accepted definition exists for abnormal p53 staining. Herein, we assess p53 stains in two cohorts to: (1) define abnormal p53 staining in BE-related dysplasia (BERD) and (2) assess the specificity and sensitivity of this cut-point for the diagnosis of dysplasia.

METHODS

Cohort 1 (n = 313) included (1) dysplastic BE biopsies, (2) prior non-dysplastic BE (NDBE) biopsies from the same patients and (3) NDBE biopsies from patients who never progressed to dysplasia. Cohort 2 (n = 191) consisted of BE biopsies in which p53 staining aided in diagnosing dysplasia. Automated p53 staining quantification was performed on cohort 1. A semiquantitative p53 analysis, performed on both cohorts, included: (1) number of strongly positive glands, (2) strong glandular surface staining, (3) percentage of strongly positive glands and (4) null phenotype.

RESULTS

NDBE biopsies from cohort 1 patients who progressed to dysplasia were more likely to show p53 positivity than non-progressors (16.9 versus 0.6%) (P = 0.0001). The optimal quantitative cut-point for distinguishing dysplastic from never-dysplasia biopsies was 10 strongly positive cells. By semiquantitative analysis, a single strongly p53-positive gland distinguished dysplastic from never-dysplasia BE (sensitivity 98.6%, specificity 99.4%). The semiquantitative and quantitative analyses correlated (P = 0.0001). In cohort 2, the sensitivity and specificity for BERD of ≥ 1 strongly positive p53 gland were 86.0 and 88.6%.

CONCLUSIONS

A single strongly positive p53 gland is sensitive and specific for BERD. Automated p53 analysis may reduce subjectivity associated with the diagnosis of BERD.

Histological evaluation of PAXgene tissue fixation in Barrett’s esophagus and esophageal adenocarcinoma diagnostics

The dysplasia grading of Barrett’s esophagus (BE), based on the histomorphological assessment of formalin-fixed, paraffin-embedded (FFPE) tissue, suffers from high interobserver variability leading to an unsatisfactory prediction of cancer risk. Thus, pre-analytic preservation of biological molecules, which could improve risk prediction in BE enabling molecular and genetic analysis, is needed. We aimed to evaluate such a molecular pre-analytic fixation tool, PAXgene-fixed paraffin-embedded (PFPE) biopsies, and their suitability for histomorphological BE diagnostics in comparison to FFPE. In a ring trial, 9 GI pathologists evaluated 116 digital BE slides of non-dysplastic BE (NDBE), low-grade dysplasia (LGD), high-grade dysplasia (HGD), and esophageal adenocarcinomas (EAC) using virtual microscopy. Overall quality, cytological and histomorphological parameters, dysplasia criteria, and diagnosis were analyzed. PFPE showed better preservation of nuclear details as chromatin and nucleoli, whereas overall quality and histomorphologic parameters as visibility of basal lamina, goblet cells, and presence of artifacts were scored as equal to FFPE. The interobserver reproducibility with regard to the diagnosis was best for NDBE and EAC (κF = 0.72–0.75) and poor for LGD and HGD (κF = 0.13–0.3) in both. In conclusion, our data suggest that PFPE allows equally confident histomorphological diagnosis of BE and EAC, introducing a novel tool for molecular analysis and parallel histomorphological evaluation.

Development of a deep learning model for the histologic diagnosis of dysplasia in Barrett's esophagus

BACKGROUND AND AIMS

The risk of progression in Barrett's esophagus (BE) increases with development of dysplasia. There is a critical need to improve the diagnosis of BE dysplasia, given substantial interobserver disagreement among expert pathologists and overdiagnosis of dysplasia by community pathologists. We developed a deep learning model to predict dysplasia grade on whole-slide imaging.

METHODS

We digitized nondysplastic BE (NDBE), low-grade dysplasia (LGD), and high-grade dysplasia (HGD) histology slides. Two expert pathologists confirmed all histology and digitally annotated areas of dysplasia. Training, validation, and test sets were created (by a random 70/20/10 split). We used an ensemble approach combining a "you only look once" model to identify regions of interest and histology class (NDBE, LGD, or HGD) followed by a ResNet101 model pretrained on ImageNet applied to the regions of interest. Diagnostic performance was determined for the whole slide.

RESULTS

We included slides from 542 patients (164 NDBE, 226 LGD, and 152 HGD) yielding 8596 bounding boxes in the training set, 1946 bounding boxes in the validation set, and 840 boxes in the test set. When the ensemble model was used, sensitivity and specificity for LGD was 81.3% and 100%, respectively, and >90% for NDBE and HGD. The overall positive predictive value and sensitivity metric (calculated as F1 score) was .91 for NDBE, .90 for LGD, and 1.0 for HGD.

CONCLUSIONS

We successfully trained and validated a deep learning model to accurately identify dysplasia on whole-slide images. This model can potentially help improve the histologic diagnosis of BE dysplasia and the appropriate application of endoscopic therapy.

Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations

The digitalization of clinical workflows and the increasing performance of deep learning algorithms are paving the way towards new methods for tackling cancer diagnosis. However, the availability of medical specialists to annotate digitized images and free-text diagnostic reports does not scale with the need for large datasets required to train robust computer-aided diagnosis methods that can target the high variability of clinical cases and data produced. This work proposes and evaluates an approach to eliminate the need for manual annotations to train computer-aided diagnosis tools in digital pathology. The approach includes two components, to automatically extract semantically meaningful concepts from diagnostic reports and use them as weak labels to train convolutional neural networks (CNNs) for histopathology diagnosis. The approach is trained (through 10-fold cross-validation) on 3’769 clinical images and reports, provided by two hospitals and tested on over 11’000 images from private and publicly available datasets. The CNN, trained with automatically generated labels, is compared with the same architecture trained with manual labels. Results show that combining text analysis and end-to-end deep neural networks allows building computer-aided diagnosis tools that reach solid performance (micro-accuracy = 0.908 at image-level) based only on existing clinical data without the need for manual annotations.

AGA Clinical Practice Update on New Technology and Innovation for Surveillance and Screening in Barrett's Esophagus: Expert Review

DESCRIPTION

The purpose of this best practice advice (BPA) article from the Clinical Practice Update Committee of the American Gastroenterological Association is to provide an update on advances and innovation regarding the screening and surveillance of Barrett's esophagus.

METHODS

The BPA statements presented here were developed from expert review of existing literature combined with discussion and expert opinion to provide practical advice. Formal rating of the quality of evidence or strength of BPAs was not the intent of this clinical practice update. This expert review was commissioned and approved by the AGA Institute Clinical Practice Updates Committee (CPUC) and the AGA Governing Board to provide timely guidance on a topic of high clinical importance to the AGA membership, and underwent internal peer review by the CPUC and external peer review through standard procedures of Clinical Gastroenterology and Hepatology. BEST PRACTICE ADVICE 1: Screening with standard upper endoscopy may be considered in individuals with at least 3 established risk factors for Barrett's esophagus (BE) and esophageal adenocarcinoma, including individuals who are male, non-Hispanic white, age >50 years, have a history of smoking, chronic gastroesophageal reflux disease, obesity, or a family history of BE or esophageal adenocarcinoma. BEST PRACTICE ADVICE 2: Nonendoscopic cell-collection devices may be considered as an option to screen for BE. BEST PRACTICE ADVICE 3: Screening and surveillance endoscopic examination should be performed using high-definition white light endoscopy and virtual chromoendoscopy, with endoscopists spending adequate time inspecting the Barrett's segment. BEST PRACTICE ADVICE 4: Screening and surveillance exams should define the extent of BE using a standardized grading system documenting the circumferential and maximal extent of the columnar lined esophagus (Prague classification) with a clear description of landmarks and the location and characteristics of visible lesions (nodularity, ulceration), when present. BEST PRACTICE ADVICE 5: Advanced imaging technologies such as endomicroscopy may be used as adjunctive techniques to identify dysplasia. BEST PRACTICE ADVICE 6: Sampling during screening and surveillance exams should be performed using the Seattle biopsy protocol (4-quadrant biopsies every 1-2 cm and target biopsies from any visible lesion). BEST PRACTICE ADVICE 7: Wide-area transepithelial sampling may be used as an adjunctive technique to sample the suspected or established Barrett's segment (in addition to the Seattle biopsy protocol). BEST PRACTICE ADVICE 8: Patients with erosive esophagitis should be biopsied when concern of dysplasia or malignancy exists. A repeat endoscopy should be performed after 8 weeks of twice a day proton pump inhibitor therapy. BEST PRACTICE ADVICE 9: Tissue systems pathology-based prediction assay may be utilized for risk stratification of patients with nondysplastic BE. BEST PRACTICE ADVICE 10: Risk stratification models may be utilized to selectively identify individuals at risk for Barrett's associated neoplasia. BEST PRACTICE ADVICE 11: Given the significant interobserver variability among pathologists, the diagnosis of BE-related neoplasia should be confirmed by an expert pathology review. BEST PRACTICE ADVICE 12: Patients with BE-related neoplasia should be referred to endoscopists with expertise in advanced imaging, resection, and ablation. BEST PRACTICE ADVICE 13: All patients with BE should be placed on at least daily proton pump inhibitor therapy. BEST PRACTICE ADVICE 14: Patients with nondysplastic BE should undergo surveillance endoscopy in 3 to 5 years. BEST PRACTICE ADVICE 15: In patients undergoing surveillance after endoscopic eradication therapy, random biopsies should be taken of the esophagogastric junction, gastric cardia, and the distal 2 cm of the neosquamous epithelium as well as from all visible lesions, independent of the length of the original BE segment.

Management of Dysplastic Barrett's Esophagus and Early Esophageal Adenocarcinoma

While patients with Barrett's esophagus without dysplasia may benefit from endoscopic surveillance, those with low-grade dysplasia may be managed with either endoscopic surveillance or endoscopic eradication. Patients with Barrett's esophagus with high-grade dysplasia and/or intramucosal adenocarcinoma will generally require endoscopic eradication therapy. The management of Barrett's esophagus with dysplasia and early esophageal adenocarcinoma is predominantly endoscopic, with multiple effective methods available for the resection of raised neoplasia and ablation of flat neoplasia. High-dose proton-pump inhibitor therapy is advised during the treatment of Barrett's esophagus with dysplasia and early esophageal adenocarcinoma. After the endoscopic eradication of Barrett's esophagus and associated neoplasia, surveillance is required for the diagnosis and retreatment of recurrence or progression.

Endoscopic Management of Esophageal Cancer

Advances in technology and improved understanding of the pathobiology of esophageal cancer have allowed endoscopy to serve a growing role in the management of this disease. Precursor lesions can be detected using enhanced diagnostic modalities and eradicated with ablation therapy. Furthermore, evolution in endoscopic resection has provided larger specimens for improved diagnostic accuracy and offer potential for cure of early esophageal cancer. In patients with advanced esophageal cancer, endoluminal therapy can improve symptom burden and provide therapeutic options for complications such as leaks, perforations, and fistulas. The purpose of this review article is to highlight the role of endoscopy in the diagnosis, treatment, and palliation of esophageal cancer.

Diagnostic Accuracy of Artificial Intelligence (AI) to Detect Early Neoplasia in Barrett's Esophagus: A Non-comparative Systematic Review and Meta-Analysis

Background and Aims

Artificial Intelligence (AI) is rapidly evolving in gastrointestinal (GI) endoscopy. We undertook a systematic review and meta-analysis to assess the performance of AI at detecting early Barrett's neoplasia.

Methods

We searched Medline, EMBASE and Cochrane Central Register of controlled trials database from inception to the 28th Jan 2022 to identify studies on the detection of early Barrett's neoplasia using AI. Study quality was assessed using Quality Assessment of Diagnostic Accuracy Studies – 2 (QUADAS-2). A random-effects model was used to calculate pooled sensitivity, specificity, and diagnostics odds ratio (DOR). Forest plots and a summary of the receiving operating characteristics (SROC) curves displayed the outcomes. Heterogeneity was determined by I², Tau² statistics and p-value. The funnel plots and Deek's test were used to assess publication bias.

Results

Twelve studies comprising of 1,361 patients (utilizing 532,328 images on which the various AI models were trained) were used. The SROC was 0.94 (95% CI: 0.92–0.96). Pooled sensitivity, specificity and diagnostic odds ratio were 90.3% (95% CI: 87.1–92.7%), 84.4% (95% CI: 80.2–87.9%) and 48.1 (95% CI: 28.4–81.5), respectively. Subgroup analysis of AI models trained only on white light endoscopy was similar with pooled sensitivity and specificity of 91.2% (95% CI: 85.7–94.7%) and 85.1% (95% CI: 81.6%−88.1%), respectively.

Conclusions

AI is highly accurate at detecting early Barrett's neoplasia and validated for patients with at least high-grade dysplasia and above. Further well-designed prospective randomized controlled studies of all histopathological subtypes of early Barrett's neoplasia are needed to confirm these findings further.

Prediction of neoplastic progression in Barrett's esophagus using nanoscale nuclear architecture mapping: a pilot study

BACKGROUND AND AIMS

Nanoscale nuclear architecture mapping (nanoNAM), an optical coherence tomography-derived approach, is capable of detecting with nanoscale sensitivity structural alterations in the chromatin of epithelial cell nuclei at risk for malignant transformation. Because these alterations predate the development of dysplasia, we aimed to use nanoNAM to identify patients with Barrett's esophagus (BE) who might progress to high-grade dysplasia (HGD) or esophageal adenocarcinoma (EAC).

METHODS

This is a nested case-control study of 46 BE patients, of which 21 progressed to HGD/EAC over 3.7 ± 2.37 years (cases/progressors) and 25 patients who did not progress over 6.3 ± 3.1 years (control subjects/nonprogressors). The archived formalin-fixed paraffin-embedded tissue blocks collected as part of standard clinical care at the index endoscopy were used. nanoNAM imaging was performed on a 5-μm formalin-fixed paraffin-embedded section, and each nucleus was mapped to a 3-dimensional (3D) depth-resolved optical path difference (drOPD) nuclear representation, quantifying nanoscale-sensitive alterations in the 3D nuclear architecture of the cell. Using 3D-drOPD representation of each nucleus, we computed 12 patient-level nanoNAM features summarizing the alterations in intrinsic nuclear architecture. A risk prediction model was built incorporating nanoNAM features and clinical features.

RESULTS

A statistically significant differential shift was observed in the drOPD cumulative distributions between progressors and nonprogressors. Of the 12 nanoNAM features, 6 (mean-maximum, mean-mean, mean-median, entropy-median, entropy-entropy, entropy-skewness) showed a statistically significant difference between cases and control subjects. NanoNAM features based prediction model identified progression in independent validation sets, with an area under the receiver operating characteristic curve of 80.8% ± .35% (mean ± standard error), with an increase to 82.54% ± .46% when combined with length of the BE segment.

CONCLUSIONS

NanoNAM can serve as an adjunct to histopathologic evaluation of BE patients and aid in risk stratification.

External validation of a model determining risk of neoplastic progression of Barrett's esophagus in a cohort of U.S. veterans

BACKGROUND AND AIMS

Risk of esophageal adenocarcinoma (EAC) in those with Barrett's esophagus (BE) is 11-fold greater than the general population. It remains unclear which BE patients are at highest risk of progression to EAC. We aimed to validate a predictive model risk-stratifying BE patients.

METHODS

We conducted a retrospective cohort study at the Houston Veteran Affairs Medical Center of consecutive patients with a new diagnosis of BE from November 1990 to January 2019. Study follow-up was through February 2020. Patients were excluded if they had no follow-up EGD with esophageal biopsy sampling after the initial BE-diagnosing EGD or evidence of high-grade dysplasia (HGD) or EAC on initial EGD. We performed an external validation study of a risk model containing sex, smoking, BE length, and low-grade dysplasia (LGD) status and assessed discriminatory ability using the area under the receiver operating characteristic curve (AUROC).

RESULTS

Among 608 BE patients, 24 progressed to HGD/EAC. The points-based model discriminated well with an AUROC of .72 (95% confidence interval [CI], .63-.82). When categorized into low-, intermediate-, and high-risk groups according to published cutoffs, the AUROC was poor at .57. Restructured into low-risk versus high-risk groups, the AUROC was .72 (95% CI, .64-.80). Excluding baseline LGD did not reduce discriminatory ability (AUROC, .73; 95% CI, .64-.82).

CONCLUSIONS

This external validation provides further evidence that the model including sex, LGD status, smoking status, and BE length may help to risk stratify BE patients. A simplified version excluding LGD status and/or reducing the number of risk groups has increased utility in clinical practice without loss of discriminatory ability.

Infiltration pattern predicts metastasis and progression better than the T-stage and grade in pancreatic neuroendocrine tumors: a proposal for a novel infiltration-based morphologic grading

The advancing edge profile is a powerful determinant of tumor behavior in many organs. In this study, a grading system assessing the tumor-host interface was developed and tested in 181 pancreatic neuroendocrine tumors (PanNETs), 63 of which were <=2 cm. Three tumor slides representative of the spectrum (least, medium, and most) of invasiveness at the advancing edge of the tumor were selected, and then each slide was scored as follows. Well-demarcated/encapsulated, 1 point; Mildly irregular borders and/or minimal infiltration into adjacent tissue, 2 points; Infiltrative edges with several clusters beyond the main tumor but still relatively close, and/or satellite demarcated nodules, 3 points; No demarcation, several cellular clusters away from the tumor, 4 points; Exuberantly infiltrative pattern, scirrhous growth, dissecting the normal parenchymal elements, 5 points. The sum of the rankings on the three slides was obtained. Cases with scores of 3-6 were defined as "non/minimally infiltrative" (NI; n = 77), 7-9 as "moderately infiltrative" (MI; n = 68), and 10-15 as "highly infiltrative" (HI; n = 36). In addition to showing a statistically significant correlation with all the established signs of aggressiveness (grade, size, T-stage), this grading system was found to be the most significant predictor of adverse outcomes (metastasis, progression, and death) on multivariate analysis, more strongly than T-stage, while Ki-67 index did not stand the multivariate test. As importantly, cases <=2 cm were also stratified by this grading system rendering it applicable also to this group that is currently placed in "watchful waiting" protocols. In conclusion, the proposed grading system has a strong, independent prognostic value and therefore should be considered for integration into routine pathology practice after being evaluated in validation studies with larger series.

Endoscopic Diagnosis and Management of Barrett's Esophagus with Low-Grade Dysplasia

Barrett’s Esophagus is a common condition associated with chronic gastroesophageal reflux disease. It is well known that it has an association with a higher incidence of esophageal adenocarcinoma, but this neoplastic transformation is first preceded by the onset of low and high-grade dysplasia. The evaluation of low grade dysplastic esophageal mucosa is still controversial; although endoscopic surveillance is preferred, several minimally invasive endoscopic therapeutic approaches are available. Endoscopic mucosal resection and radiofrequency ablation are the most used endoscopic treatments for the eradication of low-grade dysplasia, respectively, for nodular and flat dysplasia. Novel endoscopic treatments are cryotherapy ablation and argon plasma coagulation, that have good rates of eradication with less complications and post-procedural pain.

Diagnosis and Management of Barrett's Esophagus: An Updated ACG Guideline

Barrett's esophagus (BE) is a common condition associated with chronic gastroesophageal reflux disease. BE is the only known precursor to esophageal adenocarcinoma, a highly lethal cancer with an increasing incidence over the last 5 decades. These revised guidelines implement Grading of Recommendations, Assessment, Development, and Evaluation methodology to propose recommendations for the definition and diagnosis of BE, screening for BE and esophageal adenocarcinoma, surveillance of patients with known BE, and the medical and endoscopic treatment of BE and its associated early neoplasia. Important changes since the previous iteration of this guideline include a broadening of acceptable screening modalities for BE to include nonendoscopic methods, liberalized intervals for surveillance of short-segment BE, and volume criteria for endoscopic therapy centers for BE. We recommend endoscopic eradication therapy for patients with BE and high-grade dysplasia and those with BE and low-grade dysplasia. We propose structured surveillance intervals for patients with dysplastic BE after successful ablation based on the baseline degree of dysplasia. We could not make recommendations regarding chemoprevention or use of biomarkers in routine practice due to insufficient data.

Comprehensive RNA dataset of tissue and plasma from patients with esophageal cancer or precursor lesions

In the past decades, the incidence of esophageal adenocarcinoma has increased dramatically in Western populations. Better understanding of disease etiology along with the identification of novel prognostic and predictive biomarkers are urgently needed to improve the dismal survival probabilities. Here, we performed comprehensive RNA (coding and non-coding) profiling in various samples from 17 patients diagnosed with esophageal adenocarcinoma, high-grade dysplastic or non-dysplastic Barrett’s esophagus. Per patient, a blood plasma sample, and a healthy and disease esophageal tissue sample were included. In total, this comprehensive dataset consists of 102 sequenced libraries from 51 samples. Based on this data, 119 expression profiles are available for three biotypes, including miRNA (51), mRNA (51) and circRNA (17). This unique resource allows for discovery of novel biomarkers and disease mechanisms, comparison of tissue and liquid biopsy profiles, integration of coding and non-coding RNA patterns, and can serve as a validation dataset in other RNA landscaping studies. Moreover, structural RNA differences can be identified in this dataset, including protein coding mutations, fusion genes, and circular RNAs.

Use of a Cytosponge biomarker panel to prioritise endoscopic Barrett's oesophagus surveillance: a cross-sectional study followed by a real-world prospective pilot

BACKGROUND

Endoscopic surveillance is recommended for patients with Barrett's oesophagus because, although the progression risk is low, endoscopic intervention is highly effective for high-grade dysplasia and cancer. However, repeated endoscopy has associated harms and access has been limited during the COVID-19 pandemic. We aimed to evaluate the role of a non-endoscopic device (Cytosponge) coupled with laboratory biomarkers and clinical factors to prioritise endoscopy for Barrett's oesophagus.

METHODS

We first conducted a retrospective, multicentre, cross-sectional study in patients older than 18 years who were having endoscopic surveillance for Barrett's oesophagus (with intestinal metaplasia confirmed by TFF3 and a minimum Barrett's segment length of 1 cm [circumferential or tongues by the Prague C and M criteria]). All patients had received the Cytosponge and confirmatory endoscopy during the BEST2 (ISRCTN12730505) and BEST3 (ISRCTN68382401) clinical trials, from July 7, 2011, to April 1, 2019 (UK Clinical Research Network Study Portfolio 9461). Participants were divided into training (n=557) and validation (n=334) cohorts to identify optimal risk groups. The biomarkers evaluated were overexpression of p53, cellular atypia, and 17 clinical demographic variables. Endoscopic biopsy diagnosis of high-grade dysplasia or cancer was the primary endpoint. Clinical feasibility of a decision tree for Cytosponge triage was evaluated in a real-world prospective cohort from Aug 27, 2020 (DELTA; ISRCTN91655550; n=223), in response to COVID-19 and the need to provide an alternative to endoscopic surveillance.

FINDINGS

The prevalence of high-grade dysplasia or cancer determined by the current gold standard of endoscopic biopsy was 17% (92 of 557 patients) in the training cohort and 10% (35 of 344) in the validation cohort. From the new biomarker analysis, three risk groups were identified: high risk, defined as atypia or p53 overexpression or both on Cytosponge; moderate risk, defined by the presence of a clinical risk factor (age, sex, and segment length); and low risk, defined as Cytosponge-negative and no clinical risk factors. The risk of high-grade dysplasia or intramucosal cancer in the high-risk group was 52% (68 of 132 patients) in the training cohort and 41% (31 of 75) in the validation cohort, compared with 2% (five of 210) and 1% (two of 185) in the low-risk group, respectively. In the real-world setting, Cytosponge results prospectively identified 39 (17%) of 223 patients as high risk (atypia or p53 overexpression, or both) requiring endoscopy, among whom the positive predictive value was 31% (12 of 39 patients) for high-grade dysplasia or intramucosal cancer and 44% (17 of 39) for any grade of dysplasia.

INTERPRETATION

Cytosponge atypia, p53 overexpression, and clinical risk factors (age, sex, and segment length) could be used to prioritise patients for endoscopy. Further investigation could validate their use in clinical practice and lead to a substantial reduction in endoscopy procedures compared with current surveillance pathways.

FUNDING

Medical Research Council, Cancer Research UK, Innovate UK.

Evolutionary dynamics in Barrett oesophagus: implications for surveillance, risk stratification and therapy

Cancer development is a dynamic evolutionary process characterized by marked intratumoural heterogeneity at the genetic, epigenetic and phenotypic levels. Barrett oesophagus, the pre-malignant condition to oesophageal adenocarcinoma (EAC), is an exemplary system to longitudinally study the evolution of malignancy. Evidence has emerged of Barrett oesophagus lesions pre-programmed for progression to EAC many years before clinical detection, indicating a considerable window for therapeutic intervention. In this Review, we explore the mechanisms underlying clonal expansion and contraction that establish the Barrett oesophagus clonal mosaicism over time and space and discuss intrinsic genotypic and extrinsic environmental drivers that direct the evolutionary trajectory of Barrett oesophagus towards a malignant phenotype. We propose that understanding and exploiting the evolutionary dynamics of Barrett oesophagus will identify novel therapeutic targets, improve prognostic tools and offer the opportunity for personalized surveillance programmes geared to prevent progression to EAC.

Utility of ancillary studies in the diagnosis and risk assessment of Barrett's esophagus and dysplasia

Barrett's esophagus (BE) is a major risk factor for the development of esophageal adenocarcinoma (EAC). BE patients undergo periodic endoscopic surveillance with biopsies to detect dysplasia and EAC, but this strategy is imperfect owing to sampling error and inconsistencies in the diagnosis and grading of dysplasia, which may result in an inaccurate diagnosis or risk assessment for progression to EAC. The desire for more accurate diagnosis and better risk stratification has prompted the investigation and development of potential biomarkers that might assist pathologists and clinicians in the management of BE patients, allowing more aggressive endoscopic surveillance and treatment options to be targeted to high-risk individuals, while avoiding frequent surveillance or unnecessary interventions in those at lower risk. It is known that progression of BE to dysplasia and EAC is accompanied by a host of genetic alterations, and that exploration of these markers could be potentially useful to diagnose/grade dysplasia and/or to risk stratify BE patients. Several biomarkers have shown promise in identifying early neoplastic transformation and thus may be useful adjuncts to histologic evaluation. This review provides an overview of some of the currently available biomarkers and assays, including p53 immunostaining, Wide Area Transepithelial Sampling with Three-Dimensional Computer-Assisted Analysis (WATS^3D), TissueCypher, mutational load analysis (BarreGen), fluorescence in situ hybridization, and DNA content abnormalities as detected by DNA flow cytometry.

Wide-area transepithelial sampling for dysplasia detection in Barrett's esophagus: a systematic review and meta-analysis

BACKGROUND AND AIMS

Seattle protocol forceps biopsy sampling (FB) is currently recommended for surveillance in Barrett's esophagus (BE) but limited by sampling error and lack of compliance. Wide-area transepithelial sampling with 3-dimensional analysis (WATS3D; CDx Diagnostics, Suffern, NY, USA) is reported to increase BE dysplasia detection. We assessed the incremental yield and clinical significance of WATS3D for dysplasia detection over FB in a systematic review and meta-analysis.

METHODS

We queried major scientific databases for studies using WATS3D and FB from 2000 to 2020. The primary outcome was the incremental yield of WATS3D-detected dysplasia (defined as a composite of indefinite for dysplasia, low- and high-grade dysplasia [HGD] and esophageal adenocarcinoma [EAC]) over FB. Secondary outcomes were incremental yields of HGD/EAC and rate of reconfirmation of WATS3D dysplasia on subsequent FB.

RESULTS

Meta-analysis of 7 eligible studies demonstrated that FB diagnosed dysplasia in 15.9% of cases, whereas the incremental yield with WATS3D was 7.2% (95% confidence interval, 3.9%-11.5%; I²= 92.1%). Meta-analysis of 6 studies demonstrated that FB diagnosed HGD/EAC in 2.3% of patients, whereas the incremental yield with WATS3D was 2.1% (95% confidence interval, .4%-5.3%; I²= 92.7%). Notably, WATS3D was negative in 62.5% of cases where FB identified dysplasia. Two studies reported reconfirmation of WATS3D dysplasia with FB histology in only 20 patients.

CONCLUSIONS

WATS3D increases dysplasia detection; however, the clinical significance of this increased dysplasia detection remains uncertain. Data from endoscopic follow-up to ascertain FB histology in patients with dysplasia based solely on WATS3D are needed to determine the optimal clinical application and significance of WATS3D-only dysplasia.

Molecular characterization of Barrett's esophagus at single-cell resolution

Barrett’s esophagus (BE), the premalignant condition of esophageal adenocarcinoma, is categorized into different stages which correlate with the risk of developing carcinoma. We performed single-cell DNA-sequencing experiments with fresh biopsies, which revealed the appearance of a specific T > C and T > G mutational signature, known as COSMIC signature SBS17, in BE cells that are chromosomally unstable. The SBS17-specific mutations were, however, not detected in chromosomally stable BE cells. Additionally, we performed single-cell RNA sequencing experiments which identified seven genes that facilitate the distinction between different BE stages on histological sections.

Barrett’s esophagus (BE) is categorized, based on morphological appearance, into different stages, which correlate with the risk of developing esophageal adenocarcinoma. More advanced stages are more likely to acquire chromosomal instabilities, but stage-specific markers remain elusive. Here, we performed single-cell DNA-sequencing experiments (scDNAseq) with fresh BE biopsies. Dysplastic BE cells frequently contained chromosomal instability (CIN) regions, and these CIN cells carried mutations corresponding to the COSMIC mutational signature SBS17, which were not present in biopsy-matched chromosomally stable (CS) cells or patient-matched nondiseased control cells. CS cells were predominantly found in nondysplastic BE biopsies. The single-base substitution (SBS) signatures of all CS BE cells analyzed were indistinguishable from those of nondiseased esophageal or gastric cells. Single-cell RNA-sequencing (scRNAseq) experiments with BE biopsies identified two sets of marker genes which facilitate the distinction between columnar BE epithelium and nondysplastic/dysplastic stages. Moreover, histological validation confirmed a correlation between increased CLDN2 expression and the presence of dysplastic BE stages. Our scDNAseq and scRNAseq datasets, which are a useful resource for the community, provide insight into the mutational landscape and gene expression pattern at different stages of BE development.

Agrin loss in Barrett's esophagus-related neoplasia and its utility as a diagnostic and predictive biomarker

PURPOSE

There is an unmet need for identifying novel biomarkers in Barrett's esophagus (BE) that could stratify patients with regards to neoplastic progression. We investigate the expression patterns of extracellular matrix (ECM) molecules in BE and BE-related neoplasia, and assess their value as biomarkers for the diagnosis of BE-related neoplasia and to predict neoplastic progression.

EXPERIMENTAL DESIGN

Gene expression analyses of ECM matrisome gene sets were performed using publicly available data on human BE, BE-related dysplasia, esophageal ADCA and normal esophagus. Immunohistochemical expression of basement membrane (BM) marker agrin (AGRN) and p53 was analyzed in biopsies of BE-related neoplasia from 321 patients in three independent cohorts.

RESULTS

Differential gene expression analysis revealed significant enrichment of ECM matrisome gene sets in dysplastic BE and ADCA compared with controls. Loss of BM AGRN expression was observed in both BE-related dysplasia and ADCA. The mean AGRN loss in BE glands was significantly higher in BErelated dysplasia and ADCA compared to non-dysplastic BE (NDBE; p<0.001; specificity=82.2% and sensitivity=96.4%). Loss of AGRN was significantly higher in NDBE samples from progressors compared to non-progressors (p<0.001) and identified patients who progressed to advanced neoplasia with a specificity of 80.2% and sensitivity of 54.8%. Moreover, the combination of AGRN loss and abnormal p53 staining identified progression to BE-related advanced neoplasia with a specificity and sensitivity of 86.5% and 58.7%.

CONCLUSIONS

We highlight ECM changes during BE progression to neoplasia. BM AGRN loss is a novel diagnostic biomarker that can identify NDBE patients at increased risk of developing advanced neoplasia.

The path(ology) from reflux oesophagitis to Barrett oesophagus to oesophageal adenocarcinoma

This review seeks to summarise the steps in the path from reflux oesophagitis to Barrett oesophagus to oesophageal adenocarcinoma. The epidemiology, clinical presentation, definitions, pathological features, diagnostic pitfalls, and emerging concepts are reviewed for each entity. The histological features of reflux oesophagitis can be variable and are not specific. Cases of reflux oesophagitis with numerous eosinophils are difficult to distinguish from eosinophilic oesophagitis and other oesophagitides with eosinophils (Crohn's disease, medication effect, and connective tissue disorders). In reflux oesophagitis, the findings are often most pronounced in the distal oesophagus, the eosinophils are randomly distributed throughout the epithelium, and eosinophilic abscesses and degranulated eosinophils are rare. For reflux oesophagitis with prominent lymphocytes, clinical history and ancillary clinical studies are paramount to distinguish reflux oesophagitis from other causes of lymphocytic oesophagitis pattern. For Barrett oesophagus, the definition remains a hotly debated topic for which the requirement for intestinal metaplasia to make the diagnosis is not applied unanimously across the globe. Assessing for dysplasia is a challenging aspect of the histological interpretation that guides clinical management. We describe the histological features that we find useful in making this evaluation. Oesophageal adenocarcinoma has been steadily increasing in incidence and has a poor prognosis. The extent of invasion can be overdiagnosed due to a duplicated muscularis mucosae. We also describe the technical factors that can lead to challenges in distinguishing the mucosal and deep margins of endoscopic resections. Lastly, we give an overview of targeted therapies with emerging importance and the ancillary tests that can identify the cases best suited for each therapy.

'Artificial intelligence in Barrett's Esophagus'

Despite advances in endoscopic imaging modalities, there are still significant miss rates of dysplasia and cancer in Barrett's esophagus. Artificial intelligence (AI) is a promising tool that may potentially be a useful adjunct to the endoscopist in detecting subtle dysplasia and cancer. Studies have shown AI systems have a sensitivity of more than 90% and specificity of more than 80% in detecting Barrett's related dysplasia and cancer. Beyond visual detection and diagnosis, AI may also prove to be useful in quality control, streamlining clinical work, documentation, and lessening the administrative load on physicians. Research in this area is advancing at a rapid rate, and as the field expands, regulations and guidelines will need to be put into place to better regulate the growth and use of AI. This review provides an overview of the present and future role of AI in Barrett's esophagus.

The natural history of low-grade dysplasia in Barrett's esophagus and risk factors for progression

Background and Aim

Barrett's esophagus is associated with increased risk of esophageal adenocarcinoma. The optimal management of low‐grade dysplasia arising in Barrett's esophagus remains controversial. We performed a retrospective study from a tertiary referral center for Barrett's esophagus neoplasia, to estimate time to progression to high‐grade dysplasia/esophageal adenocarcinoma in patients with confirmed low‐grade dysplasia compared with those with downstaged low‐grade dysplasia from index presentation and referral. We analyzed risk factors for progression.

Methods

We analyzed consecutive patients with low‐grade dysplasia in Barrett's esophagus referred to a single tertiary center (July 2006–October 2018). Biopsies were reviewed by at least two expert pathologists.

Results

One hundred and forty‐seven patients referred with suspected low‐grade dysplasia were included. Forty‐two of 133 (32%) of all external referrals had confirmed low‐grade dysplasia after expert histopathology review. Multivariable analysis showed nodularity at index endoscopy (P < 0.05), location of dysplasia (P = 0.05), and endoscopic therapy after referral (P = 0.09) were associated with progression risk. At 5 years, 59% of patients with confirmed low‐grade dysplasia had not progressed versus 74% of patients in the cohort downstaged to non‐dysplastic Barrett's esophagus.

Conclusion

Our data show variability in the diagnosis of low‐grade dysplasia. The cumulative incidence of progression and time to progression varied across subgroups. Confirmed low‐grade dysplasia had a shorter progression time compared with the downstaged group. Nodularity at index endoscopy and multifocal low‐grade dysplasia were significant risk factors for progression. It is important to differentiate these high‐risk subgroups so that decisions on surveillance/endotherapy can be personalized.

Improving cost-effectiveness of endoscopic surveillance for Barrett's esophagus by reducing low-value care: a review of economic evaluations

BACKGROUND

Individuals with Barrett's esophagus are believed to be at 30-120× risk of developing esophageal adenocarcinoma (EAC). Early detection and endoscopic treatment of dysplasia/early cancer confers a significant advantage to patients under surveillance; however, most do not progress past the non-dysplastic state of Barrett's esophagus (NDBE), which is potentially an inefficient distribution of health care resources.

OBJECTIVES

This article aimed to review the outcomes of cost-effectiveness studies reducing low-value care in the context of endoscopic surveillance for non-dysplastic Barrett's esophagus (NDBE).

METHODS

A systematic search was conducted by two reviewers in accordance with PRISMA guidelines.

INCLUSION CRITERIA

cost-utility analyses of endoscopic surveillance of NDBE patients with at least one treatment strategy focused on reduction of surveillance. A narrative synthesis of economic evaluations was undertaken, along with an in-depth analysis of input parameters contributing to stated Incremental cost-effectiveness ratios (ICER). Study appraisal was performed using the consolidated health economic evaluation reporting standards (CHEERS) tool.

RESULTS

10 Studies met inclusion criteria. There was significant variation in cost-model structures, input parameters, ICER values, and willingness-to-pay thresholds between studies. All studies except one concluded guideline-specified endoscopic surveillance for NDBE patients was not cost-effective. Studies that explored a modified surveillance by deselection of low-risk NDBE patients found it to be a cost-effective strategy.

CONCLUSION

Guideline specified endoscopic surveillance for NDBE was not found to be cost-effective in the studies examined. A modified endoscopic surveillance strategy removing individuals with the lowest risk for progression from NDBE to adenocarcinoma is likely to be cost-effective but is dependent on risk profile of patients excluded from surveillance.

Independent Validation of a Tissue Systems Pathology Assay to Predict Future Progression in Nondysplastic Barrett's Esophagus: A Spatial-Temporal Analysis

An automated risk prediction assay has previously been shown to objectively identify patients with nondysplastic Barrett's esophagus (NDBE) who are at increased risk of malignant progression. To evaluate the predictive performance of the assay in 76 patients with NDBE of which 38 progressed to high-grade dysplasia/esophageal adenocarcinoma (progressors) and 38 did not (nonprogressors) and to determine whether assessment of additional (spatial) levels per endoscopy and/or multiple (temporal) time points improves assay performance.

Taking the Next Steps in Endoscopic Visual Assessment of Barrett's Esophagus: A Pilot Study

Purpose

Patients with Barrett's esophagus (BE) undergo surveillance endoscopies to assess for pre-cancerous changes. We developed a simple endoscopic classification method for predicting non-dysplastic BE (NDBE), low-grade dysplasia (LGD)/indefinite for dysplasia (ID) and high-grade dysplasia (HGD)/early esophageal adenocarcinoma (EAC).

Patients and Methods

Twenty-two patients with BE underwent endoscopy using the PENTAX Medical MagniView gastroscope and OPTIVISTA processor. Sixty-six video-still images were analyzed to characterize the microsurface, microvasculature and the presence of a demarcation line. Class A was characterized by regular microvascular and microsurface patterns and absence of a demarcation line, class B by changes in the microvascular and/or microsurface patterns compared to the background mucosa with presence of a demarcation line, and class C by irregular microvascular and/or irregular microsurface patterns with presence of a demarcation line.

Results

Of the class A images, 97.9% were NDBE. For class B, 69.2% were LGD/ID and 30.8% NDBE. One hundred percent of the class C samples were HGD/EAC. The sensitivity of our classification system was 93.8%, specificity 92%, positive predictive value 78.9%, negative predictive value 97.9% and an accuracy 92.4%.

Conclusion

In this study, we developed a simple classification system for the prediction of NDBE, LGD/ID and HGD/EAC. Its real-time clinical applicability will be validated prospectively.

Tissue Systems Pathology Test Objectively Risk Stratifies Barrett's Esophagus Patients With Low-Grade Dysplasia

INTRODUCTION

Low-grade dysplasia (LGD) is the best predictor of neoplastic progression in Barrett's esophagus (BE). Most LGD cases are downstaged to nondysplastic (ND) BE on expert pathologist review, which is prone to interobserver variation and not widely available. Recent studies indicate that a risk prediction assay (TissueCypher) risk stratifies patients with NDBE for neoplastic progression. We aimed to investigate whether this risk prediction assay predicts neoplastic progression in BE patients with LGD.

METHODS

A blinded, retrospective cohort study was derived from the screening cohort of a randomized controlled trial of SURveillance vs RadioFrequency ablation for BE patients with LGD. Hematoxylin and eosin and p53 immunohistochemistry slides from the first endoscopy with LGD were independently reviewed by 3 expert pathologists and tested by the risk prediction assay. Revision diagnoses of NDBE were considered low risk, although indefinite for dysplasia, and LGD were considered high risk for progression.

RESULTS

A total of 155 BE patients (123 men), mean age 61 ± 10 years, were analyzed. Thirty-four patients (22%) progressed to high-grade dysplasia/esophageal adenocarcinoma (median time 2.4 years) and 121 did not progress (median high-grade dysplasia/esophageal adenocarcinoma-free surveillance 7.9 years). The risk prediction assay sensitivity was 68% vs 76% for the 3 pathologists, and specificity was 79% vs 64%-77.0% for the pathologists. The assay detected 50%-56% of progressors that were downstaged to NDBE by the pathologists.

DISCUSSION

The risk prediction assay provided significant risk stratification in BE patients with LGD and identified progressors that the experts downstaged to NDBE. This objective assay provides an effective solution to the lack of standardization of expert pathology review of LGD.

Deep learning systems detect dysplasia with human-like accuracy using histopathology and probe-based confocal laser endomicroscopy

Probe-based confocal laser endomicroscopy (pCLE) allows for real-time diagnosis of dysplasia and cancer in Barrett's esophagus (BE) but is limited by low sensitivity. Even the gold standard of histopathology is hindered by poor agreement between pathologists. We deployed deep-learning-based image and video analysis in order to improve diagnostic accuracy of pCLE videos and biopsy images. Blinded experts categorized biopsies and pCLE videos as squamous, non-dysplastic BE, or dysplasia/cancer, and deep learning models were trained to classify the data into these three categories. Biopsy classification was conducted using two distinct approaches-a patch-level model and a whole-slide-image-level model. Gradient-weighted class activation maps (Grad-CAMs) were extracted from pCLE and biopsy models in order to determine tissue structures deemed relevant by the models. 1970 pCLE videos, 897,931 biopsy patches, and 387 whole-slide images were used to train, test, and validate the models. In pCLE analysis, models achieved a high sensitivity for dysplasia (71%) and an overall accuracy of 90% for all classes. For biopsies at the patch level, the model achieved a sensitivity of 72% for dysplasia and an overall accuracy of 90%. The whole-slide-image-level model achieved a sensitivity of 90% for dysplasia and 94% overall accuracy. Grad-CAMs for all models showed activation in medically relevant tissue regions. Our deep learning models achieved high diagnostic accuracy for both pCLE-based and histopathologic diagnosis of esophageal dysplasia and its precursors, similar to human accuracy in prior studies. These machine learning approaches may improve accuracy and efficiency of current screening protocols.

Deep learning systems detect dysplasia with human-like accuracy using histopathology and probe-based confocal laser endomicroscopy

Probe-based confocal laser endomicroscopy (pCLE) allows for real-time diagnosis of dysplasia and cancer in Barrett's esophagus (BE) but is limited by low sensitivity. Even the gold standard of histopathology is hindered by poor agreement between pathologists. We deployed deep-learning-based image and video analysis in order to improve diagnostic accuracy of pCLE videos and biopsy images. Blinded experts categorized biopsies and pCLE videos as squamous, non-dysplastic BE, or dysplasia/cancer, and deep learning models were trained to classify the data into these three categories. Biopsy classification was conducted using two distinct approaches-a patch-level model and a whole-slide-image-level model. Gradient-weighted class activation maps (Grad-CAMs) were extracted from pCLE and biopsy models in order to determine tissue structures deemed relevant by the models. 1970 pCLE videos, 897,931 biopsy patches, and 387 whole-slide images were used to train, test, and validate the models. In pCLE analysis, models achieved a high sensitivity for dysplasia (71%) and an overall accuracy of 90% for all classes. For biopsies at the patch level, the model achieved a sensitivity of 72% for dysplasia and an overall accuracy of 90%. The whole-slide-image-level model achieved a sensitivity of 90% for dysplasia and 94% overall accuracy. Grad-CAMs for all models showed activation in medically relevant tissue regions. Our deep learning models achieved high diagnostic accuracy for both pCLE-based and histopathologic diagnosis of esophageal dysplasia and its precursors, similar to human accuracy in prior studies. These machine learning approaches may improve accuracy and efficiency of current screening protocols.

TissueCypher Barrett's esophagus assay impacts clinical decisions in the management of patients with Barrett's esophagus

Background and study aims  The TissueCypher Barrett's Esophagus Assay is a novel tissue biomarker test, and has been validated to predict progression to high-grade dysplasia (HGD) and esophageal adenocarcinoma (EAC) in patients with Barrett's esophagus (BE). The aim of this study was to evaluate the impact of TissueCypher on clinical decision-making in the management of BE. Patients and methods  TissueCypher was ordered for 60 patients with non-dysplastic (ND, n = 18) BE, indefinite for dysplasia (IND, n = 25), and low-grade dysplasia (LGD, n = 17). TissueCypher reports a risk class (low, intermediate or high) for progression to HGD or EAC within 5 years. The impact of the test results on BE management decisions was assessed. Results  Fifty-two of 60 patients were male, mean age 65.2 ± 11.8, and 43 of 60 had long segment BE. TissueCypher results impacted 55.0 % of management decisions. In 21.7 % of patients, the test upstaged the management approach, resulting in endoscopic eradication therapy (EET) or shorter surveillance interval. The test downstaged the management approach in 33.4 % of patients, leading to surveillance rather than EET. In the subset of patients whose management plan was changed, upstaging was associated with a high-risk TissueCypher result, and downstaging was associated with a low-risk result ( P  < 0.0001). Conclusions  TissueCypher was used as an adjunct to support a surveillance-only approach in 33.4 % of patients. Upstaging occurred in 21.7 % of patients, leading to therapeutic intervention or increased surveillance. These results indicate that the TissueCypher test may enable physicians to target EET for TissueCypher high-risk BE patients, while reducing unnecessary procedures in TissueCypher low-risk patients.

Non-conventional dysplasias of the tubular gut: a review and illustration of their histomorphological spectrum

The increasing use of gastrointestinal endoscopic procedures has led to the recognition by histopathologists of non-conventional (or special-type) dysplasias of the gastrointestinal tract. These lesions can be recognised in association with prevalent underlying gastrointestinal conditions, such as Barrett oesophagus, chronic atrophic gastritis, and inflammatory bowel disease. The diagnosis of these special types can be challenging, and their biological behaviours are not fully characterised. The aim of this review is to provide a global view of non-conventional dysplastic lesions observed in the various segments of the tubular gastrointestinal tract and describe their salient features. Furthermore, as the clinical implications of these various subtypes have not been broadly tested in practice and are not represented in most management guidelines, we offer guidance on the best management practices for these lesions.

Alteration of protein expression and spliceosome pathway activity during Barrett's carcinogenesis

BACKGROUND

Barrett's esophagus (BE) is a known precursor lesion and the strongest risk factor for esophageal adenocarcinoma (EAC), a common and lethal type of cancer. Prediction of risk, the basis for efficient intervention, is commonly solely based on histologic examination. This approach is challenged by problems such as inter-observer variability in the face of the high heterogeneity of dysplastic tissue. Molecular markers might offer an additional way to understand the carcinogenesis and improve the diagnosis-and eventually treatment. In this study, we probed significant proteomic changes during dysplastic progression from BE into EAC.

METHODS

During endoscopic mucosa resection, epithelial and stromal tissue samples were collected by laser capture microdissection from 10 patients with normal BE and 13 patients with high-grade dysplastic/EAC. Samples were analyzed by mass spectrometry-based proteomic analysis. Expressed proteins were determined by label-free quantitation, and gene set enrichment was used to find differentially expressed pathways. The results were validated by immunohistochemistry for two selected key proteins (MSH6 and XPO5).

RESULTS

Comparing dysplastic/EAC to non-dysplastic BE, we found in equal volumes of epithelial tissue an overall up-regulation in terms of protein abundance and diversity, and determined a set of 226 differentially expressed proteins. Significantly higher expressions of MSH6 and XPO5 were validated orthogonally and confirmed by immunohistochemistry.

CONCLUSIONS

Our results demonstrate that disease-related proteomic alterations can be determined by analyzing minute amounts of cell-type-specific collected tissue. Further analysis indicated that alterations of certain pathways associated with carcinogenesis, such as micro-RNA trafficking, DNA damage repair, and spliceosome activity, exist in dysplastic/EAC.

Advances in Biomarkers for Risk Stratification in Barrett's Esophagus

Dysplasia currently is the primary biomarker used to risk stratify patients with Barrett's esophagus, but dysplasia has a number of considerable limitations in this regard. Thus, investigators over the years have explored innumerable alternative molecular biomarkers for risk stratification in Barrett's esophagus. This report focuses only on those biomarkers that appear most promising based on the availability of multiple published studies corroborating good results, and on the commercial availability of the test. These promising biomarkers include p53 immunostaining, TissueCypher, BarreGEN, and wide-area transepithelial sampling with computer-assisted 3-dimensional analysis (WATS^3D).

Approaches to Research Determination of Late Acute Cellular Rejection in Pediatric Liver Transplant Recipients

A central pathology or site reading of biopsy slides is used in liver transplant clinical trials to determine rejection. We evaluated interrater reliability of readings of "rejection or not" using digitized slides from the Medication Adherence in Children who had a Liver Transplant (MALT) study. Four masked experienced pathologists read the digitized slides and then reread them after a study-specific histologic endpoint development program. Agreement was expressed throughout as a Kappa or Fleiss Kappa statistic (ҡ). A ҡ > 0.6 was predefined as desirable. Readings were correlated with immunosuppressant adherence (the Medication Level Variability Index, [MLVI]), and maximal liver enzyme levels during the study period. Interrater agreement between site and central review in MALT, and between 4 pathologists later on, was low (ҡ = 0.44, Fleiss ҡ = 0.41, respectively). Following the endpoint development program, agreement improved and became acceptable (ҡ = 0.71). The final reading was better-aligned with maximal gamma-glutamyl transferase levels and MLVI as compared with the original central reading. We found substantial disagreement between experienced pathologists reading the same slides. A unique study-specific procedure improved interrater reliability to the point it was acceptable. Such a procedure may be indicated to increase reliability of histopathologic determinations in future research, and perhaps also clinically.