Active clinical trials for "Polyps"

Freenome is using a type of artificial intelligence, called machine learning, to identify patterns of cell-free biomarkers in blood to detect cancer early. The purpose of this study is to develop and validate a blood-based assay to detect colorectal cancer by collecting blood and stool samples from healthy patients undergoing routine screening colonoscopy and from patients recently diagnosed with colorectal cancer or advanced adenomas.

To assess the accuracy of predicting histology with virtual chromoendoscopy for distal colorectal polyps according to the ASGE PIVI statement.

In this study, Dutch gastroenterologists who are certified for performing colonoscopies on FIT-positive patients in the Dutch population screening program are trained in optical diagnosis with validated methods. After this training, an ex- and in-vivo test phase leads to "accreditation" and endoscopists will be observed in their optical diagnosis for 1 year. During this year, half of the endoscopists will be randomized towards 3-monthly feedback and the other half will receive feedback on their results after 1 year. The endoscopic prediction of endoscopists on polyp histology will be compared to histopathological outcome.

There is no consensus method for removal of diminutive (5mm) to small(6-9mm) colorectal polyps at colonoscopy. Neither the European Society of Gastrointestinal Endoscopy or the American Society of Gastrointestinal Endoscopy have guidelines for the removal of these polyps, despite the fact that around 90% of lesions removed by polypectomy at colonoscopy are diminutive to small. Multiple techniques are used for polyp removal, especially diminutive lesions. These include either forceps, both hot and cold, as well as snare with electrocautery or cold snare. Forceps utilises shearing force to grasp tissue and remove it, with the hot method passing a current through the grasper to essentially burn tissue. Snare is the use of a small metal loop placed and tightened at the base of polyps to cut through the tissue either straight away in a cold method or with electrocautery where a small current is passed through the loop to assist cutting through tissue. Surveys of Colonoscopists and Gastroenterologists in Australia and the United States show that the choice of method used for diminutive to small polyps is highly variable with cold snaring marginally favoured.Studies into polypectomy techniques are limited and it is clear that additional data and the review of polypectomy methods needs to be undertaken in order determine the optimal method for the removal of diminutive and small colorectal polyps. A technique is used at the Gloucestershire National Health Service (NHS) trust involving a submucosal pre injection with a standard solution then the use of cold forceps for removal of polyps ≤7mm. This appears to be both very safe and highly effective method for the removal of these lesions compared to other techniques. No formal published studies have been completed to evaluate this method at national and international levels. We propose a study to evaluate the effectiveness, safety and costs of this method.

Colorectal cancer remains the third most common cause of death from cancer worldwide. Colonoscopy allows removal of adenomatous polyps is the best colorectal cancer screening, according to the adenoma-carcinoma sequence. Recent studies have reported approximately 30% of interval cancer may be incomplete polyp resection. Complete polyp resection may be particularly important when implementing new methods for surveillance colonoscopies. Cold snare polypectomy (CSP) is considered to be a safer procedure for removing subcentimeter lesions than conventional hot snare polypectomy (HSP). CSP removal of polyps sized ≤5 mm have recommended by the European Society of Gastrointestinal Endoscopy guideline as the preferred technique. Previous report said that the complete resection rate of CSP for adenomatous polyps 4-9 mm in size was comparable to that of HSP, and in the foreseeable future CSP can be one of the standard techniques for 4-9 mm colorectal polyps. However, data on complete resection of colorectal polyps 1.0-1.5 mm in size is sparse. Investigators are interested in comparison of the resection rate of cold snare polypectomy for large (10-15 mm) and small (5-9 mm) colorectal polyps using CSP.

Rationale: Diminutive colorectal polyps (1-5mm in size) have a high prevalence and very low risk of harbouring cancer. Current practice is to send all these polyps for histopathological assessment by the pathologist. If an endoscopist would be able to correctly predict the histology of these diminutive polyps during colonoscopy, histopathological examination could be omitted and practise could become more time- and cost-effective. Studies have shown that prediction of histology by the endoscopist remains dependent on training and experience and varies greatly between endoscopists, even after systematic training. Computer aided diagnosis (CAD) based on convolutional neural networks (CNN) may facilitate endoscopists in diminutive polyp differentiation. Up to date, studies comparing the diagnostic performance of CAD-CNN to a group of endoscopists performing optical diagnosis during real-time colonoscopy are lacking. Objective: To develop a CAD-CNN system that is able to differentiate diminutive polyps during colonoscopy with high accuracy and to compare the performance of this system to a group of endoscopist performing optical diagnosis, with the histopathology as the gold standard. Study design: Multicentre, prospective, observational trial. Study population: Consecutive patients who undergo screening colonoscopy (phase 2) Main study parameters/endpoints: The accuracy of optical diagnosis of diminutive colorectal polyps (1-5mm) by CAD-CNN system compared with the accuracy of the endoscopists. Histopathology is used as the gold standard.

Colorectal cancer (CRC) is a leading cause of cancer-related morbidity and mortality worldwide, with rates of CRC predicted to increase. Colonoscopy is currently the gold standard of screening for CRC. Artificial intelligence (AI) is seen as a solution to bridge this gap in adenoma detection, which is a quality indicator in colonoscopy. AI systems utilize deep neural networks to enable computer-aided detection (CADe) and computer-aided classification (CADx). CADe is concerned with the detection of polyps during colonoscopy, which in turn is postulated to help decrease the adenoma miss-rate. In contrast, CADx deals with the interpretation of polyp appearance during colonoscopy to determine the predicted histology. Prediction of polyp histology is crucial in helping Clinicians decide on a "resect and discard" or "diagnose and leave strategy". It is also useful for the Clinician to be aware of the predicted histology of a colorectal polyp in determining the appropriate method of resection in terms of safety and efficacy. While CADe has been studied extensively in randomized controlled trials, there is a lack of prospective data validating the use of CADx in a clinical setting to predict polyp histology. The investigators plan to conduct a prospective, multi-centre clinical trial to validate the accuracy of CADx support for prediction of polyp histology in real-time colonoscopy.

The hypothesis of this study is that prophylactic coagulation therapy with coagulation forceps to visible vessels within the mucosal defect for colonic Endoscopic Mucosal Resection (EMR) will reduce the rate of delayed bleeding when compared with current established standard EMR technique.

The study team has developed a set of biomarkers of risk for colon cancer; this study tests 1) whether or not calcium and/or vitamin D supplementation can favorably affect these biomarkers in persons who are at higher than average risk for colon cancer (ie, have already undergone the removal of colon growths, called adenomatous polyps, which are known to be precursors to developing colon cancer), and 2) whether effects on the biomarkers predict who will get new colon polyps or not.

Comparison of the number of adenomas missed by the first exploration of the right colon by LCI (linked color imaging) or by white light during a colonoscopy, according to the order of randomization.