Metabolic and Bariatric Endoscopy: A Mini-Review

We are currently in a worldwide obesity pandemic, which is one of the most significant health problems of the 21st century. As the prevalence of obesity continues to rise, new and innovate treatments are becoming available. Metabolic and bariatric endoscopic procedures are exciting new areas of gastroenterology that have been developed as a direct response to the obesity crisis. These novel interventions offer a potentially reversible, less invasive, safer, and more cost-effective method of tackling obesity compared to traditional bariatric surgery. Minimally invasive endoscopic treatments are not entirely novel, but as technology has rapidly improved, many of the procedures have been proven to be extremely effective for weight loss and metabolic health, based on high-quality clinical trial data. This mini-review examines the existing evidence for the most prominent metabolic and bariatric procedures, followed by a discussion on the future trajectory of this emerging subspecialty

Effect of gastro-esophageal reflux symptoms on the risk of Barrett's esophagus: A systematic review and meta-analysis

Background and Aim Gastro-esophageal reflux (GER) is the main predisposing factor for Barrett's esophagus (BE). A more precise estimate of the association of GER symptoms with the risk of BE would be important to prioritize endoscopic screening. We conducted a systematic review and meta-analysis to examine this issue. Methods MEDLINE, EMBASE, and EMBASE Classic were searched to identify cross-sectional studies that reported the prevalence of BE based on presence of GER symptoms. The prevalence of BE was compared according to presence or absence of GER symptoms using an odds ratio (OR), with a 95% confidence interval (CI). Specificity and sensitivity of GER symptoms for predicting BE was calculated. Results Of 10,463 citations evaluated, 19 studies reported the prevalence of BE in 43,017 subjects. The pooled OR among individuals with weekly GER symptoms compared with those without was 1.67 (95% CI 1.30-2.15) for endoscopically suspected BE, and 2.42 (95% CI 1.59-3.68) for histologically confirmed BE. No significant association was found between weekly GER symptoms and the presence of short segment BE (OR 1.30; 95% CI 0.86-1.97), whereas a strong association was present with long segment BE, with an OR of 6.30 (95% CI 2.26-17.61). Conclusions Gastro-esophageal reflux symptoms are associated with an increased odds of BE, with a further increase when weekly symptoms are present. Overall, GER symptoms showed low sensitivity and specificity for predicting BE; however, a strong association was found between weekly GER symptoms and long segment BE, but not short segment BE, suggesting that it may be worth considering screening individuals with weekly GER symptoms to rule out long segment BE

Interpretable Fully Convolutional Classification of Intrapapillary Capillary Loops for Real-Time Detection of Early Squamous Neoplasia

In this work, we have concentrated our efforts on the interpretability of classification results coming from a fully convolutional neural network. Motivated by the classification of oesophageal tissue for real-time detection of early squamous neoplasia, the most frequent kind of oesophageal cancer in Asia, we present a new dataset and a novel deep learning method that by means of deep supervision and a newly introduced concept, the embedded Class Activation Map (eCAM), focuses on the interpretability of results as a design constraint of a convolutional network. We present a new approach to visualise attention that aims to give some insights on those areas of the oesophageal tissue that lead a network to conclude that the images belong to a particular class and compare them with those visual features employed by clinicians to produce a clinical diagnosis. In comparison to a baseline method which does not feature deep supervision but provides attention by grafting Class Activation Maps, we improve the F1-score from 87.3% to 92.7% and provide more detailed attention maps

Factors influencing participation in randomised clinical trials among patients with early Barrett's neoplasia: a multicentre interview study

OBJECTIVES: Strong recruitment and retention into randomised controlled trials involving invasive therapies is a matter of priority to ensure better achievement of trial aims. The BRIDE (Barrett's Randomised Intervention for Dysplasia by Endoscopy) Study investigated the feasibility of undertaking a multicentre randomised controlled trial comparing argon plasma coagulation and radiofrequency ablation, following endoscopic resection, for the management of early Barrett's neoplasia. This paper aims to identify factors influencing patients' participation in the BRIDE Study and determine their views regarding acceptability of a potential future trial comparing surgery with endotherapy. DESIGN: A semistructured telephone interview study was performed, including both patients who accepted and declined to participate in the BRIDE trial. Interview data were analysed using the constant comparison approach to identify recurring themes. SETTING: Interview participants were recruited from across six UK tertiary centres where the BRIDE trial was conducted. PARTICIPANTS: We interviewed 18 participants, including 11 participants in the BRIDE trial and 7 who declined. RESULTS: Four themes were identified centred around interviewees' decision to accept or decline participation in the BRIDE trial and a potential future trial comparing endotherapy with surgery: (1) influence of the recruitment process and participant-recruiter relationship; (2) participants' views of the design and aim of the study; (3) conditional altruism as a determining factor and (4) participants' perceptions of surgical risks versus less invasive treatments. CONCLUSION: We identified four main influences to optimising recruitment and retention to a randomised controlled trial comparing endotherapies in patients with early Barrett's-related neoplasia. These findings highlight the importance of qualitative research to inform the design of larger randomised controlled trials

Endoscopic eradication therapy for Barrett’s esophagus–related neoplasia: a final 10-year report from the UK National HALO Radiofrequency Ablation Registry

Background and Aims: Long-term durability data for effectiveness of radiofrequency ablation (RFA) to prevent esophageal adenocarcinoma in patients with dysplastic Barrett’s esophagus (BE) are lacking. Methods: We prospectively collected data from 2535 patients with BE (mean length, 5.2 cm; range, 1-20) and neoplasia (20% low-grade dysplasia, 54% high-grade dysplasia, 26% intramucosal carcinoma) who underwent RFA therapy across 28 UK hospitals. We assessed rates of invasive cancer and performed detailed analyses of 1175 patients to assess clearance rates of dysplasia (CR-D) and intestinal metaplasia (CR-IM) within 2 years of starting RFA therapy. We assessed relapses and rates of return to CR-D (CR-D2) and CR-IM (CR-IM2) after further therapy. CR-D and CR-IM were confirmed by an absence of dysplasia and intestinal metaplasia on biopsy samples taken at 2 consecutive endoscopies. Results: Ten years after starting treatment, the Kaplan-Meier (KM) cancer rate was 4.1% with a crude incidence rate of .52 per 100 patient-years. CR-D and CR-IM after 2 years of therapy were 88% and 62.6%, respectively. KM relapse rates were 5.9% from CR-D and 18.7% from CR-IM at 8 years, with most occurring in the first 2 years. Both were successfully retreated with rates of CR-D2 of 63.4% and CR-IM2 of 70.0% 2 years after retreatment. EMR before RFA increased the likelihood of rescue EMR from 17.2% to 41.7% but did not affect the rate of CR-D, whereas rescue EMR after RFA commenced reduced CR-D from 91.4% to 79.7% (χ2 P < .001). Conclusions: RFA treatment is effective and durable to prevent esophageal adenocarcinoma. Most treatment relapses occur early and can be successfully retreated

Identifying key mechanisms leading to visual recognition errors for missed colorectal polyps using eye-tracking technology

BACKGROUND AND AIMS: Lack of visual recognition of colorectal polyps may lead to interval cancers. The mechanisms contributing to perceptual variation, particularly for subtle and advanced colorectal neoplasia, has scarcely been investigated. We aimed to evaluate visual recognition errors and provide novel mechanistic insights. METHODS: Eleven participants (7 trainees, 4 medical students) evaluated images from the UCL polyp perception dataset, containing 25 polyps, using eye tracking equipment. Gaze errors were defined as those where the lesion was not observed according to eye tracking technology. Cognitive errors occurred when lesions were observed but not recognised as polyps by participants. A video study was also performed including 39 subtle polyps, where polyp recognition performance was compared with a convolutional neural network (CNN). RESULTS: Cognitive errors occurred more frequently than gaze errors overall (65.6%) , with a significantly higher proportion in trainees (P=0.0264). In the video validation, the CNN detected significantly more polyps than trainees and medical students, with per polyp sensitivities of 79.5%, 30.0% and 15.4% respectively. CONCLUSIONS: Cognitive errors were the most common reason for visual recognition errors. The impact of interventions such as artificial intelligence, particularly on different types of perceptual errors, needs further investigation including potential effects on learning curves. To facilitate future research, a publicly accessible visual perception colonoscopy polyp database was created

Computer aided characterization of early cancer in Barrett's esophagus on i-scan magnification imaging - Multicenter international study

BACKGROUND AND AIMS: We aimed to develop a computer aided characterization system that can support the diagnosis of dysplasia in Barrett's esophagus (BE) on magnification endoscopy. METHODS: Videos were collected in high-definition magnification white light and virtual chromoendoscopy with i-scan (Pentax Hoya, Japan) imaging in patients with dysplastic/ non-dysplastic BE (NDBE) from 4 centres. We trained a neural network with a Resnet101 architecture to classify frames as dysplastic or non-dysplastic. The network was tested on three different scenarios: high-quality still images, all available video frames and a selected sequence within each video. RESULTS: 57 different patients each with videos of magnification areas of BE (34 dysplasia, 23 NDBE) were included. Performance was evaluated using a leave-one-patient-out cross-validation methodology. 60,174 (39,347 dysplasia, 20,827 NDBE) magnification video frames were used to train the network. The testing set included 49,726 iscan-3/optical enhancement magnification frames. On 350 high-quality still images the network achieved a sensitivity of 94%, specificity of 86% and Area under the ROC (AUROC) of 96%. On all 49,726 available video frames the network achieved a sensitivity of 92%, specificity of 82% and AUROC of 95%. On a selected sequence of frames per case (total of 11,471 frames) we used an exponentially weighted moving average of classifications on consecutive frames to characterize dysplasia. The network achieved a sensitivity of 92%, specificity of 84% and AUROC of 96% The mean assessment speed per frame was 0.0135 seconds (SD, + 0.006) CONCLUSION: Our network can characterize BE dysplasia with high accuracy and speed on high-quality magnification images and sequence of video frames moving it towards real time automated diagnosis

Revising the European Society of Gastrointestinal Endoscopy (ESGE) research priorities: a research progress update

AbstractBackground One of the aims of the European Society of Gastrointestinal Endoscopy (ESGE) is to encourage high quality endoscopic research at a European level. In 2016, the ESGE research committee published a set of research priorities. As endoscopic research is flourishing, we aimed to review the literature and determine whether endoscopic research over the last 4 years had managed to address any of our previously published priorities.Methods As the previously published priorities were grouped under seven different domains, a working party with at least two European experts was created for each domain to review all the priorities under that domain. A structured review form was developed to standardize the review process. The group conducted an extensive literature search relevant to each of the priorities and then graded the priorities into three categories: (1) no longer a priority (well-designed trial, incorporated in national/international guidelines or adopted in routine clinical practice); (2) remains a priority (i. e. the above criterion was not met); (3) redefine the existing priority (i. e. the priority was too vague with the research question not clearly defined).Results The previous ESGE research priorities document published in 2016 had 26 research priorities under seven domains. Our review of these priorities has resulted in seven priorities being removed from the list, one priority being partially removed, another seven being redefined to make them more precise, with eleven priorities remaining unchanged. This is a reflection of a rapid surge in endoscopic research, resulting in 27 % of research questions having already been answered and another 27 % requiring redefinition.Conclusions Our extensive review process has led to the removal of seven research priorities from the previous (2016) list, leaving 19 research priorities that have been redefined to make them more precise and relevant for researchers and funding bodies to target

A new artificial intelligence system successfully detects and localises early neoplasia in Barrett's esophagus by using convolutional neural networks

BACKGROUND AND AIMS: Seattle protocol biopsies for Barrett's Esophagus (BE) surveillance are labour intensive with low compliance. Dysplasia detection rates vary, leading to missed lesions. This can potentially be offset with computer aided detection. We have developed convolutional neural networks (CNNs) to identify areas of dysplasia and where to target biopsy. METHODS: 119 Videos were collected in high-definition white light and optical chromoendoscopy with i-scan (Pentax Hoya, Japan) imaging in patients with dysplastic and non-dysplastic BE (NDBE). We trained an indirectly supervised CNN to classify images as dysplastic/non-dysplastic using whole video annotations to minimise selection bias and maximise accuracy. The CNN was trained using 148,936 video frames (31 dysplastic patients, 31 NDBE, two normal esophagus), validated on 25,161 images from 11 patient videos and tested on 264 iscan-1 images from 28 dysplastic and 16 NDBE patients which included expert delineations. To localise targeted biopsies/delineations, a second directly supervised CNN was generated based on expert delineations of 94 dysplastic images from 30 patients. This was tested on 86 i-scan one images from 28 dysplastic patients. FINDINGS: The indirectly supervised CNN achieved a per image sensitivity in the test set of 91%, specificity 79%, area under receiver operator curve of 93% to detect dysplasia. Per-lesion sensitivity was 100%. Mean assessment speed was 48 frames per second (fps). 97% of targeted biopsy predictions matched expert and histological assessment at 56 fps. The artificial intelligence system performed better than six endoscopists. INTERPRETATION: Our CNNs classify and localise dysplastic Barrett's Esophagus potentially supporting endoscopists during surveillance