NCT06773832
AI in Predicting Polyp Pathology and Endoscopic Classification
Recruiting · Not specified · Peking Union Medical College Hospital · registry updated 2025-01-14
Inclusion and exclusion lines below are quoted from ClinicalTrials.gov. No match score is shown, because a score needs a person's age, biomarkers, and treatment dates. Confirm the record with the study team.
Background: Colonoscopy with optical diagnosis based on the appearance of polyps can guide the selection of endoscopic treatment methods, reduce unnecessary polypectomy procedures and the need for tissue pathological diagnosis, and formulate follow-up strategies in a timely manner \[1\]. This approach significantly alleviates the economic burden on patients and the healthcare system and can effectively ease the tension on clinical resources \[2\]. Various endoscopic polyp classification methods, including Pit Pattern \[3\], NICE \[4\], WASP \[5\], and MS \[6\], are used to determine pathological types. However, mastering these classification methods requires endoscopists to undergo extensive training, and due to the inherent flaws in each method, no single endoscopic classification method can accurately diagnose all types of polyps to meet the requirements of optical diagnosis. This limitation has hindered the widespread application of optical diagnosis in clinical practice \[7\]. The application of artificial intelligence technology in this field, known as computer-aided diagnosis (CADx), has seen rapid development in recent years....
Inclusion
- Outpatients or inpatients undergoing routine colonoscopy screening at the endoscopy centers of multicenter hospitals;
- Aged 18 years or older;
- Have understanding of the study content and have signed the informed consent form.
Exclusion
- Gastroparesis or gastric outlet obstruction;
- Known or suspected intestinal obstruction or perforation;
- Severe chronic renal failure (creatinine clearance less than 30 mL/minute);
- Severe congestive heart failure (New York Heart Association Class III or IV);
- Currently pregnant or breastfeeding;
- Toxic colitis or megacolon;