Multichannel impedance monitoring for distinguishing nonerosive reflux esophagitis with minor changes on endoscopy in children

Objectives: There are reports describing the relationship between baseline impedance level and esophageal mucosal integrity at endoscopy, such as erosive and nonerosive reflux esophagitis. However, many children with symptoms of gastroesophageal reflux disease have normal findings or minor changes on esophagogastroduodenoscopy. We aimed to examine whether modest changes at esophagogastroduodenoscopy can be evaluated and correlated with esophageal multichannel intraluminal impedance monitoring. Methods: Patients (ages 0–17 years) with upper gastrointestinal symptoms who underwent combined esophagogastroduodenoscopy and multichannel intraluminal impedance monitoring at the Women’s and Children’s Hospital, Adelaide, Australia, between 2014 and 2016 were retrospectively studied and the following data were collected and used for analysis: demographics, multichannel intraluminal impedance data, included baseline impedance. Endoscopic findings were classified by modified Los Angeles grading, Los Angeles N as normal, Los Angeles M as with minimal change such as the erythema, pale mucosa, or friability of the mucosa following biopsy. Patients on proton pump inhibitor were excluded. Results: Seventy patients (43 boys; 61%) were enrolled with a mean age of 7.9 years (range 10 months to 17 years). Fifty-one patients (72.9%) were allocated to Los Angeles N, while Los Angeles M was evident in 19 patients (27.1%). Statistically significant differences were observed in the following parameters: frequency of acid and nonacid reflux and baseline impedance in channels 5 and 6. The median values of the data were 18.3 episodes, 16.0 episodes, 2461.0 Ω, 2446.0 Ω in Los Angeles N, 36.0 episodes, 31.0 episodes, 2033.0 Ω, 2009.0 Ω in Los Angeles M, respectively. Conclusion: Lower baseline impedance is helpful in predicting minimal endoscopic changes in the lower esophagus. A higher frequency of acid and nonacid reflux episodes was also predictive of minimal endoscopic change in the lower esophagus.

Application of artificial intelligence in pancreaticobiliary diseases

The role of artificial intelligence and its applications has been increasing at a rapid pace in the field of gastroenterology. The application of artificial intelligence in gastroenterology ranges from colon cancer screening and characterization of dysplastic and neoplastic polyps to the endoscopic ultrasonographic evaluation of pancreatic diseases. Artificial intelligence has been found to be useful in the evaluation and enhancement of the quality measure for endoscopic retrograde cholangiopancreatography. Similarly, artificial intelligence techniques like artificial neural networks and faster region-based convolution network are showing promising results in early and accurate diagnosis of pancreatic cancer and its differentiation from chronic pancreatitis. Other artificial intelligence techniques like radiomics-based computer-aided diagnosis systems could help to differentiate between various types of cystic pancreatic lesions. Artificial intelligence and computer-aided systems also showing promising results in the diagnosis of cholangiocarcinoma and the prediction of choledocholithiasis. In this review, we discuss the role of artificial intelligence in establishing diagnosis, prognosis, predicting response to treatment, and guiding therapeutics in the pancreaticobiliary system.

Training and deploying a deep learning model for endoscopic severity grading in ulcerative colitis using multicenter clinical trial data

Introduction: The Mayo Clinic Endoscopic Subscore is a commonly used grading system to assess the severity of ulcerative colitis. Correctly grading colonoscopies using the Mayo Clinic Endoscopic Subscore is a challenging task, with suboptimal rates of interrater and intrarater variability observed even among experienced and sufficiently trained experts. In recent years, several machine learning algorithms have been proposed in an effort to improve the standardization and reproducibility of Mayo Clinic Endoscopic Subscore grading. Methods: Here we propose an end-to-end fully automated system based on deep learning to predict a binary version of the Mayo Clinic Endoscopic Subscore directly from raw colonoscopy videos. Differently from previous studies, the proposed method mimics the assessment done in practice by a gastroenterologist, that is, traversing the whole colonoscopy video, identifying visually informative regions and computing an overall Mayo Clinic Endoscopic Subscore. The proposed deep learning–based system has been trained and deployed on raw colonoscopies using Mayo Clinic Endoscopic Subscore ground truth provided only at the colon section level, without manually selecting frames driving the severity scoring of ulcerative colitis. Results and Conclusion: Our evaluation on 1672 endoscopic videos obtained from a multisite data set obtained from the etrolizumab Phase II Eucalyptus and Phase III Hickory and Laurel clinical trials, show that our proposed methodology can grade endoscopic videos with a high degree of accuracy and robustness (Area Under the Receiver Operating Characteristic Curve = 0.84 for Mayo Clinic Endoscopic Subscore ⩾ 1, 0.85 for Mayo Clinic Endoscopic Subscore ⩾ 2 and 0.85 for Mayo Clinic Endoscopic Subscore ⩾ 3) and reduced amounts of manual annotation. Plain language summary Patient, caregiver and provider thoughts on educational materials about prescribing and medication safety Artificial intelligence can be used to automatically assess full endoscopic videos and estimate the severity of ulcerative colitis. In this work, we present an artificial intelligence algorithm for the automatic grading of ulcerative colitis in full endoscopic videos. Our artificial intelligence models were trained and evaluated on a large and diverse set of colonoscopy videos obtained from concluded clinical trials. We demonstrate not only that artificial intelligence is able to accurately grade full endoscopic videos, but also that using diverse data sets obtained from multiple sites is critical to train robust AI models that could potentially be deployed on real-world data.

Artificial intelligence for identification and characterization of colonic polyps

Colonoscopy remains the gold standard exam for colorectal cancer screening due to its ability to detect and resect pre-cancerous lesions in the colon. However, its performance is greatly operator dependent. Studies have shown that up to one-quarter of colorectal polyps can be missed on a single colonoscopy, leading to high rates of interval colorectal cancer. In addition, the American Society for Gastrointestinal Endoscopy has proposed the “resect-and-discard” and “diagnose-and-leave” strategies for diminutive colorectal polyps to reduce the costs of unnecessary polyp resection and pathology evaluation. However, the performance of optical biopsy has been suboptimal in community practice. With recent improvements in machine-learning techniques, artificial intelligence–assisted computer-aided detection and diagnosis have been increasingly utilized by endoscopists. The application of computer-aided design on real-time colonoscopy has been shown to increase the adenoma detection rate while decreasing the withdrawal time and improve endoscopists’ optical biopsy accuracy, while reducing the time to make the diagnosis. These are promising steps toward standardization and improvement of colonoscopy quality, and implementation of “resect-and-discard” and “diagnose-and-leave” strategies. Yet, issues such as real-world applications and regulatory approval need to be addressed before artificial intelligence models can be successfully implemented in clinical practice. In this review, we summarize the recent literature on the application of artificial intelligence for detection and characterization of colorectal polyps and review the limitation of existing artificial intelligence technologies and future directions for this field.

How should we do colon capsule endoscopy reading: a practical guide

In this article, we aim to provide general principles as well as personal views for colonic capsule endoscopy. To allow an in-depth understanding of the recommendations, we also present basic technological characteristics and specifications, with emphasis on the current as well as the previous version of colonic capsule endoscopy and relevant software. To date, there is no scientific proof to support the optimal way of reading a colonic capsule endoscopy video, or any standards or guidelines exist. Hence, any advice is a mixture of recommendations by the capsule manufacturer and experts’ opinion. Furthermore, there is a paucity of data regarding the use of term(s) (pre-reader/reader-validator) in colonic capsule endoscopy. We also include a couple of handy tables in order to get info at a glance.

Evolving management of colorectal polyps

Advances in endoscopic technology have led to increased success in colorectal cancer (CRC) screening and polyp management, with reduction of CRC incidence and mortality. Despite these advances, CRC is still one of the leading causes of cancer deaths, and half of all CRC develops from lesions that were missed during colonoscopy while one-fifth of CRC arise from prior incomplete resection. Techniques to improve polyp detection are needed, along with optimization of complete resection of any abnormal lesions that are found. This article will review the currently available endoscopic resection techniques and will discuss where they fit in the management of polyps of different sizes and types, such as pedunculated versus nonpedunculated, and those with or without suspected invasion.

The role of ablation in the treatment of dysplastic Barrett’s esophagus

Endoscopic eradication therapy for Barrett’s esophagus has been established as an effective management strategy for patients with Barrett’s esophagus with dysplasia and early esophageal cancer. Among the endoscopic therapies, ablation techniques such as radiofrequency ablation and cryoablation are effective primary treatment interventions with acceptable low complication rates forming the spectrum of a multimodal approach. Appropriate selection of patients, high-definition endoscopic evaluation, and dedicated histological assessment are important cornerstones to help navigate to the best effective treatment method. Carefully structured surveillance programs and preventive measures will be needed to provide long-term durability for maintaining complete remission.

Bariatric procedures and microbiota: patient selection and outcome prediction

Obesity is a major health issue throughout the world and bariatric surgery plays a key role in its management and treatment. The role of microbiota in determining the pathogenesis of obesity has been widely studied, while its role in determining the outcome of bariatric surgery is an emerging issue that will be an outcome in near future studies. Studies on mice first showed the key role of microbiota in determining obesity, highlighting the fat mass increase in mice transplanted with microbiota from fat individuals, as well as the different microbiota composition between mice undergone to low-fat or high-fat diets. This led to characterize the asset of microbiota composition in obesity: increased abundance of Firmicutes, reduced abundance of Bacteroidetes and other taxonomical features. Variations on the composition of gut microbiome have been detected in patients undergone to diet and/or bariatric surgery procedures. Patients undergone to restricting diets showed lower level of trimethylamine N-oxide and other metabolites strictly associated to microbiome, as well as patients treated with bariatric surgery showed, after the procedure, changes in the relative abundance of Bacteroidetes, Firmicutes and other phyla with a role in the pathogenesis of obesity. Eventually, studies have been led about the effects that the modification of microbiota could have on obesity itself, mainly focusing on elements like fecal microbiota transplantation and probiotics such as inulin. This series of studies and considerations represent the first step in order to select patients eligible to bariatric surgery and to predict their outcome.

Clearance of circulating tumor DNA in a high-risk stage-IV rectal carcinoma patient with synchronous liver metastases after conversion surgery is correlated with pathologic complete response

Colorectal cancer is the third most common cancer worldwide, and its incidence continues to grow. Approximately one-third of patients with colorectal cancer develop liver metastases during the natural course of disease. Complete surgical resection is associated with very low mortality in colorectal liver metastasis patients, but only a small fraction of colorectal liver metastasis patients fulfill the selection criteria for surgical treatment. We herein describe a high-risk stage-IV rectal carcinoma patient who was initially unresectable according to the National Comprehensive Cancer Network guidelines with a clinical risk score of 4 but received conversion surgery combined with systemic chemotherapy and achieved a favorable long-term clinical outcome (pathologic complete response) of approximately 28 months. Furthermore, serial circulating tumor DNA monitoring using next-generation sequencing provided a comprehensive view of the patient’s clinical and pathologic status for better clinical decision support over the course of the disease. The absence of circulating tumor DNA/cells after conversion surgery was correlated with pathologic complete response. This case study not only demonstrated that a curative oncosurgical approach could be considered for high-risk colorectal liver metastasis patients under specific circumstances but also highlighted the role of circulating tumor DNA monitoring to gain further insight into the evolution of a patient’s response over time.

Endobariatric procedures for obesity: clinical indications and available options

Obesity remains a growing public health epidemic that has increased healthcare costs and related comorbidities. Current treatment guidelines encourage a multidisciplinary approach starting from patient selection, interventions, and long-term follow-up to maintain weight loss. However, these conservative interventions are largely ineffective at reducing body weight due to low adherence to the treatment regimen. Recently, endoscopic bariatric therapies have become an attractive alternative to traditional invasive bariatric surgeries due to their improved efficacy, safety, and cost-effectiveness. Endoscopic bariatric therapies include intragastric balloon placement, endoscopic sleeve gastroplasty, gastric bypass revision, and aspiration therapy. These procedures fall into two separate categories depending on the primary mechanism involved: restrictive or malabsorptive. Restrictive methods, such as the Orbera® and ReShape™ intragastric balloons, increase satiation and delay gastric emptying while decreasing the amount of food that can be ingested. In contrast, malabsorptive devices, such as the EndoBarrier®, interfere with the small intestine’s ability to absorb food while restoring normal gastrointestinal hormone levels regulating satiation. Together, these techniques provide useful alternatives for patients in whom pharmacological or lifestyle modifications have proven ineffective. Despite these advantages, the long-term effects of these procedures on metabolic changes remain to be studied. Furthermore, the management of complications from these procedures continues to evolve. In this review, we aim to elaborate on the clinical indications and efficacy of the endobariatric procedures, together with various types of available endoscopic bariatric therapy procedures.