Faculty Bibliography

BACKGROUND/UNASSIGNED:Computer-aided diagnosis (CADx) allows prediction of polyp histology during colonoscopy, which may reduce unnecessary removal of nonneoplastic polyps. However, the potential benefits and harms of CADx are still unclear. PURPOSE/UNASSIGNED:To quantify the benefit and harm of using CADx in colonoscopy for the optical diagnosis of small (≤5-mm) rectosigmoid polyps. DATA SOURCES/UNASSIGNED:Medline, Embase, and Scopus were searched for articles published before 22 December 2023. STUDY SELECTION/UNASSIGNED:Histologically verified diagnostic accuracy studies that evaluated the real-time performance of physicians in predicting neoplastic change of small rectosigmoid polyps without or with CADx assistance during colonoscopy. DATA EXTRACTION/UNASSIGNED:The clinical benefit and harm were estimated on the basis of accuracy values of the endoscopist before and after CADx assistance. The certainty of evidence was assessed using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) framework. The outcome measure for benefit was the proportion of polyps predicted to be nonneoplastic that would avoid removal with the use of CADx. The outcome measure for harm was the proportion of neoplastic polyps that would be not resected and left in situ due to an incorrect diagnosis with the use of CADx. Histology served as the reference standard for both outcomes. DATA SYNTHESIS/UNASSIGNED:Ten studies, including 3620 patients with 4103 small rectosigmoid polyps, were analyzed. The studies that assessed the performance of CADx alone (9 studies; 3237 polyps) showed a sensitivity of 87.3% (95% CI, 79.2% to 92.5%) and specificity of 88.9% (CI, 81.7% to 93.5%) in predicting neoplastic change. In the studies that compared histology prediction performance before versus after CADx assistance (4 studies; 2503 polyps), there was no difference in the proportion of polyps predicted to be nonneoplastic that would avoid removal (55.4% vs. 58.4%; risk ratio [RR], 1.06 [CI, 0.96 to 1.17]; moderate-certainty evidence) or in the proportion of neoplastic polyps that would be erroneously left in situ (8.2% vs. 7.5%; RR, 0.95 [CI, 0.69 to 1.33]; moderate-certainty evidence). LIMITATION/UNASSIGNED:The application of optical diagnosis was only simulated, potentially altering the decision-making process of the operator. CONCLUSION/UNASSIGNED:Computer-aided diagnosis provided no incremental benefit or harm in the management of small rectosigmoid polyps during colonoscopy. PRIMARY FUNDING SOURCE/UNASSIGNED:European Commission. (PROSPERO: CRD42023402197).

BACKGROUND AND AIMS/OBJECTIVE:The use of artificial intelligence (AI) has transformative implications to the practice of gastroenterology and endoscopy. The aims of this study were to understand the perceptions of the gastroenterology community toward AI and to identify potential barriers for adoption. METHODS:analysis was performed to determine the association between participant demographic information and perceptions of AI. RESULTS:Of 10,162 invited gastroenterologists, 374 completed the survey. The mean age of participants was 46 years (standard deviation, 12), and 299 participants (80.0%) were men. One hundred seventy-nine participants (47.9%) had >10 years of practice experience, with nearly half working in the community setting. Only 25 participants (6.7%) reported the current use of AI in their clinical practice. Most participants (95.5%) believed that AI solutions will have a positive impact in their practice. One hundred seventy-six participants (47.1%) believed that AI will make clinical duties more technical but will also ease the burden of the electronic medical record (54.0%). The top 3 areas where AI was predicted to be most influential were endoscopic lesion detection (65.3%), endoscopic lesion characterization (65.8%), and quality metrics (32.6%). Participants voiced a desire for education on topics such as the clinical use of AI applications (64.4%), the advantages and limitations of AI applications (57.0%), and the technical methodology of AI (44.7%). Most participants (42.8%) expressed that the cost of AI implementation should be covered by their hospital. Demographic characteristics significantly associated with this perception included participants' years in practice and practice setting. CONCLUSIONS:Gastroenterologists have an overall positive perception regarding the use of AI in clinical practice but voiced concerns regarding its technical aspects and coverage of costs associated with implementation. Further education on the clinical use of AI applications with understanding of the advantages and limitations appears to be valuable in promoting adoption.

BACKGROUND & AIMS/OBJECTIVE:Both computer-aided detection (CADe)-assisted and Endocuff-assisted colonoscopy have been found to increase adenoma detection. We investigated the performance of the combination of the 2 tools compared with CADe-assisted colonoscopy alone to detect colorectal neoplasias during colonoscopy in a multicenter randomized trial. METHODS:Men and women undergoing colonoscopy for colorectal cancer screening, polyp surveillance, or clincial indications at 6 centers in Italy and Switzerland were enrolled. Patients were assigned (1:1) to colonoscopy with the combinations of CADe (GI-Genius; Medtronic) and a mucosal exposure device (Endocuff Vision [ECV]; Olympus) or to CADe-assisted colonoscopy alone (control group). All detected lesions were removed and sent to histopathology for diagnosis. The primary outcome was adenoma detection rate (percentage of patients with at least 1 histologically proven adenoma or carcinoma). Secondary outcomes were adenomas detected per colonoscopy, advanced adenomas and serrated lesions detection rate, the rate of unnecessary polypectomies (polyp resection without histologically proven adenomas), and withdrawal time. RESULTS:From July 1, 2021 to May 31, 2022, there were 1316 subjects randomized and eligible for analysis; 660 to the ECV group, 656 to the control group). The adenoma detection rate was significantly higher in the ECV group (49.6%) than in the control group (44.0%) (relative risk, 1.12; 95% CI, 1.00-1.26; P = .04). Adenomas detected per colonoscopy were significantly higher in the ECV group (mean ± SD, 0.94 ± 0.54) than in the control group (0.74 ± 0.21) (incidence rate ratio, 1.26; 95% CI, 1.04-1.54; P = .02). The 2 groups did not differ in term of detection of advanced adenomas and serrated lesions. There was no significant difference between groups in mean ± SD withdrawal time (9.01 ± 2.48 seconds for the ECV group vs 8.96 ± 2.24 seconds for controls; P = .69) or proportion of subjects undergoing unnecessary polypectomies (relative risk, 0.89; 95% CI, 0.69-1.14; P = .38). CONCLUSIONS:The combination of CADe and ECV during colonoscopy increases adenoma detection rate and adenomas detected per colonoscopy without increasing withdrawal time compared with CADe alone. CLINICALTRIALS/RESULTS:gov, Number: NCT04676308.

In the past few years, we have seen a surge in the development of relevant artificial intelligence (AI) algorithms addressing a variety of needs in GI endoscopy. To accept AI algorithms into clinical practice, their effectiveness, clinical value, and reliability need to be rigorously assessed. In this article, we provide a guiding framework for all stakeholders in the endoscopy AI ecosystem regarding the standards, metrics, and evaluation methods for emerging and existing AI applications to aid in their clinical adoption and implementation. We also provide guidance and best practices for evaluation of AI technologies as they mature in the endoscopy space. Note, this is a living document; periodic updates will be published as progress is made and applications evolve in the field of AI in endoscopy.

BACKGROUND AND AIMS/OBJECTIVE: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. METHODS: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. RESULTS: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]). CONCLUSIONS: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.

INTRODUCTION/UNASSIGNED:Colorectal cancer (CRC) is the third most common malignancy and second leading cause of cancer-related mortality in the world. Adenoma detection rate (ADR), a quality indicator for colonoscopy, has gained prominence as it is inversely related to CRC incidence and mortality. As such, recent efforts have focused on developing novel colonoscopy devices and technologies to improve ADR. AREAS COVERED/UNASSIGNED:The main objective of this paper is to provide an overview of advancements in the fields of colonoscopy mechanical attachments, artificial intelligence-assisted colonoscopy, and colonoscopy optical enhancements with respect to ADR. We accomplished this by performing a comprehensive search of multiple electronic databases from inception to September 2023. This review is intended to be an introduction to colonoscopy devices and technologies. EXPERT OPINION/UNASSIGNED:Numerous mechanical attachments and optical enhancements have been developed that have the potential to improve ADR and AI has gone from being an inaccessible concept to a feasible means for improving ADR. While these advances are exciting and portend a change in what will be considered standard colonoscopy, they continue to require refinement. Future studies should focus on combining modalities to further improve ADR and exploring the use of these technologies in other facets of colonoscopy.

Introduction: Looping during colonoscopy increases scope forces and torquing which are causes of ergonomic injury among endoscopists. In addition, manual abdominal pressure and patient repositioning, used to address looping in 52% and 34% of colonoscopies, respectively, are known causes of musculoskeletal injuries among endoscopy staff. ColoWrap (ColoWrap, LLC, Durham, NC) is an anti-looping abdominal compression device applied during colonoscopy to decrease looping and limit the need for manual pressure and patient repositioning. We aimed to determine extent to which ColoWrap reduces ergonomic hazards associated with colonoscopy by performing a chart review and obtaining physician and staff feedback following use of the device.
Method(s): This retrospective, multi-center, observational chart review included patients that underwent colonoscopy with the ColoWrap device between September 25, 2016, and June 15, 2022. Demographics and procedural information were abstracted from patient records. Physician and staff experiences were captured using a survey instrument.
Result(s): 849 procedures were included in the review. The population was majority male (53%), over 60 (mean age: 60.8 +/- 11.6), and obese (mean BMI: 33.6 +/- 7.2). 49 patients (5.7%) had an abdominal hernia, 139 (16.3%) had at least one prior abdominal surgery, and 52 (6.1%) had a history of difficult or incomplete colonoscopy. Cecal intubation was achieved in 841 cases (99.1%). Mean cecal intubation time was 6.8 +/- 6.2 (min). Manual pressure was used in 109 cases (12.8%); significant manual pressure (> 3 min) was needed in only 21 procedures (2.5%). Patient repositioning was used in 48 cases (5.6%). No significant adverse events were reported. 84% of physicians indicated that ColoWrap use mitigated looping, shortened cecal intubation time, and reduced physical strain associated with advancing the scope. 90% of endoscopy staff reported reduced manual pressure and patient repositioning, and alleviation of musculoskeletal pain (Figure).
Conclusion(s): ColoWrap is safe and significantly reduces manual pressure and patient repositioning during colonoscopy relative to published rates. Physicians using ColoWrap experience less looping and physical strain and endoscopy staff suffer less musculoskeletal pain. The device is a viable tool among solutions to improve the safety and efficiency of colonoscopy. Further studies to identify circumstances in which ColoWrap use offers the greatest benefit to patients, physicians, and staff are warranted. (Figure Presented)

Introduction: Colorectal cancer (CRC) is the second leading cause of cancer-related mortality in the world. While effective at preventing CRC, standard colonoscopy can miss precancerous polyps placing patients at risk for interval CRC. Endoscopic mechanical attachments and artificial intelligence (AI) are technologies that have independently shown improvement in adenoma detection rate (ADR). We sought to compare the performance of Endocuff-assisted colonoscopy (EAC) to combined AI and EAC (AEAC) in relation to ADR.
Method(s): This was a single-center study involving patients who underwent either AEAC or EAC between December 2021 and May 2022. Demographic (age, sex) and clinical (indication, Boston Bowel preparation scale (BBPS), withdrawal time, polyp location, histology and size) data on patients was obtained from the electronic health record. The primary outcome was ADR. Secondary outcomes were polyp detection rate (PDR), adenomas per colonoscopy (APC), polyps per colonoscopy (PPC), sessile serrated lesion rate (SSR) and sessile serrated lesions per colonoscopy (SSPC). Categorical variables were analyzed using a two-sided chi square test. Continuous variables were assessed using the student's t-test or Mann-Whitney U-test. Odds ratios (OR) and 95% confidence intervals (CI) were calculated using logistic regression.
Result(s): 148 patients (50.7% men, mean age 60.9 years; 74 AEAC vs 74 EAC) were included. The AEAC group did not differ by age, sex, indication or BBPS from the EAC group (Table). ADR in the AEAC group was higher (71.6% vs 60.8%; OR 1.63; 95% CI 0.82-3.24; P = 0.17). SSR was 14.9% in the EAC group versus 24.3% in the AEAC group (P < 0.05) (Table). For adenomas .5-10mm in size, the AEAC group had a significantly higher ADR (28.4% vs 14.9%; OR 2.27; 95% CI 1.00-5.13; P = 0.05). Withdrawal time was longer in the AEAC group (8.0min vs 7.3min; P = 0.03). Subgroup analysis by indication revealed that ADR trended towards significance for patients in the AEAC group undergoing colonoscopy for CRC screening (70.3% vs 52.3%; OR 2.17; 95% CI 0.94-4.98; P = 0.068).
Conclusion(s): Combining AI with Endocuff-assisted colonoscopy increased ADR, PDR, APC, PPC, SSR and SSPC when compared to EAC. ADR trended towards significance for patients in the AEAC group undergoing CRC screening. This study highlights the potential benefits of maximizing surface area exposure (mechanical enhancement) combined with enhanced mucosal inspection (AI). Future larger studies will be needed to further validate this combination

PURPOSE OF REVIEW/OBJECTIVE:Colorectal cancer continues to be one of the most common causes of cancer-related death. Widespread dissemination of screening colonoscopy in the United States has led to a significant reduction in the incidence and mortality. Here we review current literature with an aim to highlight recent improvements in the safety, efficiency, and effectiveness of screening colonoscopy. RECENT FINDINGS/RESULTS:Colon capsule endoscopy is an emerging noninvasive method to capture images of colonic mucosa for select patients with appreciable sensitivity for polyp detection. Recent literature supports the use of the novel oral anticoagulant apixaban over other anticoagulants to reduce the risk of gastrointestinal bleeding related to colonoscopy. Cold snare polypectomy for smaller lesions and prophylactic clipping following resection of large polyps in the proximal colon may reduce the rate of delayed bleeding. Novel methods and devices for improving bowel preparation continue to emerge. Mechanical attachment devices and artificial intelligence represent recent innovations to improve polyp detection. SUMMARY/CONCLUSIONS:Clinicians should be aware of relevant data and literature that continue to improve the quality and safety of screening colonoscopy and incorporate these findings into their clinical practice.

Since its inception, endoscopy has evolved from being a solely diagnostic procedure to an expanding therapeutic field within gastroenterology. The incorporation of robotics in gastroenterology initially aimed to address shortcomings of flexible endoscopes in natural orifice transluminal endoscopy. Developing therapeutic endoscopic robotic platforms now offer operators improved ergonomics, visualization, dexterity, precision, and control and the possibility of increasing proficiency and standardization of complex endoscopic procedures including endoscopic submucosal dissection, endoscopic full thickness resection, and endoscopic suturing. The following review discusses the history, potential applications, and tools that are currently available and in development for robotics in therapeutic endoscopy.