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Artificial intelligence (AI) tools aimed at improving polyp detection have been shown to increase the adenoma detection rate during colonoscopy. However, it is unknown how increased polyp detection rates by AI affect the burden of patient surveillance after polyp removal.We conducted a pooled analysis of 9 randomized controlled trials (5 in China, 2 in Italy, 1 in Japan, and 1 in the United States) comparing colonoscopy with or without AI detection aids. The primary outcome was the proportion of patients recommended to undergo intensive surveillance (ie, 3-year interval). We analyzed intervals for AI and non-AI colonoscopies for the U.S. and European recommendations separately. We estimated proportions by calculating relative risks using the Mantel-Haenszel method.A total of 5796 patients (51% male, mean 53 years of age) were included; 2894 underwent AI-assisted colonoscopy and 2902 non-AI colonoscopy. When following U.S. guidelines, the proportion of patients recommended intensive surveillance increased from 8.4% (95% CI, 7.4%-9.5%) in the non-AI group to 11.3% (95% CI, 10.2%-12.6%) in the AI group (absolute difference, 2.9% [95% CI, 1.4%-4.4%]; risk ratio, 1.35 [95% CI, 1.16-1.57]). When following European guidelines, it increased from 6.1% (95% CI, 5.3%-7.0%) to 7.4% (95% CI, 6.5%-8.4%) (absolute difference, 1.3% [95% CI, 0.01%-2.6%]; risk ratio, 1.22 [95% CI, 1.01-1.47]).The use of AI during colonoscopy increased the proportion of patients requiring intensive colonoscopy surveillance by approximately 35% in the United States and 20% in Europe (absolute increases of 2.9% and 1.3%, respectively). While this may contribute to improved cancer prevention, it significantly adds patient burden and healthcare costs.

Barrett’s esophagus is the sole known precursor for esophageal adenocarcinoma. Endoscopic surveillance for Barrett’s esophagus is recommended to help identify and manage dysplasia, with the ultimate goal being prevention or early detection of esophageal adenocarcinoma. The current standard of care for endoscopic surveillance for Barrett’s esophagus, the Seattle protocol, has many drawbacks. Methods to overcome these disadvantages have been an active area of research. This review will focus on some of the technologies to help improve dysplasia surveillance in Barrett’s esophagus, including advanced endoscopic imaging, artificial intelligence, and wide-area transepithelial sampling with computer-assisted 3D analysis (WATS-3D).

BACKGROUND In resource-limited countries, risk stratification can be used to optimize colorectal cancer screening. Few prospective risk prediction models exist for advanced neoplasia (AN) in true average-risk individuals. AIM To create and internally validate a risk prediction model for detection of AN in average-risk individuals. METHODS Prospective study of asymptomatic individuals undergoing first screening colonoscopy. Detailed characteristics including diet, exercise and medications were collected. Multivariate logistic regression was used to elucidate risk factors for AN (adenoma ≥1 cm, villous histology, high-grade dysplasia or carcinoma). The model was validated through bootstrapping, and discrimination and calibration of the model were assessed. RESULTS 980 consecutive individuals (51% F; 49% M) were enrolled. Adenoma and AN detection rates were 36.6% (F 29%: M 45%; P < 0.001) and 5.1% (F 3.8%; M 6.5%) respectively. On multivariate analysis, predictors of AN [OR (95%CI)] were age [1.036 (1.00-1.07); P = 0.048], BMI [overweight 2.21 (0.98-5.00); obese 3.54 (1.48-8.50); P = 0.018], smoking [< 40 pack-years 2.01 (1.01-4.01); ≥ 40 pack-years 3.96 (1.86-8.42); P = 0.002], and daily red meat consumption [2.02 (0.92-4.42) P = 0.079]. Nomograms of AN risk were developed in terms of risk factors and age separately for normal, overweight and obese individuals. The model had good discrimination and calibration. CONCLUSION The prevalence of adenoma and AN in average-risk Lebanese individuals is similar to the West. Age, smoking, and BMI are important predictors of AN, with obesity being particularly powerful. Though external validation is needed, this model provides an important platform for improved risk-stratification for screening programs in regions where universal screening is not currently employed.

Background & Aims Artificial intelligence-based computer-aided polyp detection (CADe) systems are intended to address the issue of missed polyps during colonoscopy. The effect of CADe during screening and surveillance colonoscopy has not previously been studied in a United States (U.S.) population. Methods We conducted a prospective, multi-center, single-blind randomized tandem colonoscopy study to evaluate a deep-learning based CADe system (EndoScreener, Shanghai Wision AI, China). Patients were enrolled across 4 U.S. academic medical centers from 2019 through 2020. Patients presenting for colorectal cancer screening or surveillance were randomized to CADe colonoscopy first or high-definition white light (HDWL) colonoscopy first, followed immediately by the other procedure in tandem fashion by the same endoscopist. The primary outcome was adenoma miss rate (AMR), and secondary outcomes included sessile serrated lesion (SSL) miss rate and adenomas per colonoscopy (APC). Results A total of 232 patients entered the study, with 116 patients randomized to the CADe colonoscopy first and 116 patients to HDWL colonoscopy first. After the exclusion of 9 patients, the study cohort included 223 patients. AMR was lower in the CADe-first group compared with the HDWL-first group (20.12% [34/169] vs 31.25% [45/144]; odds ratio [OR], 1.8048; 95% confidence interval [CI], 1.0780-3.0217; P = .0247). SSL miss rate was lower in the CADe-first group (7.14% [1/14]) vs the HDWL-first group (42.11% [8/19]; P = .0482). First-pass APC was higher in the CADe-first group (1.19 [standard deviation (SD), 2.03] vs 0.90 [SD, 1.55]; P = .0323). First-pass ADR was 50.44% in the CADe-first group and 43.64 % in the HDWL-first group (P = .3091). Conclusion In this U.S. multicenter tandem colonoscopy randomized controlled trial, we demonstrate a decrease in AMR and SSL miss rate and an increase in first-pass APC with the use of a CADe-system when compared with HDWL colonoscopy.

Colorectal cancer is the third most common cancer in the USA. Colonoscopy is considered the gold standard for colorectal cancer screening and can offer both diagnosis and therapy. The bowel preparation remains a significant barrier for patients who need to undergo colonoscopy and is often cited as the most dreaded aspect of the colonoscopy process. Inadequate bowel preparations still occur in 10–25% of colonoscopies, and this in turn can lead to increased procedural times, lower cecal intubation rates, and shorter interval between colonoscopies. From a quality standpoint, it is imperative that we do what we can to decrease the rate of inadequate bowel preparations. This review will focus on recent data regarding bowel preparation and offers a glimpse into what may be coming in the future. Recent advances in the field have been made to improve tolerability of bowel preparations and allow for more adequate colonoscopies. Newer, lower volume, flavored preparations, the use of adjuncts, and using split-dose preparations all can help with tolerability, compliance, and, in turn, preparation quality. Edible bowel preparations may become available in the near future. Early data on the use of artificial intelligence for assessment of preparation quality has been promising. Additionally, utilization of smartphone technology for education prior to the bowel preparation has also been shown to improve the adequacy of bowel preparations. Ongoing efforts to improve the tolerability and palatability of colonoscopy bowel preparations are important from a quality improvement standpoint to ensure the adequacy of colonoscopy. Incorporating patient-specific factors and comorbidities is also an essential aspect of improving the quality of bowel preparation. Leveraging technology to better communicate with and educate patients on the bowel preparation process is likely to play a larger role in the coming years.

Barrett’s esophagus (BE) is a premalignant condition that increases the risk of esophageal adenocarcinoma (EAC). Significantly more common in the Western world, risk factors include increased age, male sex, white race, gastro-esophageal reflux disease (GERD), central obesity, and cigarette smoking. The rates of progression to cancer depend on the grade of Barrett’s dysplasia. Screening for BE is recommended in patients with GERD and additional risk factors. Endoscopic surveillance of patients with BE likely improves overall outcomes. Advanced endoscopic imaging can help increase the efficiency of current endoscopic surveillance. Endoscopic therapy is safe and effective for the treatment of dysplastic BE and intramucosal EAC, but ongoing surveillance following treatment is necessary. This review will cover screening, surveillance, advanced imaging, chemoprevention, endoscopic treatment, and post-treatment surveillance of BE.

BACKGROUND: The proportions of patients with oesophageal adenocarcinoma (OAC) diagnosed by Barrett’s oesophagus surveillance or with preexisting Barrett’s oesophagus are unclear. AIM: A systematic review and meta-analysis to estimate the prevalence of prior and concurrent Barrett’s oesophagus diagnosis among patients with OAC or oesophagogastric junction adenocarcinomas (OGJAC). METHODS: We searched PubMed and Embase to identify studies published 1966–1/8/2020 that examined the prevalence of prior (≥6 months) or concurrent Barrett’s diagnosis (at cancer diagnosis) among OAC and OGJAC patients. Random effects models estimated overall and stratified pooled prevalence rates. RESULTS: A total of 69 studies, including 33,002 OAC patients (53 studies) and 2,712 with OGJAC (28 studies) were included. The pooled prevalence of prior Barrett’s oesophagus diagnosis in OAC was 11.8% (95% confidence interval [CI] 8.4–15.6%). The prevalence of prior Barrett’s oesophagus diagnosis was higher in single-center resection studies (16.0%, 95%CI 8.7–24.9%) than population-based cancer registry studies (8.4%, 95%CI 5.5–11.9%). The prevalence of concurrent Barrett’s oesophagus in OAC was 56.6% (95%CI 48.5–64.6%). Studies with 100% early stage OAC had higher prevalence of concurrent Barrett’s oesophagus (91.3%, 95%CI 82.4–97.6%) than studies with

Fiber-optic endomicroscopy is a minimally invasive tool to probe disease progression with subcellular resolution. In this Letter, we demonstrate a low-cost and compact fluorescence microendoscope capable of line-scanning confocal imaging by synchronizing a digital light projector with a CMOS camera. We present the digital aperture design to enable real-time confocal imaging, and we implement parallel illumination to improve the optical sectioning performance. Furthermore, we show that the confocal microendoscope can enhance visualization of disease-associated features when imaging highly scattering esophageal specimens.

Esophageal adenocarcinoma (EAC) is a growing problem with a rapidly rising incidence. Risk factors include gastroesophageal reflux disease, central obesity, and smoking. The prognosis of EAC remains poor because it is usually diagnosed late, and many efforts have been made to improve prevention, early detection, and treatment. Acid suppression, nonsteroidal antiinflammatory drugs (NSAIDs), and statins may play a role in chemoprevention. Screening for Barrett's esophagus (BE), the only known precursor lesion of EAC, is indicated for individuals with increased risk. Endoscopic surveillance of patients with BE likely improves overall outcomes. Endoscopic ablation and resection is highly effective for treating dysplastic BE and early EAC, whereas esophagectomy is indicated for patients with locally advanced disease. This review covers epidemiology, staging, screening, and prevention of EAC as well as endoscopic and surgical management.

Context Lymphangiomas are uncommon benign neoplasms that result from a blockage of the lymphatic system. Pancreatic cystic lymphangiomas are extremely rare. Pancreatic cystic lymphangiomas have been classically diagnosed on histopathologic examination following surgical excision, but recent reports have demonstrated successful diagnosis using endoscopic ultrasound with fine-needle aspiration (EUS-FNA). Data on the natural history of these lesions following drainage via EUS-FNA are lacking. We present a case of successful initial diagnosis and drainage of a pancreatic cystic lymphangioma using EUS-FNA, with unfortunate recurrence of the lesion four months later. Case report A 50-year-old female was evaluated for epigastric abdominal pain and nausea. CT scan revealed a 4 cm retroperitoneal cystic lesion. EUS-FNA was performed with complete drainage of the lesion using a 22-gauge needle. Twenty-five mL of chylous white fluid was obtained with laboratory analysis consistent with a pancreatic cystic lymphangioma. The patient was symptom-free for 4 months following drainage, but eventually had symptoms again with a CT scan confirming recurrence. Conclusions While EUS-FNA is effective for the diagnosis of pancreatic cystic lymphangiomas, its role in the management of these lesions is questionable. Temporary relief of symptoms can be achieved after EUS-guided drainage, but recurrence is a concern. Definitive cure likely requires complete surgical excision., JOP. Journal of the Pancreas, Vol 14, N° 3 (2013): May - p. 221-303