Active clinical trials for "Colonic Polyps"

Colorectal carcinoma (CRC) is the third most common cancer in male and female worldwide. In India, it is the fourth most common cause of cancer in males and third most common cancer in female. Age, smoking, colonic adenomatous polyp, family history are traditional risk factor for CRC. The vast majority of CRC results from malignant transformation from adenoma, which is called as adenoma carcinoma sequence. These adenomatous polyps grows slowly over many years and malignant transformation eventually occurs over 10 years. So, the early detection and removal of polyp at early stage should benefit in preventing CRC.

Adenomas are polyps of the colorectum that have the potential to develop into colon cancer. However, some adenomas never become malignant tumors, or if so, progression from adenoma into cancer takes a long time. As a result, screening colonoscopy programs were established in order to detect and resect adenomas at an early stage. After resection, polyps should be sent to pathology in order to make a histological diagnosis. Approximately 40-50% of all polyps have adenomatous histology whereas others contain benign histology (e.g. hyperplastic or inflammatory polyps). The latter polyps do not bear the risk to develop colon cancer. The bigger a polyp is the greater the chance is of it being malignant. During colonoscopy polyp size can be estimated visually by comparing the polyp with an opened biopsy forceps. The span of an opened forceps is 7 mm. Prior to using this technique, the forceps has to be inserted into the colon through a small working channel of the endoscope. Information on the actual adenoma size is crucial as surveillance recommendations depend on the size of the resected polyps. Moreover current guidelines contain the possibilities to disregard hyperplastic polyps in the sigmoid colon if the polyp size is below 5 mm. This means that diminutive hyperplastic polyps (< 5mm) do not necessarily require resection due to their benign dignity. However, there is increasing evidence that large human bias effects exist in estimating the size of polypoid lesions. For example, it has been shown that endoscopists exhibit terminal digit preferences leading to an exaggeration of estimated polyp size. In consequence the human bias problem might lead to wrong adenoma surveillance decisions. There is no doubt that technical devices are needed which can support endoscopists in finding the right declaration of polyp sizes. The aim of the current project is to create a computer program that is able to automatically measure polyp sizes during colonoscopy.

The purpose of this study is to determine the effects of the plant hormones strigolactones, on cell cultures of colonic polyps and colorectal cancer.

Individualized colonoscopy withdrawal time is determined based on the different grade of physician experience and quality of bowel preparation.

The Italian Society of Digestive Endoscopy (SIED) and the Italian Association of Gastroenterologists and Hospital Digestive Endoscopists (AIGO) want to develop an effective training program for endoscopists to improve the quality of colonoscopies through careful evaluation of quality indicators and how they can be improved with an appropriate educational program. Primary objective of this study is to evaluate the variation of "Polyp Detection Rate (PDR) and Adenoma Detection Rate (ADR)" obtained by operators at high and low volume of colonoscopy before and after a training period. Secondary objectives are to compare high and low volume endoscopists' performance before and after training comparing by evaluation of withdrawal time; Number polyps / patient and Number adenomas / patient; the percentage and time of intubation of the cecum, ; patient's pain perception based on the Nurse Assessed Patient Comfort Score (NAPCOMS) scale. The study is structured as follow: A first phase when all endoscopists collect the results of 200 colonoscopies in an electronic Case Report Form (eCRF) is formed(maximum enrollment period 4 months). A second phase of training through an e-platform in which the endoscopists are offered with an online refresh reviewing the international standard parameters to perform a quality colonoscopy. Once the final training exam have been passed, the endoscopist will be able to access the third phase A third phase in which the endoscopists will collect prospectively the colonoscopies they perform in an eCRF (maximum enrollment period 4 months).

The aim of this study was to assess the performance of AI system in polypectomy

Colorectal cancer is a maior cause of morbidity and mortality worldwide.Colonoscopy and removal of all adenomas is the most efficient method to prevent colorectal cancer.The most colorectal polyps detected are small(<10mm) and diminutive(≦5mm) during colonoscopy.At that size,the are overwhelmingly hyperplastic or adenomatous,and rarely harbour high-grade dysplasia,cancer or sessile serrated adenoma/polyp.Traditional white-light endoscopy cannot reliably distinguish between small adenomatous and hyperplastic polyps,thus,real-time recognition of the polyp histology during colonoscopy has the potential to minimize both the costs and complications associated with endoscopic biopsy and polpectomy.Linked color imaging(LCI),a new system for endoscopy modality,creates clear and bright endoscopic images by using short-wavelength narrow-band laser light combined with white laser light on the basis of magnifying blue laser imaging(BLI) technology. it is easier to recognize a slight difference in color of the mucosa. This is a study to investigate the impact of Linked color imaging endoscopes on the in vivo histology prediction of colonic polyps.

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

The aim of the study is to develop a computer program which is able to distinguish between adenomatous and non- adenomatous polyps on the basis of optical features of the polyps. Still images of polyps (< 10 mm of size) will be collected during routine colonoscopy procedures. All polyps will be resected endoscopically so that histopathological diagnoses (gold standard) can be notified. In the validation phase of the study a computer program will be established which aims to distinguish between adenomatous and non- adenomatous polyps on the basis of optical features derived from still images. The program will operated using the the random forest learning method. Afterwards, in the testing phase of the study, still images of 100 polyps (not used in the validation phase) will be presented to the computer program. The establishment of a well- functioning computer program is the primary aim of the study.

The aim of the study is to develop a computer program which is able to automatically detect colorectal polyps in endoscopic video sequences. Furthermore, the program shall be able to automatically distinguish between adenomas, serrated adenomas and hyperplastic polyps on the basis of optical features of the polyps. Video sequences of polyps will be collected during routine colonoscopy procedures. All polyps will be resected endoscopically so that histopathological diagnoses (gold standard) can be notified. In the validation phase of the study a computer program will be established which aims to distinguish between adenomas, serrated adenomas and hyperplastic polyps on the basis of optical features derived from the videos. A deep learning approach will be used for programming. Afterwards, in the testing phase of the study, videos of 100 polyps (not used in the validation phase) will be presented to the computer program. The establishment of a well- functioning computer program is the primary aim of the study.