Combination of Mucosa-Exposure Device and Computer-Aided Detection for Adenoma Detection During Colonoscopy: A Randomized Trial
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.
Framework and metrics for the clinical use and implementation of artificial intelligence algorithms into endoscopy practice: recommendations from the American Society for Gastrointestinal Endoscopy Artificial Intelligence Task Force
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.
Impact of Artificial Intelligence on Colonoscopy Surveillance After Polyp Removal: A Pooled Analysis of Randomized Trials
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.
ColoWrap Real-World Evidence: Colonoscopy Compression Device Mitigates Ergonomic Hazards for Endoscopists and Staff [Meeting Abstract]
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)
Comparing the Adenoma Detection Rate of Endocuff-Assisted Colonoscopy (EAC) Against Combined Artificial Intelligence and Endocuff-Assisted Colonoscopy (AEAC) [Meeting Abstract]
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
Safe, efficient, and effective screening colonoscopy
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.
Robotics in Therapeutic Endoscopy: Where We Are and Where Are We Going? (with video)
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.
Impact of comprehensive family history and genetic analysis in the multidisciplinary pancreatic tumor clinic setting
BACKGROUND:Genetic testing is recommended for all pancreatic ductal adenocarcinoma (PDAC) patients. Prior research demonstrates that multidisciplinary pancreatic cancer clinics (MDPCs) improve treatment- and survival-related outcomes for PDAC patients. However, limited information exists regarding the utility of integrated genetics in the MDPC setting. We hypothesized that incorporating genetics in an MDPC serving both PDAC patients and high-risk individuals (HRI) could: (1) improve compliance with guideline-based genetic testing for PDAC patients, and (2) optimize HRI identification and PDAC surveillance participation to improve early detection and survival. METHODS:Demographics, genetic testing results, and pedigrees were reviewed for PDAC patients and HRI at one institution over 45â€‰months. Genetic testing analyzed 16 PDAC-associated genes at minimum. RESULTS:Overall, 969 MDPC subjects were evaluated during the study period; another 56 PDAC patients were seen outside the MDPC. Among 425 MDPC PDAC patients, 333 (78.4%) completed genetic testing; 29 (8.7%) carried a PDAC-related pathogenic germline variant (PGV). Additionally, 32 (9.6%) met familial pancreatic cancer (FPC) criteria. These PDAC patients had 191 relatives eligible for surveillance or genetic testing. Only 2/56 (3.6%) non-MDPC PDAC patients completed genetic testing (pâ€‰<â€‰0.01). Among 544 HRI, 253 (46.5%) had a known PGV or a designation of FPC, and were eligible for surveillance at baseline; of the remainder, 15/291 (5.2%) were eligible following genetic testing and PGV identification. CONCLUSION/CONCLUSIONS:Integrating genetics into the multidisciplinary setting significantly improved genetic testing compliance by reducing logistical barriers for PDAC patients, and clarified cancer risks for their relatives while conserving clinical resources. Overall, we identified 206 individuals newly eligible for surveillance or genetic testing (191 relatives of MDPC PDAC patients, and 15 HRI from this cohort), enabling continuity of care for PDAC patients and at-risk relatives in one clinic.
Response to Yoo and Sonnenberg & Braillon
Deep Learning Computer-aided Polyp Detection Reduces Adenoma Miss Rate: A United States Multi-center Randomized Tandem Colonoscopy Study (CADeT-CS Trial)
BACKGROUND & AIMS/OBJECTIVE: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 undergo CADe colonoscopy first and 116 patients randomized to undergo 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; PÂ = .0247). SSL miss rate was lower in the CADe-first group (7.14% [1/14]) vs the HDWL-first group (42.11% [8/19]; PÂ = .0482). First-pass APC was higher in the CADe-first group (1.19 [standard deviation (SD), 2.03] vs 0.90 [SD, 1.55]; PÂ = .0323). First-pass ADR was 50.44% in the CADe-first group and 43.64 % in the HDWL-first group (PÂ = .3091). CONCLUSION/CONCLUSIONS: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 alone.