View clinical trials related to Colon Polyp.
Filter by:The CRC DRAW study will assess the sensitivity and specificity of the blood-based, Next-Gen CRC Screening Test for the detection of CRC.
Overall Objective: To optimize timing of surveillance colonoscopy. Principal research question and specific aims: To assess the impact of access to a hand-held application on the timing of surveillance colonoscopy. To assess whether access to the tool improves adherence to recommended guidelines for follow-up colonoscopy intervals. Colonoscopy is commonly used for surveillance of patients with high risk of developing colorectal cancer, including those with family history of colorectal cancer and those with colorectal polyps. The recommended timing of surveillance colonoscopy varies by the estimated risk for development of colorectal cancer. The estimated risk varies by family history of colorectal cancer (number of affected individuals, age of the persons affected with CRC) and characteristics of the colorectal polyps (size, number, and histology of colorectal polyps (tubular or villous; high grade or low-grade dysplasia; sessile serrated polyp, sessile serrated polyp with dysplasia, hyperplastic polyp or traditional serrated adenomas). Guidelines take all of these factors into account in the recommendations for follow-up colonoscopy and hence are difficult to recall for the busy clinicians. Colonoscopy surveillance is frequently performed at shorter or longer than the recommended time intervals. The investigators have developed a smart phone application in which the characteristics of the patients can be inputted and the tool provides the recommended time interval for surveillance colonoscopy, based on North American guidelines. The investigators are proposing a pilot randomized trial to determine sample size estimates for a larger trial to assess the utility of this application in clinical practice.
Water exchange (WE) improves adenoma detection rate (ADR) but missed polyps occur due to human limitations. Computer-aided detection (CADe) improves polyp detection and can overcome human omissions, but a limiting factor is feces and air bubbles related false alarms (FA). WE provides salvage cleansing and can potentially reduce FA. The investigators compared the additional polyp detection rate (APDR) and false alarm rate (FAR) by CADe between WE and air insufflation.
The PREEMPT CRC study is a prospective multi-center observational study to validate a blood-based test for the early detection of colorectal cancer by collecting blood samples from average-risk participants who will undergo a routine screening colonoscopy.
Background: Colonoscopy is accepted to be the gold standard for screening of colorectal cancer (CRC). Most CRCs develop from adenomatous polyps, with colonoscopy accepted to be the gold standard for screening of CRC. An endoscopist's ability to detect polyps is assessed in the form of an Adenoma Detection Rate (ADR). Each 1.0% increase in ADR is associated with a 3.0% decrease in the risk of the patient developing an interval CRC. There remains a wide variation in endoscopist ADR. More recently, the use of artificial intelligence (AI) and computer aided diagnosis in endoscopy has been gaining increasing attention for its role in automated lesion detection and characterisation. AI can potentially improve ADR, but previous AI related work has largely focused on retrospectively assessing still endoscopic images and selected video sequences which may be subject to bias and lack clinical utility. There are only limited clinical studies evaluating the effect of AI in improving ADR. The CADDIE device uses convolutional neural networks developed for computer assisted detection and computer assisted diagnosis of polyps. Primary objective: To determine whether the CADDIE artificial intelligence system improves endoscopic detection of adenomas during colonoscopy. Primary endpoint: The difference in adenoma detection rate (ADR) between the intervention (supported with the CADDIE system) and non-intervention arm Study design: Multi-Centre, open-label, randomised, prospective trial to assess efficacy and safety of the CADDIE artificial intelligence system for improving endoscopic detection of colonic polyps in real-time.