View clinical trials related to Colonic Polyps.
Filter by:Colonoscopy is the current standard method for evaluation of colonic disorders such as colorectal cancer, IBD, polyps, and other conditions.
To investigate the role of different types of laxatives (compounded polyethylene glycol electrolyte dispersions and compounded sodium pico-sulfate) on the composition, evolution and recovery of the gut microbiome of patients with colonic polyps undergoing bowel preparation.
The aim of the study is to assess whether the use of artificial intelligence improves polyp detection in a segment of the colon (the right colon). To achieve this objective, patients will be divided into two groups: one will undergo a standard colonoscopy, the other a colonoscopy with the artificial intelligence software connected to the machine. This software does not modify the colonoscopy technique in any way, and does not require the administration of any product to the patient. The study will compare the detection rate of right colon polyps between the group of patients who underwent standard colonoscopy and those who underwent colonoscopy with artificial intelligence. If this number does not differ between the two groups, the investigators can conclude that there is no point in using artificial intelligence.
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.
CCIS is a novel score, created specifically to evaluate the completeness of caecal visualized. It can be applied to a single or multiple images. To create the CCIS, the caecum was divided into eight parts: the appendiceal orifice (AO), the tri-radiate fold part 1 (TF-1), 2 (TF-2), 3 (TF-3) and four outer quadrants (OQ 1-4). The ileo-caecal valve (ICV) is a reference point but is not part of the score. The quadrant adjacent to the ICV is labelled OQ1. The three other quadrants are labelled clockwise from this quadrant. The tri-radiate folds are also labelled clockwise with TF1 representing the triangle side that is majority-contained within OQ1. TF2 and TF3 are then labelled clockwise from TF1.
The present trial is aimed at evaluating whether in individuals scheduled for colonoscopy in the framework of a structured FIT (Fecal Immunochemical stool test)-based colorectal cancer screening program, the combination of an AI (artificial intelligence) system (CADEYE) with a mucosal exposure device (G-EYE 760R endoscope) increases the identification of subjects at high risk to develop colorectal cancer (according to recent ESGE-European Society of Gastrointestinal Endoscopy guidelines subjects are labelled as "high-risk" if harboring at least 1 adenoma ≥ 10 mm or with high grade dysplasia, or ≥ 5 adenomas, or any serrated polyp ≥ 10 mm or with dysplasia) when compared to colonoscopy performed with the support of AI only. Individuals fulfilling inclusion criteria are randomized (1:1) to two different arms (Control arm and Interventional arm, see below). Randomization is based on a computer-generated randomized block sequence, stratified according to age (50-61 vs. 62-74) and gender (male vs. female); size of the blocks (10 individuals) is not communicated to the investigator. Allocation is concealed and kept in a sealed envelope, which is opened just before starting colonoscopy. Individuals randomized in the Intervention arm receive colonoscopy examination with G-EYE 760R colonoscopes; once the cecum is reached the balloon is inflated, and the endoscope is withdrawn with the inflated balloon; the colonoscopy is performed with the support of the CADEYE system for polyp detection in both insertion and withdrawal phase; all polyps identified are removed and sent for histopathology examination. Individuals randomized in the Control arm (CADEYE only) receive colonoscopy with G-EYE 760R colonoscope but the balloon remains deflated for the entire procedure; the colonoscopy is performed with the support of the CADEYE system for polyp detection in both insertion and withdrawal phase; all polyps identified are removed and sent for histopathology examination. The main outcome measure is the rate of "high risk" individuals across the two study arms.
The investigators hope that this project will determine if the Endocuff device is a useful adjunct during colonoscopy by optimizing polyp detection and eliminating the need for the painful rectal retroflexion. As such, by improving polyp detection and eliminating the need for rectal retroflexion, it will directly reduce the likelihood of colon cancer and improve patient comfort respectively.
This is a prospective randomized placebo-controlled trial to evaluate the efficacy of peppermint oil spraying into the colonic lumen through the scope channel during screening colonoscopy. The primary outcome is to compare the colonic peristalsis between peppermint oil and placebo. The secondary outcomes compare the procedural time, polyp detection rate, adenoma detection rate, and adverse events.
Size of colorectal polyps is important to decide on appropriate surveillance intervals and treatment modality, as well as carrying out optical diagnosis strategies. However, polyp size measurement is often prone to inter-observer variability. An easy and accurate tool to assist in polyp size measurement is required. Recently, a virtual scale function for size measurement during endoscopy (SCALE EYE), operating in real-time without the use of any additional devices, has been developed. The aim of this study is to assess whether use of the SCALE EYE for polyp size measurement can reduce inter-observer variability.
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.