Effect of Colonoscopy Screening on Risks of Colorectal Cancer and Related Death.

BACKGROUND: Although colonoscopy is widely used as a screening test to detect colorectal cancer, its effect on the risks of colorectal cancer and related death is unclear. METHODS: We performed a pragmatic, randomized trial involving presumptively healthy men and women 55 to 64 years of age drawn from population registries in Poland, Norway, Sweden, and the Netherlands between 2009 and 2014. The participants were randomly assigned in a 1:2 ratio either to receive an invitation to undergo a single screening colonoscopy (the invited group) or to receive no invitation or screening (the usual-care group). The primary end points were the risks of colorectal cancer and related death, and the secondary end point was death from any cause. RESULTS: Follow-up data were available for 84,585 participants in Poland, Norway, and Sweden - 28,220 in the invited group, 11,843 of whom (42.0%) underwent screening, and 56,365 in the usual-care group. A total of 15 participants had major bleeding after polyp removal. No perforations or screening-related deaths occurred within 30 days after colonoscopy. During a median follow-up of 10 years, 259 cases of colorectal cancer were diagnosed in the invited group as compared with 622 cases in the usual-care group. In intention-to-screen analyses, the risk of colorectal cancer at 10 years was 0.98% in the invited group and 1.20% in the usual-care group, a risk reduction of 18% (risk ratio, 0.82; 95% confidence interval [CI], 0.70 to 0.93). The risk of death from colorectal cancer was 0.28% in the invited group and 0.31% in the usual-care group (risk ratio, 0.90; 95% CI, 0.64 to 1.16). The number needed to invite to undergo screening to prevent one case of colorectal cancer was 455 (95% CI, 270 to 1429). The risk of death from any cause was 11.03% in the invited group and 11.04% in the usual-care group (risk ratio, 0.99; 95% CI, 0.96 to 1.04). CONCLUSIONS: In this randomized trial, the risk of colorectal cancer at 10 years was lower among participants who were invited to undergo screening colonoscopy than among those who were assigned to no screening. (Funded by the Research Council of Norway and others; NordICC ClinicalTrials.gov number, NCT00883792.).

Autonomous Artificial Intelligence vs Artificial Intelligence-Assisted Human Optical Diagnosis of Colorectal Polyps: A Randomized Controlled Trial.

BACKGROUND & AIMS: Artificial intelligence (AI)-based optical diagnosis systems (CADx) have been developed to allow pathology prediction of colorectal polyps during colonoscopies. However, CADx systems have not yet been validated for autonomous performance. Therefore, we conducted a trial comparing autonomous AI to AI-assisted human (AI-H) optical diagnosis. METHODS: We performed a randomized noninferiority trial of patients undergoing elective colonoscopies at 1 academic institution. Patients were randomized into (1) autonomous AI-based CADx optical diagnosis of diminutive polyps without human input or (2) diagnosis by endoscopists who performed optical diagnosis of diminutive polyps after seeing the real-time CADx diagnosis. The primary outcome was accuracy in optical diagnosis in both arms using pathology as the gold standard. Secondary outcomes included agreement with pathology for surveillance intervals. RESULTS: A total of 467 patients were randomized (238 patients/158 polyps in the autonomous AI group and 229 patients/179 polyps in the AI-H group). Accuracy for optical diagnosis was 77.2% (95% confidence interval [CI], 69.7-84.7) in the autonomous AI group and 72.1% (95% CI, 65.5-78.6) in the AI-H group (P = .86). For high-confidence diagnoses, accuracy for optical diagnosis was 77.2% (95% CI, 69.7-84.7) in the autonomous AI group and 75.5% (95% CI, 67.9-82.0) in the AI-H group. Autonomous AI had statistically significantly higher agreement with pathology-based surveillance intervals compared to AI-H (91.5% [95% CI, 86.9-96.1] vs 82.1% [95% CI, 76.5-87.7]; P = .016). CONCLUSIONS: Autonomous AI-based optical diagnosis exhibits noninferior accuracy to endoscopist-based diagnosis. Both autonomous AI and AI-H exhibited relatively low accuracy for optical diagnosis; however, autonomous AI achieved higher agreement with pathology-based surveillance intervals. (ClinicalTrials.gov, Number NCT05236790).

Texture and Color Enhancement Imaging Improves Colonic Adenoma Detection: A Multicenter Randomized Controlled Trial.

The global burden of colorectal cancer is expected to increase more than 60% by 2030; however, compelling evidence now shows that the implementation of population screening programs in developed countries has led to a substantial reduction in incidence and mortality.1,2 Despite this, patients continue to develop preventable colorectal cancers, in part because of high rates of interval colon cancer diagnosed after screening or surveillance colonoscopies.3.

Colon Polyp Surveillance: Separating the Wheat From the Chaff.

One goal of colorectal cancer (CRC) screening is to prevent CRC incidence by removing precancerous colonic polyps, which are detected in up to 50% of screening examinations. Yet, the lifetime risk of CRC is 3.9%-4.3%, so it is clear that most of these individuals with polyps would not develop CRC in their lifetime. It is, therefore, a challenge to determine which individuals with polyps will benefit from follow-up, and at what intervals. There is some evidence that individuals with advanced polyps, based on size and histology, benefit from intensive surveillance. However, a large proportion of individuals will have small polyps without advanced histologic features (ie, "nonadvanced"), where the benefits of surveillance are uncertain and controversial. Demand for surveillance will further increase as more polyps are detected due to increased screening uptake, recent United States recommendations to expand screening to younger individuals, and emergence of polyp detection technology. We review the current understanding and clinical implications of the natural history, biology, and outcomes associated with various categories of colon polyps based on size, histology, and number. Our aims are to highlight key knowledge gaps, specifically focusing on certain categories of polyps that may not be associated with future CRC risk, and to provide insights to inform research priorities and potential management strategies. Optimization of CRC prevention programs based on updated knowledge about the future risks associated with various colon polyps is essential to ensure cost-effective screening and surveillance, wise use of resources, and inform efforts to personalize recommendations.

AGA Clinical Practice Update on the Role of Artificial Intelligence in Colon Polyp Diagnosis and Management: Commentary.

DESCRIPTION: The purpose of this American Gastroenterological Association (AGA) Institute Clinical Practice Update (CPU) is to review the available evidence and provide expert commentary on the current landscape of artificial intelligence in the evaluation and management of colorectal polyps. METHODS: This CPU 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 Gastroenterology. This Expert Commentary incorporates important as well as recently published studies in this field, and it reflects the experiences of the authors who are experienced endoscopists with expertise in the field of artificial intelligence and colorectal polyps.

Nationally Automated Colonoscopy Performance Feedback Increases Polyp Detection: The NED APRIQOT Randomized Controlled Trial.

BACKGROUND & AIMS: Postcolonoscopy colorectal cancer incidence and mortality rates are higher for endoscopists with low polyp detection rates. Using the UK's National Endoscopy Database (NED), which automatically captures real-time data, we assessed if providing feedback of case-mix-adjusted mean number of polyps (aMNP), as a key performance indicator, improved endoscopists' performance. Feedback was delivered via a theory-informed, evidence-based audit and feedback intervention. METHODS: This multicenter, prospective, NED Automated Performance Reports to Improve Quality Outcomes Trial randomized National Health Service endoscopy centers to intervention or control. Intervention-arm endoscopists were e-mailed tailored monthly reports automatically generated within NED, informed by qualitative interviews and behavior change theory. The primary outcome was endoscopists' aMNP during the 9-month intervention. RESULTS: From November 2020 to July 2021, 541 endoscopists across 36 centers (19 intervention; 17 control) performed 54,770 procedures during the intervention, and 15,960 procedures during the 3-month postintervention period. Comparing the intervention arm with the control arm, endoscopists during the intervention period: aMNP was nonsignificantly higher (7%; 95% CI, -1% to 14%; P = .08). The unadjusted MNP (10%; 95% CI, 1%-20%) and polyp detection rate (10%; 95% CI, 4%-16%) were significantly higher. Differences were not maintained in the postintervention period. In the intervention arm, endoscopists accessing NED Automated Performance Reports to Improve Quality Outcomes Trial webpages had a higher aMNP than those who did not (aMNP, 118 vs 102; P = .03). CONCLUSIONS: Although our automated feedback intervention did not increase aMNP significantly in the intervention period, MNP and polyp detection rate did improve significantly. Engaged endoscopists benefited most and improvements were not maintained postintervention; future work should address engagement in feedback and consider the effectiveness of continuous feedback. CLINICAL TRIALS REGISTRY:  www.isrctn.org ISRCTN11126923 .

AGA Clinical Practice Update on Appropriate and Tailored Polypectomy: Expert Review.

DESCRIPTION: In this Clinical Practice Update (CPU), we provide guidance on the appropriate use of different polypectomy techniques. We focus on polyps <2 cm in size that are most commonly encountered by the practicing endoscopist, including use of classification systems to characterize polyps and various polypectomy methods. We review characteristics of polyps that require complex polypectomy techniques and provide guidance on which types of polyps require more advanced management by a therapeutic endoscopist or surgeon. This CPU does not provide a detailed review of complex polypectomy techniques, such as endoscopic submucosal dissection, which should only be performed by endoscopists with advanced training. METHODS: This expert review was commissioned and approved by the American Gastroenterological Association (AGA) Institute CPU Committee 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 CPU Committee and external peer review through standard procedures of Clinical Gastroenterology and Hepatology. These Best Practice Advice statements were drawn from a review of the published literature and from expert opinion. Because systematic reviews were not performed, these Best Practice Advice statements do not carry formal ratings regarding the quality of evidence or strength of the presented considerations. BEST PRACTICE ADVICE 1: A structured visual assessment using high-definition white light and/or electronic chromoendoscopy and with photodocumentation should be conducted for all polyps found during routine colonoscopy. Closely inspect colorectal polyps for features of submucosally invasive cancer. BEST PRACTICE ADVICE 2: Use cold snare polypectomy for polyps <10 mm in size. Cold forceps polypectomy can alternatively be used for 1- to 3-mm polyps where cold snare polypectomy is technically difficult. BEST PRACTICE ADVICE 3: Do not use hot forceps polypectomy. BEST PRACTICE ADVICE 4: Clinicians should be familiar with various techniques, such as cold and hot snare polypectomy and endoscopic mucosal resection, to ensure effective, safe, and optimal resection of intermediate-size polyps (10-19 mm). BEST PRACTICE ADVICE 5: Consider using lifting agents or underwater endoscopic mucosal resection for removal of sessile polyps 10-19 mm in size. BEST PRACTICE ADVICE 6: Serrated polyps should be resected using cold resection techniques. Submucosal injection may be helpful for polyps >10 mm if margins cannot be well delineated. BEST PRACTICE ADVICE 7: Use hot snare polypectomy to remove pedunculated lesions >10 mm in size. BEST PRACTICE ADVICE 8: Do not routinely use clips to close resection sites for polyps <20 mm. BEST PRACTICE ADVICE 9: Refer patients with polyps to endoscopic referral centers in the context of size ≥20 mm, challenging polypectomy location, or recurrent polyp at a prior polypectomy site. BEST PRACTICE ADVICE 10: Tattoo lesions that may need future localization at endoscopy or surgery. Tattoos should be placed in a location that will not interfere with subsequent attempts at endoscopic resection. BEST PRACTICE ADVICE 11: Refer patients with nonpedunculated polyps with clear evidence of submucosally invasive cancer for surgical evaluation. BEST PRACTICE ADVICE 12: Understand the endoscopy suite's electrosurgical generator settings appropriate for polypectomy or postpolypectomy thermal techniques.

Effect of Real-Time Computer-Aided Polyp Detection System (ENDO-AID) on Adenoma Detection in Endoscopists-in-Training: A Randomized Trial.

BACKGROUND: The effect of computer-aided polyp detection (CADe) on adenoma detection rate (ADR) among endoscopists-in-training remains unknown. METHODS: We performed a single-blind, parallel-group, randomized controlled trial in Hong Kong between April 2021 and July 2022 (NCT04838951). Eligible subjects undergoing screening/surveillance/diagnostic colonoscopies were randomized 1:1 to receive colonoscopies with CADe (ENDO-AID[OIP-1]) or not (control) during withdrawal. Procedures were performed by endoscopists-in-training with <500 procedures and <3 years' experience. Randomization was stratified by patient age, sex, and endoscopist experience (beginner vs intermediate level, <200 vs 200-500 procedures). Image enhancement and distal attachment devices were disallowed. Subjects with incomplete colonoscopies or inadequate bowel preparation were excluded. Treatment allocation was blinded to outcome assessors. The primary outcome was ADR. Secondary outcomes were ADR for different adenoma sizes and locations, mean number of adenomas, and non-neoplastic resection rate. RESULTS: A total of 386 and 380 subjects were randomized to CADe and control groups, respectively. The overall ADR was significantly higher in the CADe group than in the control group (57.5% vs 44.5%; adjusted relative risk, 1.41; 95% CI, 1.17-1.72; P < .001). The ADRs for <5 mm (40.4% vs 25.0%) and 5- to 10-mm adenomas (36.8% vs 29.2%) were higher in the CADe group. The ADRs were higher in the CADe group in both the right colon (42.0% vs 30.8%) and left colon (34.5% vs 27.6%), but there was no significant difference in advanced ADR. The ADRs were higher in the CADe group among beginner (60.0% vs 41.9%) and intermediate-level (56.5% vs 45.5%) endoscopists. Mean number of adenomas (1.48 vs 0.86) and non-neoplastic resection rate (52.1% vs 35.0%) were higher in the CADe group. CONCLUSIONS: Among endoscopists-in-training, the use of CADe during colonoscopies was associated with increased overall ADR. (ClinicalTrials.gov, Number: NCT04838951).

Using Computer-aided Optical Diagnosis and Expert Review to Evaluate Colorectal Polyps Diagnosed as Normal Mucosa in Pathology.

Pathological assessment of colorectal polyps is considered the current reference standard for histologic diagnosis. About 10% of polyps sent to the pathology lab are returned with the diagnosis of mucosal folds, mucosal prolapse, or normal mucosa.1,2 Two recent publications have indicated that disagreements between endoscopic optical diagnosis and the subsequent pathological diagnoses might be due to misdiagnosis in pathology.3,4 We were therefore interested in re-evaluating pathology-based diagnosis of "mucosal polyps" using expert endoscopists and computer-assisted diagnosis (CADx) evaluation.

Impact of Bowel Preparation Quality on Colonoscopy Findings and Colorectal Cancer Deaths in a Nation-Wide Colorectal Cancer Screening Program.

INTRODUCTION: Adequate bowel preparation is paramount for a high-quality screening colonoscopy. Despite the importance of adequate bowel preparation, there is a lack of large studies that associated the degree of bowel preparation with long-term colorectal cancer outcomes in screening patients. METHODS: In a large population-based screening program database in Austria, quality of bowel preparation was estimated according to the Aronchick Scale by the endoscopist (excellent, good, fair, poor, and inadequate bowel preparation). We used logistic regression to assess the influence of bowel preparation on the detection of different polyp types and the interphysician variation in bowel preparation scoring. Time-to-event analyses were performed to investigate the association of bowel preparation with postcolonoscopy colorectal cancer (PCCRC) death. RESULTS: A total of 335,466 colonoscopies between January 2012 and follow-up until December 2022 were eligible for the analyses. As compared with excellent bowel preparation, adenoma detection was not significantly lower for good bowel preparation (odds ratio 1.01, 95% confidence interval [CI] 0.9971-1.0329, P = 0.1023); however, adenoma detection was significantly lower in fair bowel preparation (odds ratio 0.97, 95% CI 0.9408-0.9939, P = 0.0166). Individuals who had fair or lower bowel preparation at screening colonoscopy had significantly higher hazards for PCCRC death (hazard ratio for fair bowel preparation 2.56, 95% CI 1.67-3.94, P < 0.001). DISCUSSION: Fair bowel preparation on the Aronchick Scale was not only associated with a lower adenoma detection probability but also with increased risk of PCCRC death. Efforts should be made to increase bowel cleansing above fair scores.

Predicting Risk of Colorectal Cancer After Adenoma Removal in a Large Community-Based Setting.

INTRODUCTION: Colonoscopy surveillance guidelines categorize individuals as high or low risk for future colorectal cancer (CRC) based primarily on their prior polyp characteristics, but this approach is imprecise, and consideration of other risk factors may improve postpolypectomy risk stratification. METHODS: Among patients who underwent a baseline colonoscopy with removal of a conventional adenoma in 2004-2016, we compared the performance for postpolypectomy CRC risk prediction (through 2020) of a comprehensive model featuring patient age, diabetes diagnosis, and baseline colonoscopy indication and prior polyp findings (i.e., adenoma with advanced histology, polyp size ≥10 mm, and sessile serrated adenoma or traditional serrated adenoma) with a polyp model featuring only polyp findings. Models were developed using Cox regression. Performance was assessed using area under the receiver operating characteristic curve (AUC) and calibration by the Hosmer-Lemeshow goodness-of-fit test. RESULTS: Among 95,001 patients randomly divided 70:30 into model development (n = 66,500) and internal validation cohorts (n = 28,501), 495 CRC were subsequently diagnosed; 354 in the development cohort and 141 in the validation cohort. Models demonstrated adequate calibration, and the comprehensive model demonstrated superior predictive performance to the polyp model in the development cohort (AUC 0.71, 95% confidence interval [CI] 0.68-0.74 vs AUC 0.61, 95% CI 0.58-0.64, respectively) and validation cohort (AUC 0.70, 95% CI 0.65-0.75 vs AUC 0.62, 95% CI 0.57-0.67, respectively). DISCUSSION: A comprehensive CRC risk prediction model featuring patient age, diabetes diagnosis, and baseline colonoscopy indication and polyp findings was more accurate at predicting postpolypectomy CRC diagnosis than a model based on polyp findings alone.

Adenomas and Sessile Serrated Lesions in 45- to 49-Year-Old Individuals Undergoing Colonoscopy: A Systematic Review and Meta-Analysis.

INTRODUCTION: Colorectal cancer (CRC) screening is now recommended at the age of 45 years in the United States. However, information regarding the adenomas detection rate (ADR) and sessile serrated lesions (SSLs) in 45- to 49-year-old individuals is limited. In addition, the impact of lowering the screening age to 45 years on the ADR and the detection rate of SSLs is not well elucidated. This systematic review and meta-analysis aims to report the overall ADR and SSL detection rate in 45- to 49-year-old individuals undergoing colonoscopy. METHODS: We searched MEDLINE, EMBASE, SCOPUS, Web of Science, ClinicalTrials.gov , and the Cochrane database from inception through October 2022 to identify studies reporting on ADR and SSL detection rates in 45- to 49-year-old individuals undergoing colonoscopies for all indications. This approach acknowledges the possibility of including individuals undergoing diagnostic colonoscopies or those with increased risk factors for CRC. We also conducted a separate analysis examining ADR in average-risk individuals undergoing screening colonoscopy. The pooled rates with their corresponding 95% confidence intervals (CIs) were generated using the fixed-effects model. I2 was used to adjudicate heterogeneity. RESULTS: Sixteen studies met the inclusion criteria. All studies were retrospective except one; 3 had data from national/local registries. There were 41,709 adenomas detected across 150,436 colonoscopies. The pooled overall ADR was 23.1% (95% CI 19.7%-27.0%, I2 = 98.6%). The pooled ADR in individuals with average risk of CRC from 7 studies was 28.2% (95% CI 24.6%-32.0%, I2 = 96.5%). The pooled overall SSL detection rate from 6 studies was 6.3% (95% CI 3.8%-10.5%, I2 = 97%). The included studies were heterogeneous because of differences in the inclusion and exclusion criteria and patient population. DISCUSSION: In 45- to 49-year-old individuals undergoing a colonoscopy for any indication, the ADR and SSL detection rates were 23.1% and 6.3%, respectively. We conclude that these outcomes in 45- to 49-year-olds are comparable with individuals aged 50-54 years.

Use of a Novel Artificial Intelligence System Leads to the Detection of Significantly Higher Number of Adenomas During Screening and Surveillance Colonoscopy: Results From a Large, Prospective, US Multicenter, Randomized Clinical Trial.

INTRODUCTION: Adenoma per colonoscopy (APC) has recently been proposed as a quality measure for colonoscopy. We evaluated the impact of a novel artificial intelligence (AI) system, compared with standard high-definition colonoscopy, for APC measurement. METHODS: This was a US-based, multicenter, prospective randomized trial examining a novel AI detection system (EW10-EC02) that enables a real-time colorectal polyp detection enabled with the colonoscope (CAD-EYE). Eligible average-risk subjects (45 years or older) undergoing screening or surveillance colonoscopy were randomized to undergo either CAD-EYE-assisted colonoscopy (CAC) or conventional colonoscopy (CC). Modified intention-to-treat analysis was performed for all patients who completed colonoscopy with the primary outcome of APC. Secondary outcomes included positive predictive value (total number of adenomas divided by total polyps removed) and adenoma detection rate. RESULTS: In modified intention-to-treat analysis, of 1,031 subjects (age: 59.1 ± 9.8 years; 49.9% male), 510 underwent CAC vs 523 underwent CC with no significant differences in age, gender, ethnicity, or colonoscopy indication between the 2 groups. CAC led to a significantly higher APC compared with CC: 0.99 ± 1.6 vs 0.85 ± 1.5, P = 0.02, incidence rate ratio 1.17 (1.03-1.33, P = 0.02) with no significant difference in the withdrawal time: 11.28 ± 4.59 minutes vs 10.8 ± 4.81 minutes; P = 0.11 between the 2 groups. Difference in positive predictive value of a polyp being an adenoma among CAC and CC was less than 10% threshold established: 48.6% vs 54%, 95% CI -9.56% to -1.48%. There were no significant differences in adenoma detection rate (46.9% vs 42.8%), advanced adenoma (6.5% vs 6.3%), sessile serrated lesion detection rate (12.9% vs 10.1%), and polyp detection rate (63.9% vs 59.3%) between the 2 groups. There was a higher polyp per colonoscopy with CAC compared with CC: 1.68 ± 2.1 vs 1.33 ± 1.8 (incidence rate ratio 1.27; 1.15-1.4; P < 0.01). DISCUSSION: Use of a novel AI detection system showed to a significantly higher number of adenomas per colonoscopy compared with conventional high-definition colonoscopy without any increase in colonoscopy withdrawal time, thus supporting the use of AI-assisted colonoscopy to improve colonoscopy quality ( ClinicalTrials.gov NCT04979962).

Endocuff With or Without Artificial Intelligence-Assisted Colonoscopy in Detection of Colorectal Adenoma: A Randomized Colonoscopy Trial.

INTRODUCTION: Both artificial intelligence (AI) and distal attachment devices have been shown to improve adenoma detection rate and reduce miss rate during colonoscopy. We studied the combined effect of Endocuff and AI on enhancing detection rates of various colonic lesions. METHODS: This was a 3-arm prospective randomized colonoscopy study involving patients aged 40 years or older. Participants were randomly assigned in a 1:1:1 ratio to undergo Endocuff with AI, AI alone, or standard high-definition (HD) colonoscopy. The primary outcome was adenoma detection rate (ADR) between the Endocuff-AI and AI groups while secondary outcomes included detection rates of polyp (PDR), sessile serrated lesion (sessile detection rate [SDR]), and advanced adenoma (advanced adenoma detection rate) between the 2 groups. RESULTS: A total of 682 patients were included (mean age 65.4 years, 52.3% male), with 53.7% undergoing diagnostic colonoscopy. The ADR for the Endocuff-AI, AI, and HD groups was 58.7%, 53.8%, and 46.3%, respectively, while the corresponding PDR was 77.0%, 74.0%, and 61.2%. A significant increase in ADR, PDR, and SDR was observed between the Endocuff-AI and AI groups (ADR difference: 4.9%, 95% CI: 1.4%-8.2%, P = 0.03; PDR difference: 3.0%, 95% CI: 0.4%-5.8%, P = 0.04; SDR difference: 6.4%, 95% CI: 3.4%-9.7%, P < 0.01). Both Endocuff-AI and AI groups had a higher ADR, PDR, SDR, and advanced adenoma detection rate than the HD group (all P < 0.01). DISCUSSION: Endocuff in combination with AI further improves various colonic lesion detection rates when compared with AI alone.

Colon polyps: updates in classification and management.

PURPOSE OF REVIEW: Colon polyps are potential precursors to colorectal cancer (CRC), which remains one of the most common causes of cancer-associated death. The proper identification and management of these colorectal polyps is an important quality measure for colonoscopy outcomes. Here, we review colon polyp epidemiology, their natural history, and updates in endoscopic classification and management. RECENT FINDINGS: Colon polyps that form from not only the adenoma, but also the serrated polyp pathway have significant risk for future progression to CRC. Therefore, correct identification and management of sessile serrated lesions can improve the quality of screening colonoscopy. Malignant polyp recognition continues to be heavily reliant on well established endoscopic classification systems and plays an important role in intraprocedural management decisions. Hot snare remains the gold standard for pedunculated polyp resection. Nonpedunculated noninvasive lesions can be effectively removed by large forceps if diminutive, but cold snare is preferred for colon polyps 3-20 mm in diameter. Larger lesions at least 20 mm require endoscopic mucosal resection. Polyps with the endoscopic appearance of submucosal invasion require surgical referral or advanced endoscopic resection in select cases. Advances in artificial intelligence may revolutionize endoscopic polyp classification and improve both patient and cost-related outcomes of colonoscopy. SUMMARY: Clinicians should be aware of the most recent updates in colon polyp classification and management to provide the best care to their patients initiating screening colonoscopy.

The 2023 top 10 list of endoscopy topics in medical publishing: an annual review by the American Society for Gastrointestinal Endoscopy Editorial Board.

Using a systematic literature search of original articles published during 2023 in Gastrointestinal Endoscopy (GIE) and other high-impact medical and gastroenterology journals, the GIE Editorial Board of the American Society for Gastrointestinal Endoscopy compiled a list of the top 10 most significant topic areas in general and advanced GI endoscopy during the year. Each GIE Editorial Board member was directed to consider 3 criteria in generating candidate topics-significance, novelty, and impact on global clinical practice-and subject matter consensus was facilitated by the Chair through electronic voting and a meeting of the entire GIE Editorial Board. The 10 identified areas collectively represent advances in the following endoscopic spheres: GI bleeding, endohepatology, endoscopic palliation, artificial intelligence and polyp detection, artificial intelligence beyond the colon, better polypectomy and EMR, how to make endoscopy units greener, high-quality upper endoscopy, endoscopic tissue apposition and closure devices, and endoscopic submucosal dissection. Each board member was assigned a topic area around which to summarize relevant important articles, thereby generating this overview of the "top 10" endoscopic advances of 2023.

Artificial intelligence-assisted real-time monitoring of effective withdrawal time during colonoscopy: a novel quality marker of colonoscopy.

BACKGROUND AND AIMS: The importance of withdrawal time during colonoscopy cannot be overstated in mitigating the risk of missed lesions and postcolonoscopy colorectal cancer. We evaluated a novel colonoscopy quality metric called the effective withdrawal time (EWT), which is an artificial intelligence (AI)-derived quantitative measure of quality withdrawal time, and its association with various colonic lesion detection rates as compared with standard withdrawal time (SWT). METHODS: Three hundred fifty video recordings of colonoscopy withdrawal (from the cecum to the anus) were assessed by the new AI model. The primary outcome was adenoma detection rate (ADR) according to different quintiles of EWT. Multivariate logistic regression, adjusting for baseline covariates, was used to determine the adjusted odd ratios (ORs) for EWT on lesion detection rates, with the lowest quintile as reference. The area under the receiver-operating characteristic curve of EWT was compared with SWT. RESULTS: The crude ADR in different quintiles of EWT, from lowest to highest, was 10.0%, 31.4%, 33.3%, 53.5%, and 85.7%. The ORs of detecting adenomas and polyps were significantly higher in all top 4 quintiles when compared with the lowest quintile. Each minute increase in EWT was associated with a 49% increase in ADR (aOR, 1.49; 95% confidence interval [CI], 1.36-1.65). The area under the receiver-operating characteristic curve of EWT was also significantly higher than SWT on adenoma detection (.80 [95% CI, .75-.84] vs .70 [95% CI, .64-.74], P < .01). CONCLUSIONS: AI-derived monitoring of EWT is a promising novel quality indicator for colonoscopy, which is more associated with ADR than SWT.

Validation of artificial intelligence-based bowel preparation assessment in screening colonoscopy (with video).

BACKGROUND AND AIMS: Accurate bowel preparation assessment is essential for determining colonoscopy screening intervals. Patients with suboptimal bowel preparation are at a high risk of missing >5 mm adenomas and should undergo an early repeat colonoscopy. In this study, we used artificial intelligence (AI) to evaluate bowel preparation and validated the ability of the system to accurately identify patients who are at high risk of having >5 mm adenomas missed due to inadequate bowel preparation. METHODS: This prospective, single-center, observational study was conducted at the Eighth Affiliated Hospital, Sun Yat-sen University, from October 8, 2021, to November 9, 2022. Eligible patients who underwent screening colonoscopy were consecutively enrolled. The AI assessed bowel preparation using the e-Boston Bowel Preparation Scale (e-BBPS) while endoscopists made evaluations using BBPS. If both BBPS and e-BBPS deemed preparation adequate, the patient immediately underwent a second colonoscopy; otherwise, the patient underwent bowel re-cleansing before the second colonoscopy. RESULTS: Among the 393 patients, 72 adenomas >5 mm in size were detected; 27 adenomas >5 mm in size were missed. In unqualified-AI patients, the >5 mm adenoma miss rate (AMR) was significantly higher than in qualified-AI patients (35.71% vs 13.19% [P = .0056]; odds ratio [OR], .2734 [95% CI, .1139-.6565]), as were the AMR (50.89% vs 20.79% [P < .001]; OR, .2532 [95% CI, .1583-.4052]) and >5 mm polyp miss rate (35.82% vs 19.48% [P = .0152]; OR, .4335 [95% CI, .2288-.8213]). CONCLUSIONS: This study confirmed that patients classified as inadequate by AI exhibited an unacceptable >5 mm AMR, providing key evidence for implementing AI in guiding bowel re-cleansing and potentially standardizing future colonoscopy screening. (Clinical trial registration number: NCT05145712.).

Differences between men and women with respect to colorectal cancer mortality despite screening colonoscopy.

BACKGROUND AND AIMS: Women aged 55 to 59 years have a similar prevalence rate and number needed to screen for colorectal adenomas as men at a 10-year younger age. The aim of this study was to determine sex-specific differences in colorectal cancer mortality and estimate the association with adenomas at screening colonoscopy. METHODS: This retrospective study analyzed 323,139 individuals who underwent colonoscopy within a national colorectal cancer screening program in Austria between January 2007 and December 2020. RESULTS: Median patient age was 60 years (interquartile range, 54-67), and the sex distribution in all age groups was nearly identical. Men had significantly higher odds of having an adenoma or serrated polyp, low-risk polyp, high-risk polyp, or colorectal cancer detected at colonoscopy than women (odds ratio [OR] 1.83; 95% confidence interval [CI], 1.80-1.86; OR, 1.46; 95% CI, 1.44-1.49; OR, 1.74; 95% CI, 1.69-1.80; and OR, 1.87; 95% CI, 1.70-2.05, respectively). Strikingly, male sex, when compared with female sex, was associated with an almost 2-fold (hazard ratio, 1.67; 95% CI, 1.05-2.67) increased risk to die from colorectal cancer when an adenoma or serrated polyp was found at the screening colonoscopy and a 4-fold (hazard ratio, 4.14; 95% CI, 2.72-6.3) increased risk when a high-risk polyp was found at the screening colonoscopy. The cumulative incidence for death of colorectal cancer for 60-year-old individuals was 8.5-fold higher in men as compared with women. Markedly, this sex gap narrowed with increasing age, whereas the difference in deaths of other causes remained similar in all age groups. CONCLUSIONS: Our findings strengthen the necessity of sex-specific screening recommendations. Importantly, further prospective studies should focus on sex differences in tumor biology to propose personalized surveillance guidelines.

Effect of an online educational module incorporating real-time feedback on accuracy of polyp sizing in trainees: a randomized controlled trial.

BACKGROUND: Although polyp size dictates surveillance intervals, endoscopists often estimate polyp size inaccurately. We hypothesized that an intervention providing didactic instruction and real-time feedback could significantly improve polyp size classification. METHODS: We conducted a multicenter randomized controlled trial to evaluate the impact of different components of an online educational module on polyp sizing. Participants were randomized to control (no video, no feedback), video only, feedback only, or video + feedback. The primary outcome was accuracy of polyp size classification into clinically relevant categories (diminutive [1-5mm], small [6-9mm], large [≥10mm]). Secondary outcomes included accuracy of exact polyp size (inmm), learning curves, and directionality of inaccuracy (over- vs. underestimation). RESULTS: 36 trainees from five training programs provided 1360 polyp size assessments. The feedback only (80.1%, P=0.01) and video + feedback (78.9%, P=0.02) groups had higher accuracy of polyp size classification compared with controls (71.6%). There was no significant difference in accuracy between the video only group (74.4%) and controls (P=0.42). Groups receiving feedback had higher accuracy of exact polyp size (inmm) and higher peak learning curves. Polyps were more likely to be overestimated than underestimated, and 29.3% of size inaccuracies impacted recommended surveillance intervals. CONCLUSIONS: Our online educational module significantly improved polyp size classification. Real-time feedback appeared to be a critical component in improving accuracy. This scalable and no-cost educational module could significantly decrease under- and overutilization of colonoscopy, improving patient outcomes while increasing colonoscopy access.