View clinical trials related to Metaplasia.
Filter by:The purpose of this study is to create a registry of participants with precursor lesions for gastric cancer, including gastric atrophy, intestinal metaplasia, and dysplasia. Normal controls and individuals with gastric cancer for comparison of baseline characteristics will also be enrolled.
In this study, we aim to establish a prospective cohort of patients with endoscopically and histologically confirmed intestinal metaplasia, collect gastric mucosal tissue samples from this cohort, and follow the development of gastric cancer over time.
The goal of this observational study is to learn about the key bacterial flora and metabolites associated with appendicitis in children. The main questions it aims to answer are: - To screen out the key biomarkers of pediatric appendicitis. - What are the microbial differences in different parts of pediatric appendicitis patients. Participants will detect feces using 16s ribosomal RiboNucleicAcid (16S rRNA) gene sequencing technology and differences of the fecal metabolites between healthy children and appendicitis children were analyzed using untargeted metabolomics based on Liquid chromatography-tandem mass spectrometry(LC-M S/MS) platform.Through the analysis of intestinal bacterial flora and metabolomics association and the differential analysis of intestinal bacterial flora in different parts of the case group, the key bacterial flora and metabolites were excavated.
Detections of goblet cells and dysplasia are crucial for diagnosis and determining the surveillance program of Barrett's esophagus (BE). However, the optimal biopsy numbers and their yield rates of intestinal metaplasia (IM) and dysplasia are still uncertain, especially in Asia. The aim of this study was to determine the optimal biopsy protocol of BE.
The operative link on gastric intestinal metaplasia assessment (OLGIM) staging systems using biopsy specimens were commonly used for histological assessment of gastric cancer risk. But its clinical application is limited for at least biopsy samples. The endoscopic grading system (EGGIM) has been shown a significant correlation with the OLGIM. The investigators designed a computer-aided diagnosis program using deep neural network to automatically evaluate the extent of IM and calculate the EGGIM scores in endoscopy examination. This study is aimed at exploring the relevance of the EGGIM scores automatically evaluated by Artificial Intelligence and OLGIM scores.
Currently, the Correa cascade is a widely accepted model of gastric carcinogenesis. Intestinal metaplasia is a high risk factor for gastric cancer. According to Sydney criteria, mild intestinal metaplasia was not associated with gastric cancer, while moderate to severe intestinal metaplasia was strongly associated with the development of gastric cancer. Because intestinal metaplasia is distributed in various forms, the use of white light endoscopy lacks specificity, and the consistency with histopathological diagnosis is poor; Pathological biopsy is still needed to make a diagnosis. At present, national guidelines suggest that OLGIM score should be used to evaluate the risk of gastric cancer, and patients with OLGIM grade III/IV should be monitored by close gastroscopy. However, it requires at least four biopsies, which is clinically infeasible. Confocal laser endomicroscopy allows real-time observation of living tissue, comparable to pathological findings.
Gastric intestinal metaplasia(GIM) is an important stage in the gastric cancer(GC). With technical advance of image-enhanced endoscopy (IEE), studies have demonstrated IEE has high accuracy for diagnosis of GIM. The endoscopic grading system (EGGIM), a new endoscopic risk scoring system for GC, have been shown to accurately identify a wide range of patients with GIM. However, the high diagnostic accuracy of GIM using IEE and EGGIM assessments performed all require much experience, which limits the application of EGGIM. The investigators aim to design a computer-aided diagnosis program using deep neural network to automatically evaluate the extent of IM and calculate the EGGIM scores.
Current national guidelines recommend the use of OLGIM score to evaluate the risk of gastric cancer in patients, and close gastroscopic monitoring should be performed after OLGIM grade III/IV. However, it would not be clinically feasible to require at least four biopsies. Confocal laser endomicroscopy is able to magnify the tissue by 1000X, which can be seen at the cellular level. Observing goblet cells under Confocal laser endomicroscopy is simpler and diagnostic accuracy is comparable to pathology. Confocal laser endomicroscopy enables better assessment of intestinal metaplasia in gastric mucosa, thus quantifying the risk of gastric cancer and avoiding multiple biopsies.
The OLGIM staging system is highly recommended for a comprehensive assessment of GIM severity to evaluate patients' gastric cancer risk. However, its need to take at least 4 biopsies is not clinically feasible due to a serious shortage of pathologists compared with the large number of gastric cancer screening population. We plan to develop a Digital Pathology artificial intelligence diagnosis system (DPAIDS), to automatically identify tumor areas in whole slide images(WSI) and quickly and accurately quantify the severity of intestinal metaplasia according to the proportion of intestinal metaplasia areas.
Since much is unknown about factors that lead to progression of the pre-neoplastic lesions and cancer. In addition, there is ongoing debate on the optimal surveillance intervals and techniques. To solve these important clinical questions, the establishment of a registry for a longitudinal study is planned.