Therapeutic Advances in Gastrointestinal Endoscopy最新文献

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.

Inflammatory bowel disease is a complex chronic inflammatory disorder with challenges in diagnosis, choosing appropriate therapy, determining individual responsiveness, and prediction of future disease course to guide appropriate management. Artificial intelligence has been examined in the field of inflammatory bowel disease endoscopy with promising data in different domains of inflammatory bowel disease, including diagnosis, assessment of mucosal activity, and prediction of recurrence and complications. Artificial intelligence use during endoscopy could be a step toward precision medicine in inflammatory bowel disease care pathways. We reviewed available data on use of artificial intelligence for diagnosis of inflammatory bowel disease, grading of severity, prediction of recurrence, and dysplasia detection. We examined the potential role of artificial intelligence enhanced endoscopy in various aspects of inflammatory bowel disease care and future perspectives in this review.

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.

Colorectal cancer is common and can be devastating, with long-term survival rates vastly improved by early diagnosis. Colon capsule endoscopy (CCE) is increasingly recognised as a reliable option for colonic surveillance, but widespread adoption has been slow for several reasons, including the time-consuming reading process of the CCE recording. Automated image recognition and artificial intelligence (AI) are appealing solutions in CCE. Through a review of the currently available and developmental technologies, we discuss how AI is poised to deliver at the forefront of CCE in the coming years. Current practice for CCE reporting often involves a two-step approach, with a 'pre-reader' and 'validator'. This requires skilled and experienced readers with a significant time commitment. Therefore, CCE is well-positioned to reap the benefits of the ongoing digital innovation. This is likely to initially involve an automated AI check of finished CCE evaluations as a quality control measure. Once felt reliable, AI could be used in conjunction with a 'pre-reader', before adopting more of this role by sending provisional results and abnormal frames to the validator. With time, AI would be able to evaluate the findings more thoroughly and reduce the input required from human readers and ultimately autogenerate a highly accurate report and recommendation of therapy, if required, for any pathology identified. As with many medical fields reliant on image recognition, AI will be a welcome aid in CCE. Initially, this will be as an adjunct to 'double-check' that nothing has been missed, but with time will hopefully lead to a faster, more convenient diagnostic service for the screening population.

The global obesity pandemic is among the most significant public health crises today. Furthermore, obesity remains a major risk factor for many weight-related comorbid conditions including cardiovascular disease, type 2 diabetes mellitus, liver disease, and cancer. Endoscopic bariatric therapies are currently on the rise as a new tool in the fight against the obesity epidemic, offering patients an alternative to more invasive surgery and a more effective option than diet and lifestyle modifications. The aim of this review article is to summarize the current literature regarding endoscopic bariatric therapies and their impact on obesity and its associated metabolic complications.

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.

Achalasia is a primary esophageal motility disorder characterized by the loss of inhibitory neurons in the myenteric plexus, resulting in impaired relaxation of the esophagogastric junction. Achalasia is an incurable disease, and the treatment modalities are aimed at disruption of the esophagogastric junction and vary widely from pharmacological to endoscopic to surgical. Traditional endoscopic therapy includes pneumatic dilation, botulinum toxin injection, and peroral endoscopic myotomy. This review aims to provide an overview of the endoscopic management of achalasia, while focusing on the utilization of peroral endoscopic myotomy and other novel approaches.

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.