View clinical trials related to Adenoma.
Filter by:The investigators aim to evaluate the diagnostic accuracy of FIT and the novel panel of four bacterial gene markers collectively named as M3, to detect recurrent advanced adenomas in patients with history of colonic adenomas.
The main purpose of the study to evaluate the usefulness of the Endo-AID artificial intelligence system combined with endocuff compared with endocuff in the detection of colorectal adenomas in consecutive patients for outpatient colonoscopy. The secondary aims were: - To evaluate the benefit of Endo-AID and endocuff in adenoma detection rate by comparing endoscopists with high and low adenoma detection rate. - To evaluate serrated detection rate, advanced adenoma detection rate, adenoma detection rate according to the size (<= 5mm, 6-9mm,> = 10mm) and number of adenomas by colonoscopy. Stratification by location and morphology.
Colonoscopy is considered the gold standard for diagnosis of colonic polyps. However, it was reported that colonoscopy could still miss colonic polyps. Many attempts have been made to improve the detection rate of colonoscopy. Artificial intelligence (AI) is a promising new technique to improve detection rate of colonic adenoma. However, it remains uncertain whether whether the combined use of Endocuff and AI assisted examination could help to further improve the adenoma detection rate. This is a prospective randomized trial comparing the use of endocuff with AI, AI alone or conventional colonoscopy examination on adenoma detection rate.
The purpose of this study is to collect clinical specimens from subjects with a diagnosis of colorectal cancer/advanced adenoma or undergoing a screening colonoscopy and meeting study eligibility criteria.
This is a prospective equivalence colonoscopy study evaluating whether overall adenoma detection rate (ADR) is a reliable alternate for screening ADR. Overall indication includes screening, surveillance, and diagnostic indications.
Refractory pituitary adenoma is characterized by invasive tumor growth, continuous growth and/or hormone hypersecretion in spite of standardized multi-modal treatment such as surgeries, medications or radiations. Quality of life or even lives are threatened by these tumors. According to the 2017 World Health Organization's new classification guideline of pituitary adenoma, patients have to suffer from symptoms or complications caused by these tumors, to bear a heavy financial burden, and to accept additional therapeutic side effects when the diagnosis of "refractory pituitary adenoma" is made. If refractory pituitary adenoma could be predicted at early stage, these patients would be able to have a more frequent clinical follow-up, receive multiple effective treatment as early as possible, or even be enrolled in clinical trials of investigational medications, so as to prevent or delay the recurrence or persistent of the tumor growth. Therefore, the unmet clinical need falls into an early prediction system for refractory pituitary adenomas, which could provide accurate guidance for subsequent treatment in the early stage. The investigators have constructed a pituitary adenoma database including clinical data, radiological images, pathological images and genetic information. The investigators are proposing a study using machine learning to extract features from these multi-dimensional, multi-omics data, which could be further used to train a prediction model for the risk of refractory pituitary adenoma. The proposed model would also be validated in another prospectively collected database. The established model would be able to identify potential medication targets and provide guidance for personalized therapy of refractory pituitary adenoma.
Computer-aided detection (CADe) systems have been actively researched for polyp detection in colonoscopy. The investigators aim to identify the effect of two CADe systems according to the system performance on false positive rate
Nasal packing is required after endoscopic pituitary adenoma resection. The patient can only breathe through the mouth. The blood and secretion in the nasal cavity may be inhaled into the trachea after the operation. GH-secreting pituitary adenoma causes pharyngeal soft tissue and tongue hypertrophy. These conditions increase the risk of respiratory obstruction and hypoxemia during anesthesia recovery. Propofol total intravenous anesthesia has a rapid effect and a low incidence of nausea and vomiting. Patients anesthetized with desflurane recover quickly is conducive to early recovery of respiratory function and orientation. This study intends to compare the effects of desflurane and propofol on the quality of anesthesia recovery period in patients undergoing endonasal endoscopic pituitary adenoma resection and to provide clinical evidence for the use of desflurane in neurosurgical anesthesia.
Retrospective study, single blind (patient), allowing a posteriori clinical data collection of 90 patients during their passage to the ambulatory endoscopy circuit, to consider 3 groups and thus to deduce a colonic adenoma detection rate for each arm : - Colonoscopy Only Group - Artificial intelligence only group (IA GI GENIUS ™ alone) - Endoscopic Cap and Artificial Intelligence Group (endoscopy cap associated with the GI GENIUS ™ IA System)
The purpose of the study is to assess whether the AI characterisation system of the CADDIE device improves the endoscopists accuracy in the optical diagnosis of diminutive colorectal polyps in the bowel during colonoscopy. Participants will either have a colonoscopy with the assistance of the CADDIE device characterisation AI system ("intervention group") or have a colonoscopy in line with routine clinical practice i.e., without the CADDIE device characterisation AI system ("control group"). The randomisation method of this trial will allocate enrolled participants to the "intervention" group and to the "control" group by a technique similar to flipping a coin.