NCT06623331

The Implementation of Computer-aided Detection in Training Improves the Quality of Future Colonoscopies

The Implementation of Computer-aided Detection in an Initial Endoscopy Training Improves the Quality Measures of Trainees' Future Colonoscopies

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 6,000 (actual)
• Sponsor: Jagiellonian University · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

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.

Conditions

• Quality Indicators, Health Care
• Colonoscopy Diagnostic Techniques and Procedures
• Artificial Intelligence (AI)

Interventions

Type	Name	Description
OTHER	AI-enhanced endoscopy training	Endoscopists trained in AI-enhanced environment. Their quality indicators are measured after completing training, without additional AI enhancement.
OTHER	Conventional endoscopy training	Endoscopists trained conventionally

Timeline

• Start date: 2022-01-01
• Primary completion: 2024-01-31
• Completion: 2024-03-31
• First posted: 2024-10-02
• Last updated: 2025-01-17

Locations

1 site across 1 country: Poland