Gastrointestinal diseases impose a significant morbidity, mortality, and health care cost burden, affecting millions annually in the United States alone. Endoscopy plays a crucial role in managing these conditions. Despite technological advancements in endoscopy, ensuring efficient, high-quality care remains challenging. A critical need to standardize high-quality endoscopy is for education reform in the training of endoscopists. Traditional apprenticeship-based training methods are dependent on the trainer as well as the patient case mix. Simulation-based mastery learning (SBML) emerges as a promising strategy to improve endoscopy training. This review discusses the current state of SBML for optimizing upper endoscopy and colonoscopy efficiency.

Erythropoietin-induced hepatocyte receptor A2 (EphA2) is a receptor tyrosine kinase that plays a key role in the development and progression of a variety of tumors. This article reviews the expression of EphA2 in gastrointestinal (GI) colorectal cancer (CRC) and its regulation of pyroptosis. Pyroptosis is a form of programmed cell death that plays an important role in tumor suppression. Studies have shown that EphA2 regulates pyrodeath through various signaling pathways, affecting the occurrence, development and metastasis of GI CRC. The overexpression of EphA2 is closely related to the aggressiveness and metastasis of GI CRC, and the inhibition of EphA2 can induce pyrodeath and improve the sensitivity of cancer cells to treatment. In addition, EphA2 regulates intercellular communication and the microenvironment through interactions with other cytokines and receptors, further influencing cancer progression. The role of EphA2 in GI CRC and its underlying mechanisms provide us with new perspectives and potential therapeutic targets, which have important implications for future cancer treatment.

To date, no regional evidence of long-term colorectal cancer (CRC) risk reduction after endoscopic premalignant lesion removal has been established. We aimed to analyze this over a long-term follow-up evaluation.

This was a prospective cohort study of participants from the Japan Polyp Study conducted at 11 Japanese institutions. Participants underwent scheduled follow-up colonoscopies after a 2-round baseline colonoscopy process. The primary outcome was CRC incidence after randomization. The observed/expected ratio of CRC was calculated using data from the population-based Osaka Cancer Registry. Secondary outcomes were the incidence and characteristics of advanced neoplasia (AN).

A total of 1895 participants were analyzed. The mean number of follow-up colonoscopies and the median follow-up period were 2.8 years (range, 1-15 y) and 6.1 years (range, 0.8-11.9 y; 11,559.5 person-years), respectively. Overall, 4 patients (all males) developed CRCs during the study period. The observed/expected ratios for CRC in all participants, males, and females, were as follows: 0.14 (86% reduction), 0.18, and 0, respectively, and 77 ANs were detected in 71 patients (6.1 per 1000 person-years). Of the 77 ANs detected, 31 lesions (40.3%) were laterally spreading tumors, nongranular type. Nonpolypoid colorectal neoplasms (NP-CRNs), including flat (<10 mm), depressed, and laterally spreading, accounted for 59.7% of all detected ANs. Furthermore, 2 of the 4 CRCs corresponded to T1 NP-CRNs.

Endoscopic removal of premalignant lesions, including NP-CRNs, effectively reduced CRC risk. More than half of metachronous ANs removed by surveillance colonoscopy were NP-CRNs. The Japan Polyp Study: University Hospital Medical Information Network Clinical Trial Registry: University Hospital Medical Information Network Clinical Trial Registry, C000000058; cohort study: UMIN000040731.

Lack of visual recognition of colorectal polyps may lead to interval cancers. The mechanisms contributing to perceptual variation, particularly for subtle and advanced colorectal neoplasia, have scarcely been investigated. We aimed to evaluate visual recognition errors and provide novel mechanistic insights.

Eleven participants (seven trainees and four medical students) evaluated images from the UCL polyp perception dataset, containing 25 polyps, using eye-tracking equipment. Gaze errors were defined as those where the lesion was not observed according to eye-tracking technology. Cognitive errors occurred when lesions were observed but not recognized as polyps by participants. A video study was also performed including 39 subtle polyps, where polyp recognition performance was compared with a convolutional neural network.

Cognitive errors occurred more frequently than gaze errors overall (65.6%), with a significantly higher proportion in trainees (P = 0.0264). In the video validation, the convolutional neural network detected significantly more polyps than trainees and medical students, with per-polyp sensitivities of 79.5%, 30.0%, and 15.4%, respectively.

Cognitive errors were the most common reason for visual recognition errors. The impact of interventions such as artificial intelligence, particularly on different types of perceptual errors, needs further investigation including potential effects on learning curves. To facilitate future research, a publicly accessible visual perception colonoscopy polyp database was created.

Three subcategories of high-risk flat and depressed lesions (FDLs), laterally spreading tumors non-granular type (LST-NG), depressed lesions, and large sessile serrated lesions (SSLs), are highly attributable to post-colonoscopy colorectal cancer (CRC). Efficient and organized educational programs on detecting high-risk FDLs are lacking. We aimed to explore whether a web-based educational intervention with training on FIND clues (fold deformation, intensive stool/mucus attachment, no vessel visibility, and demarcated reddish area) may improve the ability to detect high-risk FDLs.

This was an international web-based randomized control trial that enrolled non-expert endoscopists in 13 Asian countries. The participants were randomized into either education or non-education group. All participants took the pre-test and post-test to read 60 endoscopic images (40 high-risk FDLs, five polypoid, 15 no lesions) and answered whether there was a lesion. Only the education group received a self-education program (video and training questions and answers) between the tests. The primary outcome was a detection rate of high-risk FDLs.

In total, 284 participants were randomized. After excluding non-responders, the final data analyses were based on 139 participants in the education group and 130 in the non-education group. The detection rate of high-risk FDLs in the education group significantly improved by 14.7% (66.6-81.3%) compared with -0.8% (70.8-70.0%) in the non-education group. Similarly, the detection rate of LST-NG, depressed lesions, and large SSLs significantly increased only in the education group by 12.7%, 12.0%, and 21.6%, respectively.

Short self-education focusing on detecting high-risk FDLs was effective for Asian non-expert endoscopists. (UMIN000042348).

Studies analyzing artificial intelligence (AI) in colonoscopies have reported improvements in detecting colorectal cancer (CRC) lesions, however its utility in the realworld remains limited. In this systematic review and meta-analysis, we evaluate the efficacy of AI-assisted colonoscopies against routine colonoscopy (RC).

We performed an extensive search of major databases (through January 2021) for randomized controlled trials (RCTs) reporting adenoma and polyp detection rates. Odds ratio (OR) and standardized mean differences (SMD) with 95% confidence intervals (CIs) were reported. Additionally, trial sequential analysis (TSA) was performed to guard against errors.

Six RCTs were included (4996 participants). The mean age (SD) was 51.99 (4.43) years, and 49% were females. Detection rates favored AI over RC for adenomas (OR 1.77; 95% CI: 1.570-2.08) and polyps (OR 1.91; 95% CI: 1.68-2.16). Secondary outcomes including mean number of adenomas (SMD 0.23; 95% CI: 0.18-0.29) and polyps (SMD 0.23; 95% CI: 0.17-0.29) detected per procedure favored AI. However, RC outperformed AI in detecting pedunculated polyps. Withdrawal times (WTs) favored AI when biopsies were included, while WTs without biopsies, cecal intubation times, and bowel preparation adequacy were similar.

Colonoscopies equipped with AI detection algorithms could significantly detect previously missed adenomas and polyps while retaining the ability to self-assess and improve periodically. More effective clearance of diminutive adenomas may allow lengthening in surveillance intervals, reducing the burden of surveillance colonoscopies, and increasing its accessibility to those at higher risk. TSA ruled out the risk for false-positive results and confirmed a sufficient sample size to detect the observed effect. Currently, these findings suggest that AI-assisted colonoscopy can serve as a useful proxy to address critical gaps in CRC identification.

Colonoscopy remains the standard strategy for screening for colorectal cancer around the world due to its efficacy in both detecting adenomatous or pre-cancerous lesions and the capacity to remove them intra-procedurally. Computer-aided detection and diagnosis (CAD), thanks to the brand new developed innovations of artificial intelligence, and especially deep-learning techniques, leads to a promising solution to human biases in performance by guarantying decision support during colonoscopy. The application of CAD on real-time colonoscopy helps increasing the adenoma detection rate, and therefore contributes to reduce the incidence of interval cancers improving the effectiveness of colonoscopy screening on critical outcome such as colorectal cancer related mortality. Furthermore, a significant reduction in costs is also expected. In addition, the assistance of the machine will lead to a reduction of the examination time and therefore an optimization of the endoscopic schedule. The aim of this opinion review is to analyze the clinical applications of CAD and artificial intelligence in colonoscopy, as it is reported in literature, addressing evidence, limitations, and future prospects.

Colorectal flat (nonpolypoid) lesions can be overlooked during colonoscopy. This study evaluated the efficacy of updated autofluorescence imaging (AFI) for detecting colorectal flat neoplasms.

This was a prospective, multicenter, randomized controlled trial in 9 Japanese tertiary institutions. Patients undergoing colonoscopy because of positive fecal immunochemical tests, surveillance after polypectomy, or investigation of minor symptoms were enrolled and randomly assigned to either the white-light imaging (WLI) or the AFI group. Primary outcome measurement was number of flat neoplasms per patient.

From November 2015 to June 2017, 817 patients were enrolled. After excluding 15 patients, 802 were finally analyzed (404, WLI; 398, AFI). Patients' backgrounds (sex, age, indication of colonoscopy, experience of endoscopists) and quality of colonoscopy (bowel preparation, sedative use, cecal insertion rate, insertion and withdrawal time) were not different between groups. Number of flat neoplasms in each patient was significantly higher in the AFI than in the WLI group (.87 [95% confidence interval [CI], .78-.97] vs .53 [95% CI, .46-.61]), whereas overall and polypoid neoplasm detection was not significantly different between the groups (1.33 [95% CI, 1.22-1.45] vs 1.14 [95% CI, 1.03-1.24], .46 [95% CI, .40-.53] vs .60 [95% CI, .53-.68]). Flat neoplasms were more frequently detected in the right-sided colon with AFI (.61 [95% CI, .54-.70] vs .30 [95% CI, .25-.36]) but not in the left-sided colon and rectum (.26 [95% CI, .21-.32] vs .23 [95% CI, .19-.28]).

Updated AFI improves the detection of flat colorectal neoplasms in the right-sided colon compared with WLI. (Clinical trial registration number: UMIN000019355.).

Computer-aided diagnosis offers a promising solution to reduce variation in colonoscopy performance. Pooled miss rates for polyps are as high as 22%, and associated interval colorectal cancers after colonoscopy are of concern. Optical biopsy, whereby in-vivo classification of polyps based on enhanced imaging replaces histopathology, has not been incorporated into routine practice because it is limited by interobserver variability and generally only meets accepted standards in expert settings. Real-time decision-support software has been developed to detect and characterise polyps, and also to offer feedback on the technical quality of inspection. Some of the current algorithms, particularly with recent advances in artificial intelligence techniques, match human expert performance for optical biopsy. In this Review, we summarise the evidence for clinical applications of computer-aided diagnosis and artificial intelligence in colonoscopy.

Nonpolypoid colorectal neoplasms (NP-CRNs) are more likely to contain high-grade dysplasia or early-stage cancer than polypoid neoplasms. We aimed to determine the long-term outcomes of patients with at least 1 NP-CRN.

We performed a longitudinal cohort study of 4454 patients at a Veterans' Affairs hospital who underwent colonoscopy from 2000 through 2005; 341 were found to have 1 or more NP-CRNs and were matched (3:1) with patients found to have 1 or more polypoid neoplasms (controls, n = 1025). We collected and analyzed data on baseline colonoscopy findings and first follow-up colonoscopy results through August 2014. We calculated the incidence of advanced neoplasia at first follow-up colonoscopy, as defined by the presence of ≥1 tubular or sessile serrated adenomas ≥10 mm in diameter, tubulovillous adenoma, high-grade dysplasia, or invasive cancer.

A significantly higher proportion of patients with 1 or more NP-CRNs (16.0%) were found to have advanced neoplasia at their first follow-up colonoscopy than controls (8.6%); the adjusted risk ratio was 1.6 (95% confidence interval, 1.05-2.6; P = .03). A significantly higher proportion of patients with 1 or more NP-CRNs were found to have additional NP-CRNs at the follow-up colonoscopy (17%) than controls (7%; relative risk, 2.3; 95% confidence interval, 1.5-3.5; P < .001). Similar proportions of patients in each group developed cancers after colonoscopy.

In a longitudinal cohort study, we found that patients with NP-CRN were more likely to develop additional NP-CRNs and to have advanced neoplasms at their first follow-up colonoscopy than patients with only polypoid neoplasms. However, patients with NP-CRN were not more likely to develop cancers after colonoscopy when surveillance guidelines were followed. Larger studies are needed to determine risk of colorectal cancer in patients with NP-CRN.

Optical diagnosis is an emerging paradigm in Western endoscopic practice for the colonoscopic management of diminutive polyps, and includes two complementary clinical strategies: 'resect and discard', in which diminutive high-confidence adenomas are identified, and then removed and discarded without pathological assessment; and 'diagnose and leave', where diminutive high-confidence hyperplastic polyps are identified in the rectosigmoid and then left without resection or biopsy. Like other aspects of colonoscopy performance, adoption of optical diagnosis in Western practice is limited by operator dependency and variation in clinical effectiveness. There is substantial potential for optical diagnosis of colorectal neoplasia during colonoscopy to alleviate the rising costs of health care in the West. However, operator dependence in diagnostic performance together with critical system factors such as informed consent, credentialing, medical legal support and reimbursement incentives must be overcome before optical diagnosis of diminutive lesions is considered for widespread adoption in Western clinical practice.

To describe interval cancers (IC) and the sensitivity of colorectal cancer (CRC) screening programmes.

A systematic review of the literature was conducted through a MEDLINE (PubMed) search. The search strategy combined the terms 'interval cancer', 'false negative', 'mass screening', 'screening' 'early detection of cancer', 'colorectal cancer' and 'bowel cancer'. Inclusion criteria consisted of population-based screening programmes, original articles written in English or Spanish and publication dates between 1999/01/01 and 2015/02/28. A narrative synthesis of the included articles was performed detailing the characteristics of the screening programmes, the IC rate, and the information sources used in each study.

Thirteen articles were included. The episode sensitivity of CRC screening programmes ranged from 42.2% to 65.3% in programmes using the guaiac test and between 59.1% and 87.0% with the immunochemical test. We found a higher proportion of women who were diagnosed with IC and these lesions were mainly located in the proximal colon.

There is wide variability in the IC rate in CRC programmes. To ensure comparability between programmes, there is a need for consensus on the working definition of IC and the methods used for their identification and quantification.