View clinical trials related to Adenoma Colon.
Filter by:The goal of this observational study was to assess the degree of agreement between the endoscopic and anatomopathological diagnosis of sessile serrated colorectal lesions in adult patients undergoing colonoscopy in Hospital Sírio-Libanes. The main questions it aimed to answer were: - The degree of agreement between endoscopic and anatomopathological diagnosis of sessile serrated colorectal lesions by calculating the Kappa Value of agreement. - To establish the detection rate of sessile serrated lesions and adenomas in the Endoscopy Department at Hospital Sírio-Libanês. - To evaluate the degree of agreement between endoscopic and anatomopathological diagnosis of sessile serrated colorectal lesions based on the resection method. - To assess the accuracy, positive predictive value, and negative predictive value of endoscopic diagnosis of serrated lesions compared to anatomopathological diagnosis. The data were prospectively collected through a form specifically designed for this project, that was completed immediately after the examination by the performing colonoscopist. All patients enrolled in this study agreed to participate in it and signed an informed consent form prior to the colonoscopy.
This is a randomized controlled multicenter clinical trial of computer-aided detection (CADe) system for the adjuvant diagnosis of intestinal polyps/adenomas ever conducted in a Chinese population. In addition, this study will evaluate the effect of CADe system on adenoma detection of endoscopists under fatigue.
The goal of this clinical trial is to evaluate the diagnostic yield of CADe in a consecutive population undergoing colonoscopy. The main question it aims to answer is the Adenoma Detection Rate (ADR). Participants undergoing colonoscopy will be randomized in a 1:1 ratio to either receive Computer-Aided Detection (CADe) colonoscopy or a conventional colonoscopy (CC). Researchers will compare the CADe group and the CC-group to see if CAD-e can increase the ADR significantly.
The Clinical Investigation is a summative usability study and a 'first-in-patient'-study of the independent medical device software (MDSW) utilizing artificial intelligence. The MDSW has completed the development phase and is ready to enter production. The primary objective of this study is to assess the user safety and secondary the user-friendliness of the MDSW to confirm compliance to certain General safety and performance requirements (GSPR) set by the MDR. The software to assess will be installed in a medical grade PC to allow the use of the MDSW according to its intended purpose of detecting colorectal polyps. However, the PC is not a part of the medical device under investigation and its performance and safety will not be assessed by this investigation. The intended purpose and clinical benefit of the MDSW is to assist the endoscopist in detecting more polyps, with the possibility of subsequently preventing colorectal cancer later on. The data obtained from the investigation will be used for regulatory purposes aiming to obtain a CE certification as class IIa according to MDR for the MDSW under investigation. The multi-center investigation will assess 8-20 endoscopists experience with the MDSW and whether technical difficulties occur during its use in one site. The user experience of the endoscopists will be collected in a questionnaire form. The investigator will additionally record any possible adverse effects (AE) or adverse technical effects (ATE) of the use of the MDSW. The MDSW will be used during ordinary colonoscopy in adult, out-patients ≥18 years but variables related to the patient outcome will not be assessed. Patients with inadequate bowel preparation, active inflammation, cecum not reached or not consenting will be excluded from the study. Each endoscopist will assess the device during 3-5 patient examinations. The primary objective of the investigation is to confirm that COLO-SW-1 is safe for use during colonoscopy as intended for aiding in detection of polyps. The secondary objective is to assess the user-friendliness of the MDSW interface. The clinical investigation is estimated to start in August 2022. The participation of the endoscopists will take place continuously through the clinical investigation until required number (up to 20) of participants has been reached. When 8 participants have been included in total, an interim analysis is made, and the Principal Investigator decides if the confirmatory objectives have been met. A conclusion can be drawn from the partial objectives met at this point. The study can continue for up to 20 participants to complete all endpoints, if required. The investigation will be closed by end of October 2022. The investigation will be deemed completed once the last evaluation form has been completed by the endoscopists.
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.
Colonoscopy completion by caecal intubation seldom represents a significant effort for the endoscopist. In this situation, additional techniques are necessary to achieve this goal: patients' manual abdominal compression, postural changes, and endoscopist relay. To date, no tool allows colonoscopy technical difficulty grading. This study pursues to describe the frequency of additional techniques for caecal intubation in a large sample of Argentinians in different centres who undergo colonoscopy for attending purposes, to develop a novel score for assessing colonoscopy technical difficulty.
A randomized, controlled study investigating the potential benefits of artificial intelligence (AI) in the detection of colonic polyps during outpatient colonoscopy. Randomization between the use of AI and no AI is performed before the study procedure.
Retrospective study, single blind (patient), allowing a posteriori clinical data collection of 90 patients during their passage to the ambulatory endoscopy circuit, to consider 3 groups and thus to deduce a colonic adenoma detection rate for each arm : - Colonoscopy Only Group - Artificial intelligence only group (IA GI GENIUS ™ alone) - Endoscopic Cap and Artificial Intelligence Group (endoscopy cap associated with the GI GENIUS ™ IA System)
This study is intended to demonstrate the superiority of colorectal polyp detection using computer-assisted colonoscopy compared to conventional colonoscopy.
Deep learning technology has an increasing role in medical image applications and, recently, an artificial intelligence device has been developed and commercialized by Medtronic for identification of polyps during colonoscopy (GI-GENIUS). This kind of computer-aided detection (CADe) devices have demonstrated its ability for improving polyp detection rate (PDR) and the adenoma detection rate (ADR). However, this increase in PDR and ADR is mainly made at the expense of small polyps and non advanced adenomas. Colonoscopies after a positive fecal immunochemical test (FIT) could be the scenario with a higher prevalence of advanced lesions which could be the ideal situation for demonstrating if these CADe systems are able also to increase the detection of advanced lesions and which kind of advanced lesions are these systems able to detect. The CADILLAC study will randomize individuals within the population-based Spanish colorectal cancer screening program to receive a colonoscopy where the endoscopist is assisted by the GI-GENIUS device or to receive a standard colonoscopy. If our results are positive, that could suppose a big step forward for CADe devices, in terms of definitive demonstration of being of help for efectively identify also advanced lesions.