View clinical trials related to Colonic Polyps.
Filter by: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.
This controlled-randomized trial compares the artificial intelligence Genius® system assisted (Genius+) to standard (Genius-) colonoscopy. The aim of this study was to evaluate the impact of Genius® system on ADR in routine colonoscopy. The secondary aims will be the impact of Genius® system on polyp detection rate (PDR), serrated polyp detection rate (SPDR), advanced neoplasia detection rate (ANDR), mean number of polyps (MNP), polyp type and localization, and operator type (according to basal ADR).
Interventional prospective multicenter study: Polyp detection by an automated endoscopic tool as second observer during routine diagnostic colonoscopy
Colonoscopy is currently accepted as the gold standard in screening, surveillance and prevention for colorectal cancer (CRC), and therefore, its quality is a major priority. The quality of colonoscopy is greatly dependent on the quality of the bowel preparation, which can be limited by stool, foam, bubbles and other debris. In fact, colonic bubbles are described in 30 to 40% of colonoscopies, possibly undermining the quality of the exam, impairing the endoscopists view, demanding the further use of water or simethicone and eventually increasing fatigue and costs, while diminishing diagnostic accuracy. Although previous attempts, to date no endoscopic scale is validated regarding the presence of bubbles and most widely accepted and already validated scales do not include the presence or absence of bubbles in their definition, leading to the use of different home-made scales in randomized trials and impairing any solid meta-analysis conclusion. As so, the goal of this study is to develop and validate a new colonic bubble score (Colon Endoscopic Bubble Scale - CEBuS).
In the past decade, the demand for colonoscopy procedures has increased significantly since the introduction of population-based colorectal cancer (CRC) screening in many western countries. Post-polypectomy surveillance will increase the number of colonoscopy procedures conducted each year even further. The invasive nature of colonoscopy and the associated health-care costs warrant the development of a new non-invasive test to reduce the number of unnecessary colonoscopies. These days, many countries use a non-invasive fecal test for CRC screening which is easy to perform at home, but test characteristics such as sensitivity and specificity are suboptimal. Multiple studies have already shown that volatile organic compound (VOC) analysis has a high diagnostic accuracy for CRC and Advanced Adenomas. An additional VOC analysis, for example through breath testing, in patients with a positive fecal immunochemical test (FIT) may reduce the number of unnecessary colonoscopies. The aim of this study is to validate the diagnostic accuracy of the AeonoseTM to distinguish patients with CRC from healthy controls, and to assess reproducibility of test results.
Accurate optical diagnosis of colorectal polyps could allow a "resect and discard" strategy based on the results of the optical biopsy. Even though intensive training for optical diagnosis, there is still wide variability in individual endoscopists to meet the PIVI thresholds. The investigators with experience of prior optical diagnosis training perform new education and drill to apply proper high confidence according to their decision time. After the education program, the investigators prospectively evaluate real-time optical biopsy analysis of polyps in 8 academic gastroenterologists.
The objective of this study is to compare the polyp detection rate (PDR) of endoscopists unaware of a commercially available artificial intelligence (AI) device for polyp detection during colonoscopy and the PDR of endoscopists with the aid of such a device. Moreover, an extensive characterization of the performance of this device will be done.
This study evaluates the ability of endoscopists to perform a complete optical diagnosis of colorectal polyps between 5 and 15 mm, and the impact of the only endoscopic diagnosis on the follow-up program for those patients. This is a prospective study in which we compare the diagnosis regarding size and histology made by the endoscopist versus de pathologic diagnosis.
A prospective validation of real time deep learning artificial intelligence model for detection of missed colonic polyps
This is a single centre randomised controlled study comparing underwater clip closure versus conventional gas insufflation clip closure of post-resection defect in patients undergoing colonic endoscopic resection. The investigators hypothesize that underwater clip closure would be faster than conventional closure under gas insufflation.