An interventional study of Standard high-definition colonoscopy and Colonoscopy with real-time AI assisted automated polyp detection in Colorectal Neoplasms, Colon Polyp and Colon Adenoma, sponsored by Instituto Ecuatoriano de Enfermedades Digestivas. Status unknown at 1 site in Ecuador. Open to participants aged 45 Years to 80 Years. Per ClinicalTrials.gov, last updated 2022-03-31.
Sponsored by Instituto Ecuatoriano de Enfermedades Digestivas · Not applicable, Interventional, and Diagnostic
Evaluation of the colonic mucosa with a high definition colonoscope (EPKi7010 video processor).
The endoscopy images will be seen on a 27inch, flat-panel, high-definition LCD monitor (Radiance™ ultraSC-WU27-G1520 model) only by one expert endoscopist, randomly assigned.
The number, location, and polyps' features (Paris classification) will be recorded by the operator. If a polyp is detected, the endoscopist will remove the polyp endoscopically with a cold snare.
The same patient will be submitted to a second, the same session, computed aided real-time colonoscopy using the DISCOVERY, AI-assisted polyp detector. Colonoscopy will be performed by a same-level-of-expertise operator in comparison to the initial procedure. Any polyp or lesion detected with the AI system will be recorded and endoscopically removed and considered as a missed lesion from standard colonoscopy.
Screening colonoscopy has decreased the incidence of colorectal carcinoma in the previous decades. However, there are reports of missed polyps and interval CRC following screening colonoscopy. Several factors may affect the ADR, PDR, and missed lesions rates, such as bowel preparation, percentage of mucosal surface evaluation, and the training levels of operators.
Artificial intelligence using deep-learning algorithms has been implemented in gastrointestinal endoscopy, mainly for the detection and diagnosis of GI tract lesions such as colonic polyps and adenomas. The implementation of automated polyp detection software during screening colonoscopy may prevent the missing of polyp and adenoma during screening colonoscopy. Therefore, improving the ADR and PDR during colonoscopies. All of this, with the aim of decrease the incidence of interval colorectal carcinoma (CRC), and CRC-related morbidity and mortality.
The Discovery Artificial Intelligence assisted polyp detector (Pentax Medical, Hoya Group) was recently launched for clinical practice. This AI software was trained with 120,000 files from approximately 300 clinical cases. The visual aided detection (bounding box locating a polyp on the monitor) will alert the endoscopist if a polyp/adenoma was missed during the standard, screening procedure.
To the best of our knowledge, this may be the first study evaluating the Discovery AI-assisted polyp detector on clinical practice in the western hemisphere. The investigators aim to evaluate the real-world effectiveness of AI-assisted colonoscopy in clinical practice. The investigators will also evaluate the role of endoscopists' levels of training in the ADR, PDR, and missed lesion rate.
5,734 studies on the registry are indexed under Colorectal Neoplasms; 1,481 are open to participants now.
This study's planned enrollment of 209 is above the median of 77 across 4,222 interventional studies indexed under Colorectal Neoplasms.
Browse Colorectal Neoplasms studies →Instituto Ecuatoriano de Enfermedades Digestivas is the lead sponsor of 39 studies on the registry; 10 are open to participants now.
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Exclusion Criteria:
Consecutive patients \>45 years of age submitted for diagnostic colonoscopy
Diagnostic Test: Standard high-definition colonoscopy · Diagnostic Test: Colonoscopy with real-time AI assisted automated polyp detection
Evaluation of the colonic mucosa with a high definition colonoscope (EPKi7010 video processor). The endoscopy images will be seen on a 27inch, flat panel, high-definition LCD monitor (Radiance™ ultraSC-WU27-G1520 model) only by one expert endoscopist, randomly assigned. The number, location and polyps' features (Paris classification) will be recorded by the operator. If a polyp is detected, the endoscopist will remove the polyp endoscopically with a cold snare and forceps biopsy.
The same patient will be submitted to a second, same session, computed aided real-time colonoscopy using the DISCOVERY, AI assisted polyp detector. Colonoscopy will be performed by a same-level-of-expertise operator in comparison to the initial procedure. Any polyp or lesion detected with the AI system will be recorded and endoscopically removed and considered as a missed lesion from standard colonoscopy.
Adenoma detection rate of computer-aided after standard colonoscopy.
Number of examinations with at least one adenoma detected during colonoscopy while using the AI-based model
Time frame: 30 days
Polyp detection rate of computer-aided following standard colonoscopy.
Number of examination with at least one polyp detected while using the AI-based model
Time frame: 30 days
Polyp miss rate of standard high-definition colonoscopy.
Total number of missed polyps/ (total number of missed polyps + total number of polyps on initial examination)
Time frame: 30 days
Adenoma miss rate of standard high-definition colonoscopy.
Total number of missed adenomas/ (total number of missed adenomas + total number of adenomas on initial examination)
Time frame: 30 days
Plan to share: No
This study is status unknown, as verified in Mar 2022. You cannot join it, but the record below documents what was studied.
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Instituto Ecuatoriano de Enfermedades Digestivas