Artificial Intelligence (AI), Colonoscopy Diagnostic Techniques and Procedures, Quality Indicators, Health Care
Conditions
Keywords
Quality Indicators, Colonoscopy, Artificial Intelligence (AI), Computer-aided detection (CADe), Adenoma detection rate (ADR)
Brief summary
Computer-aided detection (CADe) based on artificial intelligence (AI) may improve colonoscopy quality. An increasing number of young endoscopists are trained in an AI environment. However its impact on trainees' future outcomes remains unclear. The study aimed to evaluate the quality indicators of endoscopists trained in an AI environment compared to those trained conventionally.
Detailed description
Computer-aided detection (CADe) based on artificial intelligence (AI) may improve colonoscopy quality. An increasing number of young endoscopists are trained in an AI environment. However its impact on trainees' future outcomes remains unclear. The study aimed to evaluate the quality indicators of endoscopists trained in an AI environment compared to those trained conventionally. A study included 6,000 adult patients who underwent a colonoscopy for various reasons. The study retrospectively evaluated the first 1,000 procedures performed by six endoscopists after completing training relying entirely on endoscopists' detection skills without AI enhancement. Three of those young endoscopists were trained with CADe, and three without additional assistance. Quality indicators were assessed in both groups. The morphology of detected polyps was evaluated to determine the influence of AI-enhanced training on laterally spreading tumors (LST) detection rate.
Interventions
OTHERAI-enhanced endoscopy training
Endoscopists trained in AI-enhanced environment. Their quality indicators are measured after completing training, without additional AI enhancement.
OTHERConventional endoscopy training
Endoscopists trained conventionally
Sponsors
Jagiellonian University
Study design
Observational model
CASE_CONTROL
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* adult participants who underwent a colonoscopy for various reasons performed by specific endoscopists that were assessed in terms of quality indicators
Exclusion criteria
* a history of bowel resection * confirmed inflammatory bowel disease * suspicion of polyps or cancer in other imaging tests * suspicion of familial adenomatous polyposis
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Cecal intubation rate (CIR) | During the colonoscopy examination | The percentage of colonoscopies with successful cecal intubations |
| Serrated polyp detection rate (SDR) | During the colonoscopy examination | The percentage of colonoscopies when the serrated polyp was found |
| withdrawal time | During the colonoscopy examination | The time from the cecal intubation to the end of the examination |
| Adenoma per colonoscopy score (APC) | During the colonoscopy examination | The average number of adenomas detected in a single colonoscopy |
| Adenoma Detection Rate (ADR) | During the colonoscopy examination | The percentage of colonoscopies when the adenoma was found |
| Advanced adenoma detection rate (AADR) | During the colonoscopy examination | The percentage of colonoscopies when the advanced adenoma (>10mm) was found |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Laterally spreading tumor detection rate | During the colonoscopy examination | The percentage of colonoscopies when the laterally spreading tumor lesion was found |
Countries
Poland
Outcome results
None listed