View clinical trials related to Colon Adenoma.
Filter by:The goal of this observational study is to assess the correlation between the artificial intelligence (AI) derived effective withdrawal time (EWT) during colonoscopy and endoscopists' baseline adenoma detection rate (ADR). The association between the AI derived EWT with ADR during the prospective colonoscopy series would also be determined. The colonoscopy video of participants will be monitored by the AI
The goal of this clinical trial is to compare the detected adenoma per colonoscopy (APC) in participants undergoing screening, surveillance, and positive fecal immunochemical test (FIT) or guaiac fecal occult blood test (gFOBT). There will be two arms in this study: WE water control and water plus artificial intelligence (AI). The main question it aims to answer is whether the addition of AI into water exchange (WE) colonoscopy increases APC than WE alone. The control method will use water instead of air inserted into the colon. The study method will use a commercially available AI system plus water during the procedure. Researchers will compare APCs to see if the addition of AI increases detection of adenomas during WE colonoscopy.
Microscopic colitis (MC) is an inflammatory bowel disease characterized by chronic non-bloody watery diarrhoea and a macroscopically normal colonic mucosa upon endoscopic exploration (colonoscopy). The diagnosis is performed by microscopic examination of mucosal biopsies that reveal specific histopathological change. Between 4-20% of patients with chronic non-bloody diarrhoea who undergo colonoscopy with serial biopsies are diagnosed with MC. It has long been hypothesized that the microbiome plays a key role in the pathogenesis of MC. In patients with collagenous colitis, faecal stream diversion results in inflammation and histological remission, followed by disease relapse after intestinal transit is reconstructed. Moreover, studies carried out with faecal samples obtained after colonoscopy have demonstrated microbiome changes (reduced alpha diversity and higher microbial dysbiosis index) in patients with active MC. To avoid potential bias due to the effect of colonic lavage prior to colonoscopy in microbiota composition, the researchers of the present study previously evaluated the microbiome in faecal samples obtained before the diagnostic colonoscopy in patients with active MC. The results confirmed a reduced alpha diversity in diarrhoea groups; however, there were no differences between MC, bile-acid diarrhoea and functional diarrhoea. The microbial dysbiosis index was significantly higher in MC compared to the other diarrheal groups, but no bacterial species showed a significantly different relative abundance. On the other hand, the risk of colorectal cancer (CRC) or adenoma seems to be reduced in MC compared to controls. Growing evidence suggests microbial dysbiosis is a crucial environmental factor in the initiation of precancerous lesions of CRC such as adenomas. The objective of the current multicentric prospective study is to assess the differences in the mucosa adherent intestinal microbiome between patients with MC, non-MC chronic diarrhoea, healthy controls and patients with advanced colon adenomas. In addition to the study of the microbiome, sociodemographic variables, history of drug usage, diets and specific characteristics of diarrhoea will be collected. The hypothesis of the present study is that CM presents a specific mucosa adherent intestinal bacterial profile that may be relevant in the pathogenesis of the disease and that, additionally, may also play a protective role against the development of CRC and adenomas.
The goal of this observational study is to assess the correlation between the artificial intelligence (AI) derived effective withdrawal time (EWT) during colonoscopy and endoscopists' baseline adenoma detection rate (ADR). The association between the AI derived EWT with ADR during the prospective colonoscopy series would also be determined. The colonoscopy video of participants will be monitored by the AI and the result of EWT will be blinded to the endoscopists
Ultivision AI is a computer-assisted detection (CADe) device intended to aid endoscopists in the real-time identification of colonic mucosal lesions (such as polyps and adenomas). Ultivision AI CADe is indicated for white light colonoscopy only.
The incidence of colorectal cancer in China is increasing year by year. Studies have shown that colorectal cancer is more common in the left colon，especially in the China. Our previous study also showed a higher rate of missed adenoma in the left colon than the right colon during colonoscopy. Additionally, prolonging withdrawal time could only improve the ADR of right colon, but had limited effect on the ADR of left colon in our previous research. Our aim is to evaluate the effect of a second forward view examination of the left colon on the detection of adenoma detection during colonoscopy.
Water exchange (WE) is an effective insertion method to minimize insertion discomfort and maximize ADR. It is characterized by infusing water to guide insertion in an airless lumen with suctioning of infused water during insertion and almost complete removal of the infused water when cecal intubation is achieved. A modified Delphi review reported water exchange showed the highest overall ADR, ADR in screening cases, and in the right side of the colon compared with water immersion and air (or CO2) insufflation. One of the plausible mechanisms of improving ADR by water exchange is salvage cleaning during insertion, which might help artificial intelligence by removing the interference of fecal debris and bubbles. However, no RCT has been performed to evaluate the effect of CADe on WE colonoscopy. Therefore, investigators will conduct a RCT comparing the ADR of CADe assisted colonoscopy inserted with either WE or insufflation. Our hypothesis will be that CADe assisted WE colonoscopy achieves higher ADR than CADe assisted air insufflation colonoscopy.
The SPARC-C study is a prospective, single-centre observational study of patients referred for the management of large (≥ 20mm) non-pedunculated colorectal polyps (LNPCPs). Patients are managed consistent with current standards of care. Prospectively collected data includes: patient clinicodemographic details, lesion details, procedural details, and clinical outcomes.
During colonoscopy, the endoscopist will document colonoscopy indication; BBPS score; withdrawal time; adenoma and polyp detection rate at index and follow-up colonoscopy; completeness of polypectomy; polyp location, size, surface, morphology (Paris classification), histopathology; complications.
This is a prospective, multicenter, randomized controlled study to evaluate the effect of the Computer-Assisted Detection (CADe) Device on Adenomas Per Colonoscopy and Positive Percent Agreement for routine colonoscopies. The control arm is colonoscopy performed with High Definition White Light Endoscopy (HD-WLE) per standard of care. The intervention arm is colonoscopy performed with HD-WLE per standard of care plus the Computer-Assisted Detection (CADe) Device.