Development and external validation of a model to predict complex treatment after RFA for Barrett's esophagus with early neoplasia

Background & Aims: Endoscopic eradication therapy for Barrett's esophagus (BE)-related neoplasia is safe and leads to complete eradication in the majority of patients. However, a subgroup will experience a more complex treatment course with a risk for failure or disease progression. Early identification of these patients may improve patient counseling and treatment outcomes. We aimed to develop a prognostic model for a complex treatment course. Methods: We collected data from a nationwide registry that captures outcomes for all patients undergoing endoscopic eradication therapy for early BE neoplasia. A complex treatment course was defined as neoplastic progression, treatment failure, or the need for endoscopic resection during the radiofrequency ablation treatment phase. We developed a prognostic model using logistic regression. We externally validated our model in an independent registry. Results: A total of 1386 patients were included, of whom 78 (6%) had a complex treatment course. Our model identified patients with a BE length of 9 cm or longer with a visible lesion containing high-grade dysplasia/cancer, and patients with less than 50% squamous conversion after radiofrequency ablation were identified as high risk for a complex treatment. This applied to 8% of the study population and included 93% of all treatment failures and 76% of all patients with advanced neoplastic progression. The model appeared robust in multiple sensitivity analyses and performed well in external validation (area under the curve, 0.84). Conclusions: We developed a prognostic model that identified patients with a BE length of 9 cm or longer and high-grade dysplasia/esophageal adenocarcinoma and those with poor squamous regeneration as high risk for a complex treatment course. The good performance in external validation suggests that it may be used in clinical management (Netherlands Trial Register: NL7039)

Performance of gastrointestinal pathologists within a national digital review panel for Barrett's oesophagus in the Netherlands: Results of 80 prospective biopsy reviews

Aims: The histopathological diagnosis of low-grade dysplasia (LGD) in Barrett's oesophagus (BO) is associated with poor interobserver agreement and guidelines dictate expert review. To facilitate nationwide expert review in the Netherlands, a web-based digital review panel has been set up, which currently consists of eight 'core' pathologists. The aim of this study was to evaluate if other pathologists from the Dutch BO expert centres qualify for the expert panel by assessing their performance in 80 consecutive LGD reviews submitted to the panel. Methods: Pathologists independently assessed digital slides in two phases. Both phases consisted of 40 cases, with a group discussion after phase I. For all cases, a previous consensus diagnosis made by five core pathologists was available, which was used as reference. The following criteria were used: (1) percentage of 'indefinite for dysplasia' diagnoses, (2) percentage agreement with consensus diagnosis and (3) proportion of cases with a consensus diagnosis of dysplasia underdiagnosed as non-dysplastic. Benchmarks were based on scores of the core pathologists. Results: After phase I, 1/7 pathologists met the benchmark scor

Blue-light imaging and linked-color imaging improve visualization of Barrett's neoplasia by nonexpert endoscopists

BACKGROUND AND AIMS: Endoscopic recognition of early Barrett's neoplasia is challenging. Blue-light imaging (BLI) and linked-color imaging (LCI) may assist endoscopists in appreciation of neoplasia. Our aim was to evaluate BLI and LCI for visualization of Barrett's neoplasia in comparison with white-light endoscopy (WLE) alone, when assessed by nonexpert endoscopists. METHODS: In this web-based assessment, corresponding WLE, BLI, and LCI images of 30 neoplastic Barrett's lesions were delineated by 3 expert endoscopists to establish ground truth. These images were then scored and delineated by 76 nonexpert endoscopists from 3 countries and with different levels of expertise, in 4 separate assessment phases with a washout period of 2 weeks. Assessments were as follows: assessment 1, WLE only; assessment 2, WLE + BLI; assessment 3, WLE + LCI; assessment 4, WLE + BLI + LCI. The outcomes were (1) appreciation of macroscopic appearance and ability to delineate lesions (visual analog scale [VAS] scores); (2) preferred technique (ordinal scores); and (3) assessors' delineation performance in terms of overlap with expert ground truth. RESULTS: Median VAS scores for phases 2 to 4 were significantly higher than in phase 1 (P < .001). Assessors preferred BLI and LCI over WLE for appreciation of macroscopic appearance (P < .001) and delineation (P < .001). Linear mixed-effect models showed that delineation performance increased significantly in phase 4. CONCLUSIONS: The use of BLI and LCI has significant additional value for the visualization of Barrett's neoplasia when used by nonexpert endoscopists. Assessors appreciated the addition of BLI and LCI better than the use of WLE alone. Furthermore, this addition led to improved delineation performance, thereby allowing for better acquisition of targeted biopsy samples. (The Netherlands Trial Registry number: NL7541.).status: publishe

Blue-light imaging and linked-color imaging improve visualization of Barrett's neoplasia by nonexpert endoscopists

Background and Aims: Endoscopic recognition of early Barrett's neoplasia is challenging. Blue-light imaging (BLI) and linked-color imaging (LCI) may assist endoscopists in appreciation of neoplasia. Our aim was to evaluate BLI and LCI for visualization of Barrett's neoplasia in comparison with white-light endoscopy (WLE) alone, when assessed by nonexpert endoscopists. Methods: In this web-based assessment, corresponding WLE, BLI, and LCI images of 30 neoplastic Barrett's lesions were delineated by 3 expert endoscopists to establish ground truth. These images were then scored and delineated by 76 nonexpert endoscopists from 3 countries and with different levels of expertise, in 4 separate assessment phases with a washout period of 2 weeks. Assessments were as follows: assessment 1, WLE only; assessment 2, WLE + BLI; assessment 3, WLE + LCI; assessment 4, WLE + BLI + LCI. The outcomes were (1) appreciation of macroscopic appearance and ability to delineate lesions (visual analog scale [VAS] scores); (2) preferred technique (ordinal scores); and (3) assessors’ delineation performance in terms of overlap with expert ground truth. Results: Median VAS scores for phases 2 to 4 were significantly higher than in phase 1 (P < .001). Assessors preferred BLI and LCI over WLE for appreciation of macroscopic appearance (P < .001) and delineation (P < .001). Linear mixed-effect models showed that delineation performance increased significantly in phase 4. Conclusions: The use of BLI and LCI has significant additional value for the visualization of Barrett's neoplasia when used by nonexpert endoscopists. Assessors appreciated the addition of BLI and LCI better than the use of WLE alone. Furthermore, this addition led to improved delineation performance, thereby allowing for better acquisition of targeted biopsy samples. (The Netherlands Trial Registry number: NL7541.

Do we still need EUS in the workup of patients with early esophageal neoplasia? A retrospective analysis of 131 cases

Background: EUS is often used for locoregional staging of early esophageal neoplasia. However, its value compared with that of endoscopic examination and diagnostic endoscopic resection (ER) may be questioned because diagnostic ER allows histological assessment of submucosal invasion and other risk factors for lymph node metastasis, eg, poor differentiation/lymphovascular invasion. Objective: To evaluate how often patients were excluded from endoscopic treatment of esophageal neoplasia based on EUS findings. Design: Retrospective cohort study. Setting: Tertiary care institution. Patients: Patients with early esophageal neoplasia. Interventions: EUS, diagnostic ER. Main Outcome Measurements: Number of patients excluded from endoscopic treatment based on EUS results. Results: A total of 131 patients were included (98 men, 33 women; age 66 +/- 13 years). In 105 of 131 patients (80%), EUS findings were unremarkable. In 23 of 105 patients (24%), diagnostic ER showed submucosal invasion (n = 17), deep resection margins positive for cancer (n = 2, confirmed at surgery), or poor differentiation/lymphovascular invasion (n = 6). In 26 of 131 patients (20%), EUS findings raised the suspicion of submucosal invasion and/or lymph node metastasis. In the 14 of 26 patients (54%) with abnormal EUS findings, endoscopy results were unremarkable. Diagnostic ER showed submucosal invasion in 7 of 14 (50%) patients, whereas no lymph node metastasis risk factors were found in 7 of 14 patients (50%), who subsequently underwent curative endoscopic treatment. In 12 of 26 patients (46%) with abnormal EUS, endoscopy also raised doubts on whether curative endoscopic treatment could be achieved. After diagnostic ER, no risk factors for lymph node metastasis were found in 3 of 12 patients (25%). Limitation: Retrospective study. Conclusions: This study shows that EUS has virtually no clinical impact on the workup of early esophageal neoplasia and strengthens the role of diagnostic ER as a final diagnostic step. (Gastrointest Endosc 2011;73:662-8.

A computer-assisted algorithm for narrow-band imaging-based tissue characterization in Barrett's esophagus.

BACKGROUND AND AIMS: The endoscopic evaluation of narrow-band imaging (NBI) zoom imagery in Barrett's esophagus (BE) is associated with suboptimal diagnostic accuracy and poor interobserver agreement. Computer-aided diagnosis (CAD) systems may assist endoscopists in the characterization of Barrett's mucosa. Our aim was to demonstrate the feasibility of a deep-learning CAD system for tissue characterization of NBI zoom imagery in BE. METHODS: The CAD system was first trained using 494,364 endoscopic images of general endoscopic imagery. Next, 690 neoplastic BE and 557 nondysplastic BE (NDBE) white-light endoscopy overview images were used for refinement training. Subsequently, a third dataset of 112 neoplastic and 71 NDBE NBI zoom images with histologic correlation was used for training and internal validation. Finally, the CAD system was further trained and validated with a fourth, histologically confirmed dataset of 59 neoplastic and 98 NDBE NBI zoom videos. Performance was evaluated using fourfold cross-validation. The primary outcome was the diagnostic performance of the CAD system for classification of neoplasia in NBI zoom videos. RESULTS: The CAD system demonstrated accuracy, sensitivity, and specificity for detection of BE neoplasia using NBI zoom images of 84%, 88%, and 78%, respectively. In total, 30,021 individual video frames were analyzed by the CAD system. Accuracy, sensitivity, and specificity of the video-based CAD system were 83% (95% confidence interval [CI], 78%-89%), 85% (95% CI, 76%-94%), and 83% (95% CI, 76%-90%), respectively. The mean assessment speed was 38 frames per second. CONCLUSION: We have demonstrated promising diagnostic accuracy of predicting the presence/absence of Barrett's neoplasia on histologically confirmed unaltered NBI zoom videos with fast corresponding assessment time.status: Published onlin

A computer-assisted algorithm for narrow-band imaging-based tissue characterization in Barrett's esophagus

Background and Aims: The endoscopic evaluation of narrow-band imaging (NBI) zoom imagery in Barrett's esophagus (BE) is associated with suboptimal diagnostic accuracy and poor interobserver agreement. Computer-aided diagnosis (CAD) systems may assist endoscopists in the characterization of Barrett's mucosa. Our aim was to demonstrate the feasibility of a deep-learning CAD system for tissue characterization of NBI zoom imagery in BE. Methods: The CAD system was first trained using 494,364 endoscopic images of general endoscopic imagery. Next, 690 neoplastic BE and 557 nondysplastic BE (NDBE) white-light endoscopy overview images were used for refinement training. Subsequently, a third dataset of 112 neoplastic and 71 NDBE NBI zoom images with histologic correlation was used for training and internal validation. Finally, the CAD system was further trained and validated with a fourth, histologically confirmed dataset of 59 neoplastic and 98 NDBE NBI zoom videos. Performance was evaluated using fourfold cross-validation. The primary outcome was the diagnostic performance of the CAD system for classification of neoplasia in NBI zoom videos. Results: The CAD system demonstrated accuracy, sensitivity, and specificity for detection of BE neoplasia using NBI zoom images of 84%, 88%, and 78%, respectively. In total, 30,021 individual video frames were analyzed by the CAD system. Accuracy, sensitivity, and specificity of the video-based CAD system were 83% (95% confidence interval [CI], 78%-89%), 85% (95% CI, 76%-94%), and 83% (95% CI, 76%-90%), respectively. The mean assessment speed was 38 frames per second. Conclusion: We have demonstrated promising diagnostic accuracy of predicting the presence/absence of Barrett's neoplasia on histologically confirmed unaltered NBI zoom videos with fast corresponding assessment time

Deep learning algorithm detection of Barrett's neoplasia with high accuracy during live endoscopic procedures: a pilot study (with video)

Background and Aims: We assessed the preliminary diagnostic accuracy of a recently developed computer-aided detection (CAD) system for detection of Barrett's neoplasia during live endoscopic procedures. Methods: The CAD system was tested during endoscopic procedures in 10 patients with nondysplastic Barrett's esophagus (NDBE) and 10 patients with confirmed Barrett's neoplasia. White-light endoscopy images were obtained at every 2-cm level of the Barrett's segment and immediately analyzed by the CAD system, providing instant feedback to the endoscopist. At every level, 3 images were evaluated by the CAD system. Outcome measures were diagnostic performance of the CAD system per level and per patient, defined as accuracy, sensitivity, and specificity (ground truth was established by expert assessment and corresponding histopathology), and concordance of 3 sequential CAD predictions per level. Results: Accuracy, sensitivity, and specificity of the CAD system in a per-level analyses were 90%, 91%, and 89%, respectively. Nine of 10 neoplastic patients were correctly diagnosed. The single lesion not detected by CAD showed NDBE in the endoscopic resection specimen. In only 1 NDBE patient, the CAD system produced false-positive predictions. In 75% of all levels, the CAD system produced 3 concordant predictions. Conclusions: This is one of the first studies to evaluate a CAD system for Barrett's neoplasia during live endoscopic procedures. The system detected neoplasia with high accuracy, with only a small number of false-positive predictions and with a high concordance rate between separate predictions. The CAD system is thereby ready for testing in larger, multicenter trials. (Clinical trial registration number: NL7544.

EAES Multidisciplinary Rapid Guideline : systematic review, meta-analysis, GRADE assessment and evidence-informed recommendations on the surgical management of paraesophageal hernias

Abstract: Background New evidence has emerged since latest guidelines on the management of paraesophageal hernia, and guideline development methodology has evolved. Members of the European Association for Endoscopic Surgery have prioritized the management of paraesophageal hernia to be addressed by pertinent recommendations. Objective To develop evidence-informed clinical practice recommendations on paraesophageal hernias, through evidence synthesis and a structured evidence-to-decision framework by an interdisciplinary panel of stakeholders. Methods We performed three systematic reviews, and we summarized and appraised the certainty of the evidence using the GRADE methodology. A panel of general and upper gastrointestinal surgeons, gastroenterologists and a patient advocate discussed the evidence in the context of benefits and harms, the certainty of the evidence, acceptability, feasibility, equity, cost and use of resources, moderated by a Guidelines International Network-certified master guideline developer and chair. We developed the recommendations in a consensus meeting, followed by a modified Delphi survey. Results The panel suggests surgery over conservative management for asymptomatic/minimally symptomatic paraesophageal hernias (conditional recommendation), and recommends conservative management over surgery for asymptomatic/minimally symptomatic paraesophageal hernias in frail patients (strong recommendation). Further, the panel suggests mesh over sutures for hiatal closure in paraesophageal hernia repair, fundoplication over gastropexy in elective paraesophageal hernia repair, and gastropexy over fundoplication in patients who have cardiopulmonary instability and require emergency paraesophageal hernia repair (conditional recommendation). A strong recommendation means that the proposed course of action is appropriate for the vast majority of patients. A conditional recommendation means that most patients would opt for the proposed course of action, and joint decision-making of the surgeon and the patient is required. Accompanying evidence summaries and evidence-to-decision frameworks should be read when using the recommendations. This guideline applies to adult patients with moderate to large paraesophageal hernias type II to IV with at least 50% of the stomach herniated to the thoracic cavity. The full guideline with user-friendly decision aids is available in https://app.magicapp.org/#/guideline/j7q7Gn. Conclusion An interdisciplinary panel provides recommendations on key topics on the management of paraesophageal hernias using highest methodological standards and following a transparent process.Guideline registration numberPREPARE-2023CN018