Repici, Alessandro

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.

AbstractBackgroundThe novel Coronavirus (SARS‐CoV‐2) has caused almost 2 million deaths worldwide. Both Food and Drug Administration and European Medicines Agency have recently approved the first COVID‐19 vaccines, and a few more are going to be approved soon.MethodsSeveral different approaches have been used to stimulate the immune system in mounting a humoral response. As more traditional approaches are under investigation (inactivated virus vaccines, protein subunit vaccines, recombinant virus vaccines), more recent and innovative strategies have been tried (non‐replicating viral vector vaccines, RNA based vaccines, DNA based vaccines).ResultsSince vaccinations campaigns started in December 2020 in both the US and Europe, gastroenterologists will be one of the main sources of information regarding SARS‐CoV 2 vaccination for patients in their practice, including vulnerable patients such as those with Inflammatory Bowel Disease (IBD), patients with chronic liver disease, and GI cancer patients.ConclusionsThus, we must ourselves be well educated and updated in order to provide unambiguous counseling to these categories of vulnerable patients. In this commentary, we aim to provide a comprehensive review of both approved COVID‐19 vaccines and the ones still under development, and explore potential risks, benefits and prioritization of vaccination.

AbstractBackground and AimRecently, the BLI Adenoma Serrated International Classification (BASIC) system was developed by European experts to differentiate colorectal polyps. Our aim was to validate the BASIC classification system among the US‐based endoscopy experts.MethodsParticipants utilized a web‐based interactive learning system where the group was asked to characterize polyps using the BASIC criteria: polyp surface (presence of mucus, regular/irregular and [pseudo]depressed), pit appearance (featureless, round/non‐round with/without dark spots; homogeneous/heterogeneous distribution with/without focal loss), and vessels (present/absent, lacy, peri‐cryptal, irregular). The final testing consisted of reviewing BLI images/videos to determine whether the criteria accurately predicted the histology results. Confidence in adenoma identification (rated “1” to “5”) and agreement in polyp (adenoma vs non‐adenoma) identification and characterization per BASIC criteria were derived. Strength of interobserver agreement with kappa (k) value was reported for adenoma identification.ResultsTen endoscopy experts from the United States identified conventional adenoma (vs non‐adenoma) with 94.4% accuracy, 95.0% sensitivity, 93.8% specificity, 93.8% positive predictive value, and 94.9% negative predictive value using BASIC criteria. Overall strength of interobserver agreement was high: kappa 0.89 (0.82–0.96). Agreement for the individual criteria was as follows: surface mucus (93.8%), regularity (65.6%), type of pit (40.6%), pit visibility (66.9%), pit distribution (57%), vessel visibility (73%), and being lacy (46%) and peri‐cryptal (61%). The confidence in diagnosis was rated at high ≥4 in 67% of the cases.ConclusionsA group of US‐based endoscopy experts have validated a simple and easily reproducible BLI classification system to characterize colorectal polyps with >90% accuracy and a high level of interobserver agreement.

Abstract Background Artificial intelligence (AI) research in colonoscopy is progressing rapidly but widespread clinical implementation is not yet a reality. We aimed to identify the top implementation research priorities. Methods An established modified Delphi approach for research priority setting was used. Fifteen international experts, including endoscopists and translational computer scientists/engineers, from nine countries participated in an online survey over 9 months. Questions related to AI implementation in colonoscopy were generated as a long-list in the first round, and then scored in two subsequent rounds to identify the top 10 research questions. Results The top 10 ranked questions were categorized into five themes. Theme 1: clinical trial design/end points (4 questions), related to optimum trial designs for polyp detection and characterization, determining the optimal end points for evaluation of AI, and demonstrating impact on interval cancer rates. Theme 2: technological developments (3 questions), including improving detection of more challenging and advanced lesions, reduction of false-positive rates, and minimizing latency. Theme 3: clinical adoption/integration (1 question), concerning the effective combination of detection and characterization into one workflow. Theme 4: data access/annotation (1 question), concerning more efficient or automated data annotation methods to reduce the burden on human experts. Theme 5: regulatory approval (1 question), related to making regulatory approval processes more efficient. Conclusions This is the first reported international research priority setting exercise for AI in colonoscopy. The study findings should be used as a framework to guide future research with key stakeholders to accelerate the clinical implementation of AI in endoscopy.

The COVID-19 pandemic has had a profound impact on provision of endoscopy services globally as staff and real estate were repurposed. As we begin to recover from the pandemic, a cohesive international approach is needed, and guidance on how to resume endoscopy services safely to avoid unintended harm from diagnostic delays. The aim of these guidelines is to provide consensus recommendations that clinicians can use to facilitate the swift and safe resumption of endoscopy services. An evidence-based literature review was carried out on the various strategies used globally to manage endoscopy during the COVID-19 pandemic and control infection. A modified Delphi process involving international endoscopy experts was used to agree on the consensus statements. A threshold of 80% agreement was used to establish consensus for each statement. 27 of 30 statements achieved consensus after two rounds of voting by 34 experts. The statements were categorised as pre-endoscopy, during endoscopy and postendoscopy addressing relevant areas of practice, such as screening, personal protective equipment, appropriate environments for endoscopy and infection control precautions, particularly in areas of high disease prevalence. Recommendations for testing of patients and for healthcare workers, appropriate locations of donning and doffing areas and social distancing measures before endoscopy are unique and not dealt with by any other guidelines. This international consensus using a modified Delphi method to produce a series of best practice recommendations to aid the safe resumption of endoscopy services globally in the era of COVID-19.

Abstract Background An oral formulation of methylene blue with colonic delivery (MB-MMX) has been developed to increase detection of colorectal polys during colonoscopy. Traditionally, there have been safety concerns regarding DNA damage when methylene blue is exposed to white light. The aim of this study was to evaluate DNA damage in colonic mucosa after MB-MMX chromoendoscopy. Methods This was an open-label phase II safety study to assess for genotoxicity on colorectal biopsies of patients undergoing two sequential colonoscopies before and after an oral dose of 200 mg MB-MMX added to their bowel prep. Analysis of a biomarker of double-stranded DNA breaks, γH2AX, was performed on biopsy specimens. Results Ten patients were included in the study. The mean expression of γH2AX ± 95 % confidence intervals of the 50 biopsies before and after MB-MMX administration were 0.58 ± 0.08 and 0.62 ± 0.09, respectively (P = 0.24). None of the analyzed samples showed excess positive γH2AX expression, confirming the absence of DNA damage on biopsies after methylene blue exposure. No deaths or serious adverse events occurred. Conclusions An oral dose of 200 mg of MB-MMX did not result in any detectable DNA damage.