Active clinical trials for "Adenoma"

When a polyp is found, we begin to wash it and observe it with OE mode 1.Then,the endoscopist gives a real-time optical diagnosis and the future surveillance interval.Finally,the polyp will be resected for the biopsy.

Colorectal cancer (CRC) is the third most common type of cancer among men and the second among women in Brazil. Despite the high incidence and significance of CRC in Brazil, very little is known about its prevalence among the asymptomatic population. Recently, a CRC screening program was implemented at the Cancer Hospital of Barretos. Characterization of the clinical findings detected in the screening population and the prevalence of basal CRC might contribute to better organization of the program and define the best strategy for a future national screening program. We hypothesize that recruitment and the early outcomes of our screening program based on the fecal immunochemical test (FIT) will differ from the outcomes corresponding to other populations due to sociodemographic differences. Aims: i. To implement a data collection and storage system for follow-up of the screening program participants and to measure early outcomes (adenoma, advanced adenoma and cancer) and associate them with sociodemographic risk factors; ii. to quantify the risk of CRC in the Brazilian population and to develop algorithms for risk stratification of CRC screening; and iii. to compare the risk stratification to other countries with low, medium and high incomes. Methods: Individuals aged 50 to 65 years will be included in the HCB screening program from November 2017 to December 2018. The following data will be collected from all participants: sociodemographic and ethnic (skin color) characteristics; risk factors for CRC, such as smoking and drinking; comorbidities, including diabetes mellitus and arterial hypertension; and FIT, colonoscopy and histopathology examination results. Data collection will be performed using the REDCap data collection/database system. The risk score will be formulated using the Chi-square test (or Fisher's exact test) and simple logistic regression, and the regression coefficients will be calculated. Then, the model identified for the training sample will be replicated with a validation sample. The resulting score will be used to calculate the sensitivity, specificity, positive predictive value, negative predictive value, accuracy, area under the receiver operating characteristic (ROC) curve and Kolmogorov D statistic.

The purpose of this study is to determine the sensitivity and specificity for LifeKit Prevent Colorectal Neoplasia Test for colorectal cancer (CRC) and for adenoma, including advanced adenoma.

The primary objective is to determine sensitivity, specificity, positive predictive value and negative predictive value of a bi-target stool DNA testing (the methylation status of SDC2 and SFRP2) for colorectal cancer and advanced precancerous neoplasm(including advanced adenoma and advanced serrated lesions) screening, using colonoscopy as the reference method. Lesions will be confirmed as malignant or precancerous by histopathologic examination. The secondary objective is to compare the performance of the bi-target stool DNA testing to a commercially available fecal immunochemical test (FIT) assay, both with respect to cancer and advanced precancerous neoplasm. Lesions will be confirmed as malignant or precancerous by colonoscopy and histopathologic examination.

A deep learning based system to calculate the proportion of Boston Bowel Prep Scale (BBPS) score of 0-1 during withdrawal phase has been constructed previously. This multi-center study is going to perform a prospective observational study to validate the threshold of the adequate proportion.

Pituitary adenomas is a very common disease, but the cause and genetics hasn't been identified. The investigators are going to use genome-wide association study to identify genes that may be related to pituitary adenomas.

Negative MRI findings may occur in up to 40% of cases of ACTH producing microadenomas. The aim of the study is to evaluate if detection of ACTH producing microadenomas can be increased using deep learning based denoising MRI.

In this observational pilot study, we assess the diagnostic performance of an artificial intelligence sytem for automated detection of colorectal polyps.

Colorectal cancer is one of the most common cancer in Hong Kong. In 2018, CRC accounted for 17.4%, 5,780 cases, of the total new cancers. CRC claimed 2,279 lives (15.8%) making it the second most deadly killer in the population. Since 2010, the Cancer Expert Working Group (CEWG) has recommended that asymptomatic average-risk individuals aged 50 to 75 years should consider one of the screening methods: fecal occult blood test (FOBT) every one to two years; OR flexible sigmoidoscopy every 5 years; OR colonoscopy every 10 years. However, it poses great challenges for large scale CRC screening using colonoscopy, such as bowel preparation difficulties, complications of procedure and poor compliance. ColoClear® is intended for use as an adjunctive screening test for the detection of colorectal neoplasia associated DNA markers and for the presence of occult hemoglobin in human stool. It has the potential of increasing the sensitivity of detecting CRC as compared to FOBT or faecal immunochemical test (FIT), which detects the presence of hemoglobin in stool alone. A positive result may indicate the presence of colorectal cancer or pre-malignant colorectal neoplasia. ColoClear® is not intended as a replacement for diagnostic colonoscopy. A positive result in ColoClear®, as with any screening test, should be followed by colonoscopy. ColoClear® is intended for colorectal cancer screening in average risk individuals: adults of either sex, 40 years or older, who are at high risk for colorectal cancer.

Screening colonoscopy is considered the gold standard for adenoma detection in the colon. However, it has been shown that a considerable number of polyps can be missed during screening colonoscopy. Until now the endoscopist himself is responsible for the detection of adenomatous polyps. No automatic tools are available supporting the colonoscopist to detect lesions. Recently, a computer program was developed that can be used to recognize and extract suspicious structure from colonoscopy video sequences. The program was built to automatically detected colonic polyps and to highlight the polyps by colour marking. The program was now refined so that the respective structures can be highlighted during real time colonoscopy. The aim of this feasibility study is to test whether the software is applicable during real time colonoscopy.