Pilot study on a new endoscopic platform for colorectal endoscopic submucosal dissection.

Background: The endoscopic submucosal dissection (ESD) is a technically demanding and time-consuming procedure, with an increased risk of adverse events compared to standard endoscopic resection techniques. The main difficulties are related to the instability of the operating field and to the loss of traction. We aimed to evaluate in a pilot trial a new endoscopic platform [tissue retractor system (TRS); ORISE, Boston scientific Co., Marlborough, MA, USA], designed to stabilize the intraluminal space, and to provide tissue retraction and counter traction. Method: We prospectively enrolled all consecutive patients who underwent an ESD for sigmoid/rectal lesions. The primary outcome was the rate of technical feasibility. Further technical aspects such as en-bloc and R0 resection rate, number of graspers used, circumferential incision time, TRS assemblage time, submucosal dissection time, and submucosal dissection speed were provided. Clinical outcomes (recurrence rate and adverse events) were recorded as well. Results: In all, 10 patients (M/F 4/6, age: 70.4 ± 11.0 years old) were enrolled. Eight out of 10 lesions were located in the rectum. Average lesion size was 31.2 ± 2.7 mm, and mean lesion area was 1628.88 ± 205.3 mm2. The two sigmoid lesions were removed through standard ESD, because the platform assemblage failed after several attempts. All rectal lesions were removed in an en-bloc fashion. R0 resection was achieved in 7/8 (87.5%) patients in an average procedure time of 60.5 ± 23.3 min. None of the patients developed neither intraprocedural nor postprocedural adverse events. Conclusion: TRS-assisted ESD is a feasible option when used in the rectum, with promising result in terms of efficacy and safety outcomes. Nevertheless, our pilot study underlines few technical limitations of the present platform that need to be overcome before the system could be widely and routinely used.

Key factors for improving adenoma detection rate.

INTRODUCTION: Colonoscopy is a fundamental tool in colorectal cancer (CRC) prevention. Nevertheless, one-fourth of colorectal neoplasms are still missed during colonoscopy, potentially being the main reason for post-colonoscopy colorectal cancer (PCCRC). Adenoma detection rate (ADR) is currently known as the best quality indicator correlating with PCCRC incidence. AREAS COVERED: We performed a literature review in order to summarize evidences investigating key factors affecting ADR: endoscopists education and training, patient management, endoscopic techniques, improved navigation (exposition defect), and enhanced lesions recognition (vision defect) were considered. EXPERT OPINION: 'Traditional' factors, such as split dose bowel preparation, adequate withdrawal time, and right colon second view, held a significant impact on ADR. Several devices and technologies have been developed to promote high-quality colonoscopy, however artificial intelligence may be considered the most promising tool for ADR improvement, provided that endoscopists education and recording are guaranteed.

Artificial intelligence and colonoscopy experience: lessons from two randomised trials.

BACKGROUND AND AIMS: Artificial intelligence has been shown to increase adenoma detection rate (ADR) as the main surrogate outcome parameter of colonoscopy quality. To which extent this effect may be related to physician experience is not known. We performed a randomised trial with colonoscopists in their qualification period (AID-2) and compared these data with a previously published randomised trial in expert endoscopists (AID-1). METHODS: In this prospective, randomised controlled non-inferiority trial (AID-2), 10 non-expert endoscopists (<2000 colonoscopies) performed screening/surveillance/diagnostic colonoscopies in consecutive 40-80 year-old subjects using high-definition colonoscopy with or without a real-time deep-learning computer-aided detection (CADe) (GI Genius, Medtronic). The primary outcome was ADR in both groups with histology of resected lesions as reference. In a post-hoc analysis, data from this randomised controlled trial (RCT) were compared with data from the previous AID-1 RCT involving six experienced endoscopists in an otherwise similar setting. RESULTS: In 660 patients (62.3±10 years; men/women: 330/330) with equal distribution of study parameters, overall ADR was higher in the CADe than in the control group (53.3% vs 44.5%; relative risk (RR): 1.22; 95% CI: 1.04 to 1.40; p<0.01 for non-inferiority and p=0.02 for superiority). Similar increases were seen in adenoma numbers per colonoscopy and in small and distal lesions. No differences were observed with regards to detection of non-neoplastic lesions. When pooling these data with those from the AID-1 study, use of CADe (RR 1.29; 95% CI: 1.16 to 1.42) and colonoscopy indication, but not the level of examiner experience (RR 1.02; 95% CI: 0.89 to 1.16) were associated with ADR differences in a multivariate analysis. CONCLUSIONS: In less experienced examiners, CADe assistance during colonoscopy increased ADR and a number of related polyp parameters as compared with the control group. Experience appears to play a minor role as determining factor for ADR. TRIAL REGISTRATION NUMBER: NCT:04260321.

Computer-aided detection versus advanced imaging for detection of colorectal neoplasia: a systematic review and network meta-analysis.

BACKGROUND: Computer-aided detection (CADe) techniques based on artificial intelligence algorithms can assist endoscopists in detecting colorectal neoplasia. CADe has been associated with an increased adenoma detection rate, a key quality indicator, but the utility of CADe compared with existing advanced imaging techniques and distal attachment devices is unclear. METHODS: For this systematic review and network meta-analysis, we did a comprehensive search of PubMed/Medline, Embase, and Scopus databases from inception to Nov 30, 2020, for randomised controlled trials investigating the effectiveness of the following endoscopic techniques in detecting colorectal neoplasia: CADe, high definition (HD) white-light endoscopy, chromoendoscopy, or add-on devices (ie, systems that increase mucosal visualisation, such as full spectrum endoscopy [FUSE] or G-EYE balloon endoscopy). We collected data on adenoma detection rates, sessile serrated lesion detection rates, the proportion of large adenomas detected per colonoscopy, and withdrawal times. A frequentist framework, random-effects network meta-analysis was done to compare artificial intelligence with chromoendoscopy, increased mucosal visualisation systems, and HD white-light endoscopy (the control group). We estimated odds ratios (ORs) for the adenoma detection rate, sessile serrated lesion detection rate, and proportion of large adenomas detected per colonoscopy, and calculated mean differences for withdrawal time, with 95% CIs. Risk of bias and certainty of evidence were assessed with the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. FINDINGS: 50 randomised controlled trials, comprising 34 445 participants, were included in our main analysis (six trials of CADe, 18 of chromoendoscopy, and 26 of increased mucosal visualisation systems). HD white-light endoscopy was the control technique in all 50 studies. Compared with the control technique, the adenoma detection rate was 7·4% higher with CADe (OR 1·78 [95% CI 1·44-2·18]), 4·4% higher with chromoendoscopy (1·22 [1·08-1·39]), and 4·1% higher with increased mucosal visualisation systems (1·16 [1·04-1·28]). CADe ranked as the superior technique for adenoma detection (with moderate confidence in hierarchical ranking); cross-comparisons of CADe with other imaging techniques showed a significant increase in the adenoma detection rate with CADe versus increased mucosal visualisation systems (OR 1·54 [95% CI 1·22-1·94]; low certainty of evidence) and with CADe versus chromoendoscopy (1·45 [1·14-1·85]; moderate certainty of evidence). When focusing on large adenomas (≥10 mm) there was a significant increase in the detection of large adenomas only with CADe (OR 1·69 [95% CI 1·10-2·60], moderate certainty of evidence) when compared to HD white-light endoscopy; CADe ranked as the superior strategy for detection of large adenomas. CADe also seemed to be the superior strategy for detection of sessile serrated lesions (with moderate confidence in hierarchical ranking), although no significant increase in the sessile serrated lesion detection rate was shown (OR 1·37 [95% CI 0·65-2·88]). No significant difference in withdrawal time was reported for CADe compared with the other techniques. INTERPRETATION: Based on the published literature, detection rates of colorectal neoplasia are higher with CADe than with other techniques such as chromoendoscopy or tools that increase mucosal visualisation, supporting wider incorporation of CADe strategies into community endoscopy services. FUNDING: None.

How to trick artificial intelligence: rectal heterotopic gastric lateral spreading tumor.

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Cap-Assisted Endoscopic Septotomy of Zenker's Diverticulum: Early and Long-Term Outcomes.

INTRODUCTION: Multiple therapeutic modalities including surgery and rigid and flexible endoscopy have been adopted to manage Zenker's diverticulum (ZD). Minimally invasive flexible endoscopic septotomy (FES) techniques have been increasingly favored over the past 20 years; however, long-term data are still scanty. The aim of this study is to evaluate early and long-term outcomes of FES for naive ZD in a single-center setting. METHODS: From 2010 to 2017, ZD patients treated with FES were included in a prospectively maintained database (NCT03948438). Those who had already been treated surgically or endoscopically were excluded from the analysis. The Dakkak and Bennett dysphagia scale was used to rate the dysphagia. Persistent complete or near-complete resolution of symptoms (Dakkak and Bennett 0 or 1) was defined as clinical success. Postprocedural adverse events were reported according to ASGE lexicon. RESULTS: Overall, 256 consecutive patients were treated. Mean pouch size was 29.8 ± 11.3 mm. The procedure was successfully completed in all scheduled patients, with an early clinical success of 96.1%. Adverse events occurred in 3.5% (9/256) of patients. Eight of them were mild/moderate with no fatal events, whereas one patient required surgery. Recurrences occurred in 31.3% (80/256) of treated patients after a mean time of 9 ± 3 months and 95% of recurrences were treated by a second FES. At an average follow-up of 5.5 years, 95.3% of patients were asymptomatic after a mean number of 1.3 procedures. DISCUSSION: FES is a safe and effective treatment modality for patients with ZD. Recurrence rate is significant; however, endoscopic reintervention is associated with long-term relief of dysphagia.

Single-dose versus short-course prophylactic antibiotics for peroral endoscopic myotomy: a randomized controlled trial.

BACKGROUND AND AIMS: Peroral endoscopic myotomy (POEM) has been recommended for achalasia treatment. To prevent the potential of infective risk, antibiotic prophylaxis is usually administered, whereas the additional need of antibiotic therapy after POEM is uncertain. The primary endpoint was to determine whether prophylaxis versus prophylaxis plus short therapy was needed after POEM. METHODS: Consecutive patients scheduled for POEM were randomly assigned (1:1) to group A (prophylactic cefazolin 2 g IV) or group B (prophylaxis + cefazolin 2 g IV × 3 followed by oral amoxicillin/clavulanate 3 g/day). Infective risk was assessed by means of host response, namely body temperature and serum levels of white blood cells and C-reactive protein; immune response (the cytokines interleukin [IL]-6, IL-1ß, and tumor necrosis factor-α and microbial translocation mediators lipopolysaccharide binding protein and soluble CD14); and blood cultures at time points before (t0) and after (t1, t2) POEM. RESULTS: After POEM, none of the 124 enrolled patients (54.6 ± 12.6 years old; 64 men) developed any fever (body temperature: t0, 36.56± .49°C; t1, 36.53± .52°C; t2, 36.48± .41°C), without any differences between groups at any time point. Regarding systemic inflammation, no difference was reported between groups in serum levels of C-reactive protein and white blood cells. Considering microbial translocation mediated response, lipopolysaccharide binding protein (group A: t0, 1539 ± 168.6 pg/mL; t1, 1321 ± 149.1 pg/mL; t2, 2492 ± 283.2 pg/mL; group B: t0, 1318 ± 115.9 pg/mL; t1, 1492 ± 163.8 pg/mL; t2, 2600 ± 328.2 pg/mL) and soluble CD14 (group A: t0, 2.16 ± .15 µg/mL; t1, 1.89 ± .15 µg/mL; t2, 2.2 ± .15 µg/mL; group B: t0, 2.1 ± .13 µg/mL; t1, 2 ± .13 µg/mL; t2, 2.5 ± .2 µg/mL) were similar between the 2 groups; the immune response cytokines IL-6, IL-1ß, and tumor necrosis factor-α also were similar in the 2 groups. In relation to blood cultures, at t1 the group B bacteremia rate was 3.2% (2/62) and group A was 1.6% (1/62) with no difference (P = .6). All subsequent blood cultures were negative at t2. CONCLUSIONS: According to our study, postprophylactic short-term antimicrobial therapy after POEM is not required because of a very low residual infective risk. (Clinical trial registration number: NCT03587337.).

Impact of artificial intelligence on colorectal polyp detection.

Since colonoscopy and polypectomy were introduced, Colorectal Cancer (CRC) incidence and mortality decreased significantly. Although we have entered the era of quality measurement and improvement, literature shows that a considerable amount of colorectal neoplasia is still missed by colonoscopists up to 25%, leading to an high rate of interval colorectal cancer that account for nearly 10% of all diagnosed CRC. Two main reasons have been recognised: recognition failure and mucosal exposure. For this purpose, Artificial Intelligence (AI) systems have been recently developed that identify a "hot" area during the endoscopic examination. In retrospective studies, where the systems are tested with a batch of unknown images, deep learning systems have shown very good performances, with high levels of accuracy. Of course, this setting may not reflect actual clinical practice where different pitfalls can occur, like suboptimal bowel preparation or poor examination technique. For this reason, a number of randomised clinical trials have recently been published where AI was tested in real time during endoscopic examinations. We present here an overview on recent literature addressing the performance of Computer Assisted Detection (CADe) of colorectal polyps in colonoscopy.

Underwater cap-assisted endoscopic retrograde cholangiopancreatography in patients with surgically altered anatomy: a pilot study.

INTRODUCTION: Endoscopic retrograde cholangiopancreatography (ERCP) in patients with surgically altered anatomy (SAA) is technically challenging and associated with a significant number of failures. We examined the feasibility and efficacy of a novel technique for the management of bile duct stones (BDSs), called underwater cap-assisted ERCP (u-ERCP). METHODS : Between June 2019 and February 2020 all patients with SAA with jaundice or cholangitis secondary to BDSs who underwent u-ERCP were enrolled. The u-ERCP technique combines the underwater advancement of a pediatric colonoscope with a transparent cap fitted on the tip of the endoscope. We evaluated the technical success, clinical success, and adverse events associated with u-ERCP. RESULTS : We describe the technique itself and our initial experience in six patients. A complete and successful procedure was carried out in all patients, with the occurrence of no adverse events. None of the patients needed additional treatments for recurrence of symptoms during the follow-up period. CONCLUSIONS : u-ERCP can be considered as a promising alternative for successful endoscopic management of biliary disease in patients with SAA.

Use of artificial intelligence in improving adenoma detection rate during colonoscopy: Might both endoscopists and pathologists be further helped.

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.

Artificial intelligence technologies for the detection of colorectal lesions: The future is now.

Several studies have shown a significant adenoma miss rate up to 35% during screening colonoscopy, especially in patients with diminutive adenomas. The use of artificial intelligence (AI) in colonoscopy has been gaining popularity by helping endoscopists in polyp detection, with the aim to increase their adenoma detection rate (ADR) and polyp detection rate (PDR) in order to reduce the incidence of interval cancers. The efficacy of deep convolutional neural network (DCNN)-based AI system for polyp detection has been trained and tested in ex vivo settings such as colonoscopy still images or videos. Recent trials have evaluated the real-time efficacy of DCNN-based systems showing promising results in term of improved ADR and PDR. In this review we reported data from the preliminary ex vivo experiences and summarized the results of the initial randomized controlled trials.

Computer-aided detection-assisted colonoscopy: classification and relevance of false positives.

BACKGROUND AND AIMS: False positive (FP) results by computer-aided detection (CADe) hamper the efficiency of colonoscopy by extending examination time. Our aim was to develop a classification of the causes and clinical relevance of CADe FPs, and to assess the relative distribution of FPs in a real-life setting. METHODS: In a post-hoc analysis of a randomized trial comparing colonoscopy with and without CADe (NCT: 04079478), we extracted 40 CADe colonoscopy videos. Using a modified Delphi process, 4 expert endoscopists identified the main domains for the reasons and clinical relevance of FPs. Then, 2 expert endoscopists manually examined each FP and classified it according to the proposed domains. The analysis was limited to the withdrawal phase. RESULTS: The 2 main domains for the causes of CADe FPs were identified as artifacts due to either the mucosal wall or bowel content, and clinical relevance was defined as the time spent on FPs and the FP rate per minute. The mean number of FPs per colonoscopy was 27.3 ± 13.1, of which 24 ± 12 (88%) and 3.2 ± 2.6 (12%) were due to artifacts in the bowel wall and bowel content, respectively. Of the 27.3 FPs per colonoscopy, 1.6 (5.7%) required additional exploration time of 4.8 ± 6.2 seconds per FP (ie, 0.7% of the mean withdrawal time). In detail, 15 (24.2%), 33 (53.2%), and 14 (22.6%) FPs were classified as being of mild, moderate, or severe clinical relevance. The rate of FPs per minute of withdrawal time was 2.4 ± 1.2, and was higher for FPs due to artifacts from the bowel wall than for those from bowel content (2.4 ± 0.6 vs 0.3 ± 0.2, P < .001). CONCLUSIONS: FPs by CADe are primarily due to artifacts from the bowel wall. Despite a high frequency, FPs result in a negligible 1% increase in the total withdrawal time because most of them are immediately discarded by the endoscopist.

Efficacy of Real-Time Computer-Aided Detection of Colorectal Neoplasia in a Randomized Trial.

BACKGROUND & AIMS: One-fourth of colorectal neoplasias are missed during screening colonoscopies; these can develop into colorectal cancer (CRC). Deep learning systems allow for real-time computer-aided detection (CADe) of polyps with high accuracy. We performed a multicenter, randomized trial to assess the safety and efficacy of a CADe system in detection of colorectal neoplasias during real-time colonoscopy. METHODS: We analyzed data from 685 subjects (61.32 ± 10.2 years old; 337 men) undergoing screening colonoscopies for CRC, post-polypectomy surveillance, or workup due to positive results from a fecal immunochemical test or signs or symptoms of CRC, at 3 centers in Italy from September through November 2019. Patients were randomly assigned (1:1) to groups who underwent high-definition colonoscopies with the CADe system or without (controls). The CADe system included an artificial intelligence-based medical device (GI-Genius, Medtronic) trained to process colonoscopy images and superimpose them, in real time, on the endoscopy display a green box over suspected lesions. A minimum withdrawal time of 6 minutes was required. Lesions were collected and histopathology findings were used as the reference standard. The primary outcome was adenoma detection rate (ADR, the percentage of patients with at least 1 histologically proven adenoma or carcinoma). Secondary outcomes were adenomas detected per colonoscopy, non-neoplastic resection rate, and withdrawal time. RESULTS: The ADR was significantly higher in the CADe group (54.8%) than in the control group (40.4%) (relative risk [RR], 1.30; 95% confidence interval [CI], 1.14-1.45). Adenomas detected per colonoscopy were significantly higher in the CADe group (mean, 1.07 ±1.54) than in the control group (mean 0.71 ± 1.20) (incidence rate ratio, 1.46; 95% CI, 1.15-1.86). Adenomas 5 mm or smaller were detected in a significantly higher proportion of subjects in the CADe group (33.7%) than in the control group (26.5%; RR, 1.26; 95% CI, 1.01-1.52), as were adenomas of 6 to 9 mm (detected in 10.6% of subjects in the CADe group vs 5.8% in the control group; RR, 1.78; 95% CI, 1.09-2.86), regardless of morphology or location. There was no significant difference between groups in withdrawal time (417 ± 101 seconds for the CADe group vs 435 ± 149 for controls; P = .1) or proportion of subjects with resection of non-neoplastic lesions (26.0% in the CADe group vs 28.7% of controls; RR, 1.00; 95% CI, 0.90-1.12). CONCLUSIONS: In a multicenter, randomized trial, we found that including CADe in real-time colonoscopy significantly increases ADR and adenomas detected per colonoscopy without increasing withdrawal time. ClinicalTrials.gov no: 04079478.

Prophylactic Clipping After Colorectal Endoscopic Resection Prevents Bleeding of Large, Proximal Polyps: Meta-analysis of Randomized Trials.

BACKGROUND & AIMS: The benefits of prophylactic clipping to prevent bleeding after polypectomy are unclear. We conducted an updated meta-analysis of randomized trials to assess the efficacy of clipping in preventing bleeding after polypectomy, overall and according to polyp size and location. METHODS: We searched the MEDLINE/PubMed, Embase, and Scopus databases for randomized trials that compared the effects of clipping vs not clipping to prevent bleeding after polypectomy. We performed a random-effects meta-analysis to generate pooled relative risks (RRs) with 95% CIs. Multilevel random-effects metaregression analysis was used to combine data on bleeding after polypectomy and estimate associations between rates of bleeding and polyp characteristics. RESULTS: We analyzed data from 9 trials, comprising 71897 colorectal lesions (22.5% 20 mm or larger; 49.2% with proximal location). Clipping, compared with no clipping, did not significantly reduce the overall risk of postpolypectomy bleeding (2.2% with clipping vs 3.3% with no clipping; RR, 0.69; 95% confidence interval [CI], 0.45-1.08; P = .072). Clipping significantly reduced risk of bleeding after removal of polyps that were 20 mm or larger (4.3% had bleeding after clipping vs 7.6% had bleeding with no clipping; RR, 0.51; 95% CI, 0.33-0.78; P = .020) or that were in a proximal location (3.0% had bleeding after clipping vs 6.2% had bleeding with no clipping; RR, 0.53; 95% CI, 0.35-0.81; P < .001). In multilevel metaregression analysis that adjusted for polyp size and location, prophylactic clipping was significantly associated with reduced risk of bleeding after removal of large proximal polyps (RR, 0.37; 95% CI, 0.22-0.61; P = .021) but not small proximal lesions (RR, 0.88; 95% CI, 0.48-1.62; P = .581). CONCLUSIONS: In a meta-analysis of randomized trials, we found that routine use of prophylactic clipping does not reduce risk of postpolypectomy bleeding overall. However, clipping appeared to reduce bleeding after removal of large (more than 20 mm) proximal lesions.