Active clinical trials for "Adenoma"

Exploration of a novel rbcDNA liquid biopsy technique for early detection of colorectal cancer is a promising development in the field of disease diagnosis and screening. This technique has the potential to establish an efficient and sensitive system for the early detection of colorectal cancer, which can provide a new perspective for individual health monitoring.

The investigators aim to evaluate and compare the diagnostic accuracy of FIT and the novel panel of bacterial gene markers (Fn, m3, Ch and Bc) collectively named as M3, in detecting colorectal advanced neoplasia.

This is a prospective equivalence colonoscopy study evaluating whether overall adenoma detection rate (ADR) is a reliable alternate for screening ADR. Overall indication includes screening, surveillance, and diagnostic indications.

This research trial studies kidney tumors in younger patients. Collecting and storing samples of tumor tissue, blood, and urine from patients with cancer to study in the laboratory may help doctors learn more about changes that occur in deoxyribonucleic acid (DNA) and identify biomarkers related to cancer.

Colon cancer is the second most common cancer in men and women. It is a disease that can be prevented if it is found early. Colonoscopy is still the best screening tool for colon cancer and the polyps that turn into colon cancer. However, due to a variety of factors, including affordability, time, and age, not all patients are able to be screened. Researchers are working on other options for early detection that are as accurate as colonoscopy. The purpose of this study if to determine if stool or blood can be used to detect colon cancers as early or earlier than colonoscopy. The researchers plan to use these samples to learn about specific proteins (also known as biomarkers) that may indicate colon polyps, colon cancer or an increased risk of developing colon cancer. In order to learn more about preventing and detecting colon and rectal cancer, we are collecting samples from subjects with cancer, adenomas, and colonoscopies who may be at risk for polyps.

The endoscopist performances in the optical diagnosis (OD) of colonic polyps with the available technologies vary widely across centers and across endoscopists. The OD process is strictly related to the operator training and expertise. Most of the available studies in optical characterization have been carried out by expert endoscopist in tertiary high volume centers, and weren't replied on large unselected populations. For these reasons, at the moment the optical characterization of polypoid lesions can't replace, in the everyday clinical practice, the histopathological evaluation of resected polyps. Artificial intelligence (AI)-based systems have the potential to make optical characterization process of colonic polyps easier and more reliable, thus supporting the endoscopist in the application of leave-in-situ and of resect-and-discard strategies. The implementation of such strategies would lead to a significant economic saving and a decrease of risks and complications related to unnecessary polypectomy. GI-Genius System (Medtronic Inc, Minneaopolis, USA) is a CNN-based algorithm allowing an automatic OD of colonic polyps. This system does not require dedicated light setting for polyp evaluation as it works with white light high definition images, which are the actual standard in every endoscopic unit. During colonoscopy, when a polyp is framed within the screen, a green detection box surrounds the polyp and the system automatically provides (whenever possible) the optical diagnosis labeling the polyp as "adenoma or non-adenoma". When the automatic polyp charaterization is unfeasible the label "no prediction" appears. Nowadays only few data about the feasibility and performances of this system in clinical practice are available. In addition published studies are mostly focused on technical rather thann clinical issues. The present prospective observational trial is primarily aimed at evaluating the diagnostic accuracy of optical characterization of colonic polyps <= 1 cm using GI-Genius System in daily clinical practice, having histopathology examination as reference standard.

Colorectal adenoma is a common disease and frequently-occurring disease in gastroenterology. With the continuous progress of colonoscopy equipment and the gradual improvement of endoscopic accessories, especially the development of chromo-endoscopy and magnifying endoscopy. The observation of the surface structure and capillary morphology of colorectal adenomas can realize optical biopsy. Currently, most clinical endoscopic diagnosis of colorectal diseases is biopsy under colonoscopy, and further treatment options are determined based on the pathological results of the biopsy. The problem is that the pathological diagnosis of some preoperative biopsy is not completely consistent with the pathological diagnosis of postoperative large specimens. Previous studies have found that the pathological diagnosis accuracy rate of preoperative biopsy is only 66-75%, so there is a certain degree of subjectivity in relying solely on colonoscopy white light biopsy. Based on the previous work, the research team has initially established an intelligent recognition model for colorectal adenoma classification (low-grade intraepithelial neoplasia, high-grade intraepithelial neoplasia), and formed a colorectal adenoma of a certain size with annotated endoscopic image data set. Using the YOLO-V4 algorithm, under the Darknet framework, to train an artificial intelligence (AI) system which specifically for adenoma recognition and diagnosis, its accuracy rate has reached more than 90%. This study intends to increase the sample size based on the previous work, and further improve the accuracy of the classification and diagnosis of the AI system, so as to guide the endoscopist to perform targeted biopsy and improve the accuracy of preoperative biopsy.

This study will be a prospective analysis conducted by Geneoscopy Inc. to evaluate the Colosense test, which is a multi-target stool RNA test for colorectal screening.

A prospective multi-center observational study. The study will enroll eligible subjects from the United States to optimize the biomarker panel and evaluate the performance of a cfDNA marker panel selected by the Sponsor for CRC and advanced adenoma detection.

The purpose of this study is to collect clinical specimens from subjects with a diagnosis of colorectal cancer/advanced adenoma or undergoing a screening colonoscopy and meeting study eligibility criteria.