View clinical trials related to Colorectal Adenoma.
Filter by:The goal of this substudy is to investigate the accuracy of a computer-aided polyp characterization (CADx) system. The main question[s] it aims to answer are: • How high is the specificity of the AI system when characterizing colorectal polyps Participants will receive a standard colonoscopy, assisted by the artificial intelligence (AI) assisted system GI Genius. Researchers will compare the AI system´s characterization with the histopathology to see how accurate the system is.
The goal of this cluster randomized multicenter controlled clinical trial (RCT) is to investigate whether a combined real time computer-aided polyp detection (CADe) and computer-aided polyp characterization (CADx) system (GI Genius, Medtronic) can increase the adenoma detection rate (ADR) and reduce the performance variability among endoscopists. Participants will be randomized (1:1) to either receive an AI-assisted colonoscopy (AIC) or a conventional colonoscopy (CC). If there is a comparison group: Researchers will compare the AIC-group and the CC-group to see if AIC can increase the ADR significantly.
Nowadays, colonoscopy is considered the gold standard for the detection of lesions in the colorectal mucosa. However, around 25% of polyps may be missed during the conventional colonoscopy. Based on this, new technological tools aimed to improve the quality of the procedures, diminishing the technical and operator-related factors associated with the missed lesions. These tools use artificial intelligence (AI), a computer system able to perform human tasks after a previous training process from a large dataset. The DiscoveryTM AI-assisted polyp detector (Pentax Medical, Hoya Group, Tokyo, Japan) is a newly developed detection system based on AI. It was designed to alert and direct the attention to potential mucosal lesions. According to its remarkable features, it may increase the polyp and adenoma detection rates (PDR and ADR, respectively) and decrease the adenoma miss rate (AMR). Based on the above, the investigators aim to assess the real-world effectiveness of the DiscoveryTM AI-assisted polyp detector system in clinical practice and compare the results between expert (seniors) and non-expert (juniors) endoscopists.
This study aims to establish a multicenter registry platform to capture clinical data from subjects undergoing colorectal EMR and ESD.
A study of carcinogenesis-related molecular markers in the patients with colorectal cancer and colorectal adenoma.
This study is to determine how the Mainz Biomed Colorectal Cancer Screening Test works when used in people aged ≥45 years of age and at an average risk of developing colorectal cancer.
This is a multi-site comparative effectiveness randomized controlled trial (RCT) comparing annual fecal immunochemical testing (FIT) and colonoscopy for post-polypectomy surveillance among adults aged 65-82 with a history of colorectal polyps who are due for surveillance colonoscopy.
This originated as an observational study of Kaiser Permanente Northern California (KPNC) patients with a history of adenoma diagnosed by colonoscopy who received a subsequent surveillance colonoscopy between 2014 and 2019. The original goal of the study was to develop a risk prediction model that would help identify patients at highest risk for a diagnosis of advanced neoplasia (colorectal cancer and/or advanced adenoma) at or within 6 months following their surveillance colonoscopy. Candidate predictors of interest included patient demographics, medical history, and details related to the index colonoscopy. The investigators are now at the implementation stage and applying the risk prediction model to patients awaiting surveillance colonoscopy at select KPNC service areas to help identify those at highest risk for colorectal cancer based on their risk scores.
This double blinded randomized controlled trial aims to assess the efficacy of a novel oral synbiotic formula (SMT04) in reducing adenoma recurrence and colorectal neoplasia-related bacterial gene markers after endoscopic resection of colorectal advanced neoplasia.
To evaluate the accuracy and effectiveness of a novel screening method based on plasma multi-omics combining with artificial intelligence in a large prospective cohort for the detection of colorectal cancer and advanced adenomas.