Clinical Research Directory

Evaluation of 'WAYMED Endo CL CS' for Automated Detection and Diagnosis of Colorectal Adenoma and Non-Adenoma Lesions

The purpose of this clinical trial is to evaluate the effectiveness of the computer-aided diagnosis (CADx) software, 'WAYMED endo CL CS', which assists medical specialists by automatically analyzing colorectal endoscopic images, identifying lesions, and providing probability values to classify them as Adenoma or Non-Adenoma. This pivotal trial is designed to confirm that 'WAYMED endo CL CS' can support clinicians in diagnostic decision-making by improving the classification of colorectal lesions.

Quantitative Fecal Immunochemical Test for Detection of Colorectal Cancer and Precancerous Lesions in Sohag

Colorectal cancer is a major cause of cancer-related morbidity and mortality worldwide, and early detection significantly improves patient outcomes. The fecal immunochemical test (FIT) is a non-invasive stool-based test used for detection of colorectal cancer; however, its diagnostic performance varies according to lesion type and anatomical location. This prospective observational cohort study aims to evaluate the diagnostic accuracy of quantitative fecal immunochemical testing (qFIT) in detecting colorectal cancer and precancerous lesions, including advanced adenomas and sessile serrated lesions, in adults undergoing colonoscopy in Sohag Government. The study will assess the sensitivity, specificity, and optimal cutoff values of qFIT according to lesion type, location, and histopathological characteristics.

Impact of Computer-aided Detection System on the Proximal Adenoma Miss Rate

This is a prospective, multicenter randomized controlled trial designed to determine whether the use of computer-aided detection system could reduce the miss rates of adenomas, SSLs, and polyps in the proximal colon during tandem colonoscopy.

Computer-Aided Water Exchange Colonoscopy With and Without Linked-Color Imaging for Detection of Clinically Significant Serrated Lesions

The goal of this clinical trial is to compare the detection rate of clinically significant serrated lesions (CSSL) in participants undergoing water exchange (WE) colonoscopy with artificial intelligence (AI)-based computer-aided detection (CADe) for screening, surveillance, diagnosis for symptoms, or referred owing to a positive fecal immunochemical test (FIT) or guaiac fecal occult blood test (gFOBT) result. There will be two arms in this study: WE with AI-assisted CADe (WEAID) control and WEAID plus linked-color imaging (LCI). The main question it aims to answer is whether the addition of LCI into WEAID colonoscopy increases CSSL detection rate. Both groups use water instead of air to insert the colonoscope into the cecum. The control method uses CADe to help detect colonic lesions. The study method uses a combination of CADe and LCI to detect lesions. Researchers will compare CSSL detection rate to see if the addition of LCI increases the detection of CSSL during CADe-assisted WE colonoscopy.