Active clinical trials for "Polyps"

The study aims to compare the results between colonoscopies with two different attachments on the distal end of the colonoscope.

This study is an open label, unblinded, non-randomized interventional study, comparing the investigational artificial intelligence tool with the current "gold standard": Data acquisition will be obtained during one scheduled colonoscopic procedure by a trained endoscopist. During insertion, no action will be taken, colonoscopy is performed following the standard of care. Once withdrawal is started, a second observer (not a trained endoscopist but person trained in polyp recognition) will start the bedside Artificial intelligence (AI) tool, connected to the endoscope's tower, for detection. This second observer is trained in assessing endoscopic images to define the AI tool's outcome. Due to the second observer watching the separate AI screen, the endoscopist is blinded of the AI outcome. When a detection is made by the AI system that is not recognized by the endoscopist, the endoscopist will be asked to relocate that same detection and to reassess the lesion and the possible need of therapeutic action. All detections are separately counted and categorized by the second observer. All polyp detections will be removed following standard of care for histological assessment. The entire colonoscopic procedure is recorded via a separate linked video-recorder.

The purpose of this study is to evaluate the performance of a non-cathartic, computer-assisted form of CT Colonography (Virtual Colonoscopy) for detection of pre-cancerous colon polyps in a group of asymptomatic screening patients.

Colorectal cancer (CRC) is the second most common cancer and the fourth leading cause of cancer death in Korea. Colonoscopy with polypectomy decreases the incidence and mortality from colorectal cancer. However, significant lesions can be missed during colonoscopy. Recent retrospective studies have shown that fellow involvement as a second observer may increase adenoma detection rate in colonoscopy. The aim of this prospective, multicenter, randomized study is to evaluate the impact when endoscopy nurse participate in adenoma detection during screening colonoscopy. The primary outcome measure is the adenoma detection rate (ADR).

Colorectal cancer (CRC) is the third most common cancer and second leading cause of cancer deaths in western countries. Colonoscopy is a preferred colorectal screening modality since it has both diagnostic and therapeutic capability. Detection and removal of polyps at colonoscopy decreases the incidence and mortality from colorectal cancer. Typical practice is to insert the colonoscope rapidly until it reaches the cecum (a pouch-like portion of the intestines, where the large bowel and the small bowel meet). The physician then withdraws the colonoscope slowly and looks for any polyps or abnormalities within the large bowel. The purpose of this study is to compare this standard practice to the approach whereby the physician examines the bowel as the scope is initially inserted AND as the colonoscope is withdrawn from patients' colons.

In this study the investigators hypothesize that High Definition White Light colonoscopy and narrow band imaging (NBI) will detect a higher number of adenomas compared to standard definition white light colonoscopy. NBI will have a higher accuracy in predicting polyp histology compared to high definition colonoscopy and standard colonoscopy. Specific Aim 1 - To compare the prevalence of adenomas detected by standard colonoscopy, high-definition white light colonoscopy and NBI. Specific Aim 2 - To compare the number of adenoma detected per subject by standard colonoscopy, high-definition white light colonoscopy and NBI. Specific Aim 3 - To compare the accuracy of predicting polyp histology between standard colonoscopy, high-definition white light colonoscopy and NBI by evaluating the surface mucosal and vascular patterns during the procedure. Specific Aim 4 - To determine the inter-observer agreement between investigators for the recognition of various polyp patterns

This is a randomized controlled trial of aspirin and/or folate supplementation for the prevention of the recurrence of neoplastic polyps (adenomas) of the large bowel.

A prospective validation of real time deep learning artificial intelligence model for detection of missed colonic polyps

The purpose of this study is to examine the role of an automatic polyp detection software (henceforth referred to as the research software) as a support system during colonoscopy; a procedure during which a physician uses a colonoscope or scope, to look inside a patient's rectum and colon. The scope is a flexible tube with a camera-to see the lining of the colon. The research software is used to aid in the detection of polyps (abnormal tissue growths in the wall of the colon and adenomas (pre-cancerous growths) during colonoscopy. The research software used in this study was programmed by a company in Shanghai, which develops artificial intelligence software for computer aided diagnostics. The research software was developed using a large repository (database or databases) of polyp images where expert colonoscopists outlined polyps and suspicious lesions. The software was subsequently developed and validated using several databases of images and video to operate in near real-time or within minutes of photographing the tissue. It is intended to point out polyps and suspicious lesions on a separate screen that stands behind the primary monitor during colonoscopy. It is not expected to change the colonoscopy procedure in any way, and the physician will make the final determination on whether or not to biopsy or remove any lesion in the colon wall. The research software will not record any video data during the colonoscopy procedure. In the future, this software may help gastroenterologists detect precancerous areas and decrease the incidence of colon cancer in the United States.

The purpose of this study is to compare cold snare polypectomy and cold forceps polypectomy using narrow-band imaging endoscopy for removal of diminutive colorectal polyps.