Active clinical trials for "Polyps"

Linked color imaging (LCI)，a new endoscopy modality, creates clear and bright images by using short wavelength narrow band laser light. LCI can make red area appear redder and white areas appear whiter. Thus, it may be possible to distinguish adenoma and non-adenoma polyps based on color evaluation of LCI images. This study aimed to assess the correlation between histology results and LCI images. Moreover, the investigators conducted a pilot study to explore the clinical potential of LCI to distinguish adenoma and non-adenoma polyps and the accuracy of an automatic computer-aided diagnosis system using LCI imagine to predict histology polyps when compared to human experts physicians.

When a polyp is found, it woulf be recorded by a white-light and OE1 model with magnification for assessing and predicting its histology. After that, its really histology will be reported by an pathologist. When a polyp is found, OE mode 1 with magnification was first used with near focus the polyp and an endoscopist made a real-time prediction of polyp pathology. After that, high-definition mode and OE mode 1 without magnification were used to observe polyp sequencely. The video of all procedure was recorded.

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 classify different entities of colorectal polyps on the basis of optical polyp features. In the end, the computer program shall differentiate between (i) hypeplastic polyps, (ii) adenomas and (iii) serrated adenomas . In the first phase of the study a computer program will be established which aims to distinguish between the above mentions entities on the basis of optical features derived from still images. A machine learning apporach will be used for creating the program. Afterwards, in a second phase of the study, still images of 100 polyps (not used in the first phase) will be presented to the computer program. Quality of the computer program will be tested by calculating the accuracy for differentiating the three different polyp types. The gold standard for true polyp diagnoses will be based on histopathological diagnoses of the polyps. The same pictures of 100 polyps will also be presented to human experts. Experts will also predict histopathological diagnoses on the basis of optical polyps featurs. Accuracy of computer-decisions and human expert predictions will be compared. The establishment of a well- functioning computer program is the primary aim of the study.

Anatomic Fallopian tubal patency and physiologic patency testing are feasible via hystertoscopy. This study aims to test the impact of different types of intrauterine polyp(s) on Darwish test (office hysteroscopic bubble suction test and tubal peristalsis).

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.

Adenomas, serrated adenomas and hyperplastic polyps are polypoid lesion in the colorectum. At the present moment, all polyps should be resected endoscopically, although only adenomas and serrated adenomas, but not hyperplastic polyps have the potential to develop colorectal cancer. This approach enables the conduction of microscopic investigations of the lesions. By today, only the pathological diagnosis can distinguish exactly between these three polyp entities. Some studies have investigated the value of the optical characterization approach which is based on visual assessment of the polyp' surface structures. Based upon optical polyp features users are encouraged to predict histopathological polyp diagnoses solely on behalf of optical or endoscopical criteria. This method is conducted in real time during colonoscopy. If it could be shown, that endoscopist using the optical characterization approach are able to predict histopathological diagnoses of colonic polyps sufficiently this would possibly lead to simplification of diagnostic procedures. For instance, it would be conceivable to resect small polyps and discard them without further assessment by a pathologist. One problem in this context is a correct differentiation between hyperplastic polyps and serrated adenomas. These two polyp entities are known to show similar optical features. However, while serrated adenomas are premalignant lesions hyperplastic polyps have benign histology and never develop into cancer. It is therefore important to sufficiently distinguish hyperplastic polyps from serrated lesions. In this study we want to investigate whether the use of narrow-band imaging (NBI) would be capable to rise accuracy of optical polyp predictions compared to standard HD white light endoscopy. NBI is a light filter tool which can be activated by pressing a button at the endoscope. The use of NBI leads to an endoscopic picture which appears blue and enables endoscopists to better assess surface structures and vascular patterns. In a prospective randomised multicenter setting we plan to conduct colonoscopy in 370 patients. Half of the patients will be examined without the use of NBI (control arm). In these cases colonoscopists will assess optical diagnosis of polyps without turning on the NBI tool. If polyps are detected in patients belonging to the intervention arm NBI will be used and optical diagnosis will be determined using the WASP (Workgroup serrAted polypS and Polyposis) classification. All polyps will be resected and send to pathology for further microscopic assessment. After completing the trial we aim to compare accuracy of the optical diagnosis in both groups. Our hypothesis is, that by using NBI accordance between optical and histopathological diagnosis can be increased from 80% to 90%.

Diminutive polyps, measuring between 1 and 5 mm, represent the vast majority of colorectal polyps encountered during colonoscopy. Since the chance of harboring advanced adenoma or carcinoma in this kind of polyps is very low, a "remove and discard" technique has been proposed. The differentiation between adenoma/non adenoma polyps is based on the use of endoscopes equipped with high definition, magnification and optical filters.

Lesions, polyps and other abnormalities in the gastrointestinal (GI) tract have a different composition compared to the normal mucose. The investigators plan to gather spectroscopic information from these features. Characterizing their unique spectrums, may help to enhance the detection and identification of these objects during endoscopy.

Many previous studies had revealed that gastrointestinal microbiome is changed compositionally and ecologically in patients with colorectal cancer comparing with healthy population. These finding provide us with a new sight to take advantage of gut microbiota. The current study aims to explore new potential biomarkers for early screening and prognostic prediction of colorectal cancer and colorectal polyps by analyzing metagenomics and metabolomics of gut microbiota.