View clinical trials related to Colorectal Polyp.
Filter by:Colorectal cancer is the most frequent tumor in our environment if both sexes are considered together. Every year almost 800 cases are diagnosed in the districts of Tarragona. A little more than half of colorectal cancers are cured with surgery, with or without the addition of complementary treatments with chemotherapy and/or radiation therapy. Those who are not cured is because at the time of diagnosis the disease has already spread or they spread after having been treated surgically with curative intent. The purpose of the EarlyCRC project is to determine whether metabolites (substances of low molecular weight) can be found in the urine and stool of patients with colorectal cancer or polyps that can be easily and cheaply differentiated (urine or stool analysis) between the patients affected by colorectal cancer or polyps, from healthy individuals. For the identification of these possible metabolites, the urine analysis will be performed using the usual techniques in metabolomics, which studies the existing metabolites in biological processes.
Accurate classification of growths in the large bowel (polyps) identified during colonoscopy is imperative to inform the risk of colorectal cancer. Reliable identification of the cancer risk of individual polyps helps determine the best treatment option for the detected polyp and determine the appropriate interval requirements for future colonoscopy to check the site of removal and for further polyps elsewhere in the bowel. Current advanced endoscopic imaging techniques require specialist skills and expertise with an associated long learning curve and increased procedure time. It is for these reasons that despite being introduced in clinical practice, uptake of such techniques is limited and current methods of polyp risk stratification during colonoscopy without Artificial intelligence (AI) is suboptimal. Approximately 25% of bowel polyps that are removed by major surgery are analysed and later proved to be non-cancerous polyps that could have been removed via endoscopy thus avoiding anatomy altering surgery and the associated risks. With accurate polyp diagnosis and risk stratification in real time with AI, such polyps could have been removed non-surgically (endoscopically). Current Computer Assisted Diagnosis (CADx, a form of AI) platforms only differentiate between cancerous and non cancerous polyps which is of limited value in providing a personalised patient risk for colorectal cancer. The development of a multi-class algorithm is of greater complexity than a binary classification and requires larger training and validation datasets. A robust CADx algorithm should also involve global trainable data to minimise the introduction of bias. It is for these reasons that this is a planned international multicentre study. The Investigators aim to develop a novel AI five class pathology prediction risk prediction tool that provides reliable information to identify cancer risk independent of the endoscopists skill. These 5 categories are chosen because treatment options differ according to the polyp type and future check colonoscopy guidelines require these categories
This study aims to develop a highly sensitive, specific, and cost-effective blood assay for early detection of colorectal adenomas and cancer, using advanced machine learning and state-of-the-art biological analyses.
The goal of this study is to learn about the epigenetic and genetic regulation (microRNA/mRNA) of colorectal polyps and their evolvement as polyps and to colorectal cancer. Furthermore, the study aims at investigating whether certain epigenetic features, linked to polyps and/or cancer are traceable in blood samples. The main questions the study aims to answer are: 1. Are there specific microRNA/mRNA that are expressed in different types of polyps and cancers and their respective stages? 2. Is microRNA/mRNA expression in polyps and cancer traceable in blood from the same patient? 3. Is the intestinal microbiata correlated with colorectal polyps and cancer and their microRNA/mRNA expression? Type of study: clinical trial Participant population Participants consist of patients undergoing a scheduled colonoscopy where a polyp or cancer is discovered. Healthy controls, with normal colonoscopy findings will be enrolled. Biopsies will be obtained from polyps/cancers and from normal surrounding intestinal mucosa. Biopsies will be obtained from defined intestinal locations from healthy controls. Blood samples will be collected from all participants. Researchers will compare microRNA/mRNA and microbiota in patients with polyps/cancers and their respective stages as well as healthy controls. Comparisons include biopsies and blood samples.
Polyp size and count determines the follow-up intervals after colonoscopy. However, relying on the endoscopist's optical diagnosis for size estimation has shown considerable variability, leading to erroneous surveillance intervals and increased colorectal cancer risk. This study aims to assess the effectiveness of a new polyp size estimation software, called POSEIDON, which uses the tip of the auxiliary water-jet as reference and is implemented together with the EndoMind polyp detection system.
After introducing a nationwide screening program for colorectal cancer (CRC) in Denmark, more cases of early-stage CRC are being detected. Cancers in the earliest stages are often removed locally, either during the diagnostic colonoscopy or through planned minimally invasive surgery. This early detection of cancer, and thereby an improved prognosis, is a positive feature but has also introduced a new clinical dilemma. Is the patient fully cured by the local resection, or do they need further surgery? Whether further surgery is recommended at the Multi-Disciplinary Team (MDT) board meeting depends on the outcome of specific criteria from the histopathological assessment of the locally removed specimen. The presence of these criteria does not, however, translate directly into the presence of residual disease - merely into a theoretically increased risk. In Denmark, after surgery, the fraction of cases with residual disease has been around 15% for many years. In the remaining 85% of cases, local removal alone was curative - and the surgery appears excessive. Investigating blood samples for the presence of circulating tumor DNA (ctDNA) is a new and promising method for cancer detection. The method utilizes that cancer cells release ctDNA into the circulation. ctDNA detected in blood drawn from a patient a few days after local removal of a tumor indicates that residual disease is present and further treatment, such as surgery, is needed. The purpose of this study is to investigate, whether analyses of ctDNA can correctly identify patients with residual disease after local removal of early CRC. If this identification proves accurate, many patients can be spared further surgery.
Beans are a forgotten staple food that shows promise in improving health. The goal of this study is to look at how bean supplementation affects metabolic and bowel health. In the long-term, the investigators believe this research will lead to a better understanding of the impact of beans on bowel health. The investigators also hope that this research study will help us understand ways to improve human diet and prevent colon cancer in the future.
The study involves the planned use of a new microwave-based device during colonoscopy procedures in 50 patients to assess the performance and safety of its use for detection of colorectal polyps and lack of normal clinical practice modification. The device is a final design version, which has been previously tested in several preclinical studies (including phantom studies, an ex vivo study with human tissues, and an in vivo study with porcine model) and in a pilot study in humans (NCT05477836)
A prospective, randomized, controlled study to compare the efficacy and safety of underwater endoscopic mucosal resection and conventional endoscopic mucosal resection in removal of non-pedunculated colorectal polyps
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.