View clinical trials related to Polyps.
Filter by:This study is intended to observe the therapeutic effect of dydrogesterone on endometrial polyps and provide a reference for clinical treatment.
Our group, prior to the present study, developed a handcrafted predictive model based on the extraction of surface patterns (textons) with a diagnostic accuracy of over 90%24. This method was validated in a small dataset containing only high-quality images. Artificial intelligence is expected to improve the accuracy of colorectal polyp optical diagnosis. We propose a hybrid approach combining a Deep learning (DL) system with polyp features indicated by clinicians (HybridAI). A pilot in vivo experiment will carried out.
Recently, artificial intelligence (AI) assisted image recognition has made remarkable breakthroughs in various medical fields with the developing of deep learning and conventional neural networks (CNNs). However, all current AI assisted-diagnosis systems (ADSs) were established and validated on endoscopic images or selected videos, while its actual assisted-diagnosis performance in real-world colonoscopy is up to now unknown. Therefore, we validated the performance of an ADS in real-world colonoscopy, which is based on deep learning algorithm and CNNs, trained and tested in multicenter datasets of 20 endoscopy centers.
This study is a prospective randomized study to evaluate the role of NBI for improving complete resection rate of sessile serrated adenoma/polyp (SSA/P). The authors will enroll consecutive patients who underwent colon polypectomy for SSA/P during colonoscopy. The authors will inspect resection margin of SSA/P using white light endosocpy (WLE) or NBI after randomization for the evaluation of remnant lesion. Additional resection will be performed for suspicious of remnant lesion, and then 4 biopsies from 4 quadrants of margin for evaluation of complete resection.
The goal of this study is to evaluate the interest of second-generation Endocuff Vision (ECV) to improve Adenoma detection rate and / or Polyp detection rate in routine colonoscopy. This is a prospective comparative cohort, on 1034 patients, 517 patients with ECV in prospective group and 517 without ECV in retrospective group
All procedures are performed in the investigator's outpatient gastroenterology and digestive endoscopy unit by experienced endoscopists in conventional mucosectomies of the lower intestinal tract. Before the procedure each patient, a normal endoscopic procedure. At the site of the lesion the lumen will be completely decompressed with aspiration of the gas, and then again relaxed with the instillation of only water. The EleviewTM will be injected into the submucosa in such quantities as to obtain a satisfactory lift of the lesion. The lesion will then be removed with a diathermic loop, preferably en-bloc, and in any case up to macroscopic evidence of complete resection. All the removed material will be stored and sent to histological analysis. Tolerability score will be recorded during the procedure. Any "bleeding" (both intra- and post-procedural), perforation, post-polypectomy syndrome, stenosis or death in the 6 months following the procedure will be born "complication". A surveillance colonoscopy including biopsy sampling of the research site scheduled 6 months after the procedure
Several imaging technologies have been developed in order to enable the endoscopists to differentiate neoplastic from non-neoplastic lesions. The real-time prediction of polyps histology is clinically relevant as diminutive polyps represent the majority of polyps detected during colonoscopy and have a very low risk of harboring advanced histology or invasive carcinoma. Thus, an optical diagnosis would allow diminutive polyps to be resected and discarded without pathological assessment or left in place without resection, with an enormous cost-saving potential. Recently, the American Society of Gastrointestinal Endoscopy (ASGE) has set the Preservation and Incorporation of Valuable endoscopic Innovation (PIVI) which defined accuracy threshold to be met, in order to consider a new technology ready to be incorporate into clinical practice. Blue Light Imaging (BLI) is a new chromoendoscopy technology integrated in the latest generation ELUXEOTM 7000 endoscopy platform (Fujifilm Co, Tokyo, Japan), based on the direct (i.e. not filtered) emission of blue light with short wavelength (410nm), that enhances visibility of both microvascular and superficial mucosal pattern. In a recent randomized trial BLI was superior to high-definition white light (HDWL) in the real time characterization of subcentimetric and diminutive colonic polyps. Nevertheless, in this study the paucity of diminutive rectosigmoid polyps analyzed does not allow to draw definite conclusions as the meeting of PIVI thresholds are concerned. Similarly, the low numbers of patients evaluated limited the per-patient analysis. Therefore further studies adequately powered to this clinically end-point were advocated. Additionally, when the study was performed a BLI dedicated classification for optical diagnosis of colonic polyps was not available, whereas recently a specific classification (the BLI Adenoma Serrated International Classification-BASIC) has been developed and a specific training set has been settled. In the present study the investigators prospectively evaluate whether the use of BLI-assisted optical characterization of diminutive polyps using BASIC classification by specifically trained endoscopists may met PIVI thresholds and particularly if it allow the endoscopists to achieve > 90% correct assignment of post-polypectomy surveillance intervals when combined with the histopathology assessment of polyps >5 mm in size.
This study has three main purposes：screening: the first purpose is to evaluate the diagnostic value of combintion of the life risk factors and immunochemical fecal occult blood test (FIT) on detection of colorectal neoplasia in Chinese population; resection: the second objective is to investigate the complete resection rate of colorectal adenoma and risk factors of incomplete resection in China; identification and classification: the third objective is to initially establish an artificial intelegence-assissted recognition and classification system of polyp based on deep learning.
Freenome is using a type of artificial intelligence, called machine learning, to identify patterns of cell-free biomarkers in blood to detect cancer early. The purpose of this study is to develop and validate a blood-based assay to detect colorectal cancer by collecting blood and stool samples from healthy patients undergoing routine screening colonoscopy and from patients recently diagnosed with colorectal cancer or advanced adenomas.
A Phase 3b Proof-of-Concept study to evaluate the ability of fevipiprant 150 mg and 450 mg, compared with placebo, as add-on to nasal spray standard-of-care (SoC), in reducing endoscopic nasal polyp score in adult (≥ 18 years) patients with nasal polyposis and concomitant asthma.