Hassan, Cesare

Abstract Artificial intelligence (AI) and mucosal exposure devices like Endocuff have independently improved the adenoma detection rate (ADR) during colonoscopy. This meta-analysis evaluated the combined effect of Endocuff and AI versus AI alone on colorectal neoplasia detection rates. We searched PubMed, Embase, and Web of Science for randomized controlled trials (RCTs) comparing the impact of Endocuff+AI versus AI alone on colorectal neoplasia detection. Primary outcome was ADR; secondary outcomes included advanced adenoma detection rate (AADR), sessile serrated lesion detection rate (SSLDR), cecal intubation time, and withdrawal time. Pooled risk ratios (RRs) and mean differences (MDs) with 95% confidence intervals (CIs) were calculated using a random-effects model. Three RCTs with 2404 subjects were included (n = 1198 Endocuff+AI vs. n = 1206 AI alone). ADR was significantly higher in the Endocuff+AI group than in the AI alone group (54% vs. 48%, respectively) (RR 1.12, 95% CI 1.03–1.21, P = 0.01, I2 = 0%). There was a trend toward higher AADR (12.3% vs. 10%, RR 1.23, 95% CI 0.96–1.59, P = 0.10, I2 = 17%) and SSLDR (17.6% vs. 15.5%, RR 1.16, 95% CI 0.96–1.40, P = 0.13, I2 = 0%) in the Endocuff+AI group compared with the AI alone group, but it did not reach statistical significance. Both cecal intubation time (MD -0.61 minutes; 95% CI -1.54–0.33; P = 0.20; I2 = 87%) and withdrawal time (MD -0.42 minutes; 95% CI -1.01–0.17; P = 0.17, I2 = 60%) were similar between the two groups. Endocuff combined with AI was superior to AI alone in improving the adenoma detection rate without increasing intubation or withdrawal times.

ObjectivesAchalasia is an esophageal motility disorder that impairs quality of life and is often missed (20–50%) on endoscopy. A newly developed computer‐aided detection (CAD) software has shown high accuracy for achalasia diagnosis in preclinical settings. However, its benefit in a clinical setting remains unclear.MethodsBetween February and August 2023, 83 endoscopists from 27 centers assessed 50 randomized endoscopic videos (25 achalasia, 25 nonachalasia) without and with CAD. Endoscopists assessed videos without CAD, then with CAD after 2 months. The primary end‐point was improvement in sensitivity for nonexperienced endoscopists (no endoscopic experience of achalasia). Sensitivity, specificity, and accuracy with and without CAD were compared using the McNemar test.ResultsSensitivity for diagnosing achalasia increased significantly with CAD, rising from 74.2% (95% confidence interval [CI] 72.2–76.0%) to 91.2% (95% CI 89.9–92.4%) for all readers, showing a difference of 17.1% (95% CI 15.1–19.0%). Specifically, sensitivity improved from 66.9% (95% CI 63.6–70.0%) to 91.9% (95% CI 89.9–93.6%) among nonexperienced endoscopists, resulting in a difference of 25.0% (95% CI 21.7–28.4%), and from 79.5% (95% CI 77.1–81.8%) to 90.8% (95% CI 89.0–92.3%) among experienced endoscopists (endoscopic experience of at least one achalasia case), with a difference of 11.3% (95% CI 8.9–13.6%). Accuracy and specificity improved significantly with CAD assistance, regardless of reader's experience.ConclusionCAD improves achalasia detection by 17%, confirming preclinical results. The benefit was higher for nonexperienced endoscopists. CAD assistance may lead to prompt and effective treatment, minimizing the risk of false‐negative diagnosis in clinical practice.Trial registrationThis study was registered in the University Hospital Medical Information Network Clinical Trial Registry (https://www.umin.ac.jp/ctr/) number: UMIN000053047.

Esophageal squamous cell carcinoma (ESCC) remains a significant global health challenge, being the sixth leading cause of cancer mortality with pronounced geographic variability. The incidence rates range from 125 per 100,000 in northern China to 1–1.5 per 100,000 in the United States, driven by environmental and lifestyle factors such as tobacco and alcohol use, dietary habits, and pollution. Major modifiable risk factors include tobacco and alcohol consumption, with a synergistic risk increase when combined. Nonmodifiable risk factors include previous diagnoses of head and neck squamous cell carcinoma (H&N SCC), achalasia, and prior radiotherapy. Prevention strategies must be tailored to specific regional burdens to efficiently allocate medical and financial resources. Gastrointestinal endoscopy is crucial in reducing ESCC burden through early detection and characterization of neoplastic changes, such as high‐grade dysplasia. Early diagnosis significantly improves survival rates, while endoscopic resection of noninvasive dysplasia can prevent ESCC onset, reducing treatment burden for advanced disease. Postresection surveillance can detect high‐risk metachronous lesions. Despite these benefits, endoscopic prevention faces challenges, including the lack of high‐level evidence supporting its efficacy, opportunity costs, the need for specialized training and techniques, and the requirement for advanced technology investments. This Position Statement from the World Endoscopy Organization (WEO) aims to address these challenges, supplying recommendations for the exploitation of endoscopic resources regarding the possible role of screening, quality, and training for the detection, characterization, resection, and surveillance of ESCC.

INTRODUCTION: The performance of a high quality esophagogastroduodenoscopy (EGD) is dependent on the mucosal cleanliness. Recently, the Polprep: Effective Assessment of Cleanliness in EGD (PEACE) scale was created to assess the degree of mucosal cleanliness during EGD. The aim of this study was to validate this scoring system in a cohort of international endoscopists. METHODS: In total, 39 EGD videos, with different degrees of mucosal cleanliness were retrieved from a previously conducted prospective trial. All experts rated the cleanliness of the mucosa on each video using the PEACE scale. To evaluate agreement of all scores (0–3), intraclass correlation coefficient 2.1 was used. The agreement on adequate (scores 2 and 3) and inadequate (scores 0 and 1) cleanliness was assessed using kappa values. RESULTS: Videos evaluating esophagus, stomach, and duodenum cleanliness were reviewed by 16 endoscopists. The PEACE scores demonstrated good agreement (intraclass correlation coefficient 0.82, 95% CI 0.75–0.89), especially for esophagus (0.84; 95% CI 0.71–0.95) and stomach (0.81; 95% CI 0.69–0.91), while agreement was moderate for the duodenum (0.69; 95% CI 0.51–0.87). The agreement was similar between Eastern (0.86; 95% CI 0.79–0.92) and Western experts (0.80; 95% CI 0.72–0.88). Similarly, agreement regarding adequate cleanliness was comparable between Eastern (0.70; 95% CI 0.55–0.85) and Western (0.74; 95% CI 0.64–0.84) endoscopists being overall 0.75 (95% CI 0.65–0.85). DISCUSSION: The PEACE scoring system is a simple and reliable scale to assess the cleanliness during EGD. The score is now validated among international experts with high concordance, justifying its use in clinical practice.

Abstract Background and study aims Use of fluoroscopy in gastrointestinal endoscopy is an essential aid in advanced endoscopic interventions. However, it also raises concerns about radiation exposure. This study aimed to develop consensus-based statements for safe and effective use of fluoroscopy in gastrointestinal endoscopy, prioritizing the safety and well-being of healthcare workers and patients. Methods A modified Delphi approach was employed to achieve consensus over three rounds of surveys. Proposed statements were generated in Round 1. In the second round, panelists rated potential statements on a 5-point scale, with consensus defined as ≥80% agreement. Statements were subsequently prioritized in Round 3, using a 1 (lowest priority) to 10 (highest priority) scale. Results Forty-six experts participated, consisting of 34 therapeutic endoscopists and 12 endoscopy nurses from six continents, with an overall 45.6% female representation (n = 21). Forty-three item statements were generated in the first round. Of these, 31 statements achieved consensus after the second round. These statements were categorized into General Considerations (n = 6), Education (n = 10), Pregnancy (n = 4), Family Planning (n = 2), Patient Safety (n = 4), and Staff Safety (n = 5). In the third round, accepted statements received mean priority scores ranging from 7.28 to 9.36, with 87.2% of statements rated as very high priority (mean score ≥ 9). Conclusions This study presents consensus-based statements for safe and effective use of fluoroscopy in gastrointestinal endoscopy, addressing the well-being of healthcare workers and patients. These consensus-based statements aim to mitigate risks associated with radiation exposure while maintaining benefits of fluoroscopy, ultimately promoting a culture of safety in healthcare settings.

The number of artificial intelligence (AI) tools for colonoscopy on the market is increasing with supporting clinical evidence. Nevertheless, their implementation is not going smoothly for a variety of reasons, including lack of data on clinical benefits and cost‐effectiveness, lack of trustworthy guidelines, uncertain indications, and cost for implementation. To address this issue and better guide practitioners, the World Endoscopy Organization (WEO) has provided its perspective about the status of AI in colonoscopy as the position statement. WEO Position Statement: Statement 1.1: Computer‐aided detection (CADe) for colorectal polyps is likely to improve colonoscopy effectiveness by reducing adenoma miss rates and thus increase adenoma detection; Statement 1.2: In the short term, use of CADe is likely to increase health‐care costs by detecting more adenomas; Statement 1.3: In the long term, the increased cost by CADe could be balanced by savings in costs related to cancer treatment (surgery, chemotherapy, palliative care) due to CADe‐related cancer prevention; Statement 1.4: Health‐care delivery systems and authorities should evaluate the cost‐effectiveness of CADe to support its use in clinical practice; Statement 2.1: Computer‐aided diagnosis (CADx) for diminutive polyps (≤5 mm), when it has sufficient accuracy, is expected to reduce health‐care costs by reducing polypectomies, pathological examinations, or both; Statement 2.2: Health‐care delivery systems and authorities should evaluate the cost‐effectiveness of CADx to support its use in clinical practice; Statement 3: We recommend that a broad range of high‐quality cost‐effectiveness research should be undertaken to understand whether AI implementation benefits populations and societies in different health‐care systems.