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The impact of a colon polyp detection CAD system based on deep learning on colon adenoma miss rate: a randomized prospective tandem study

The impact of a colon polyp detection CAD system based on deep learning on colon adenoma miss rate: a randomized prospective tandem study

Status
Active, not recruiting
Phases
Unknown
Study type
Interventional
Source
ChiCTR
Registry ID
ChiCTR1900023086
Enrollment
Unknown
Registered
2019-05-10
Start date
2019-06-03
Completion date
Unknown
Last updated
2019-08-27

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

colon polyp

Interventions

CADe-routine colonoscopy:CADe system assits to report colon polyp in the first pass
routine-CADe colonoscopy:CADe system assits to report colon polyp in the second pass

Sponsors

Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 75 Years

Inclusion criteria

Inclusion criteria: adult patients for screening and diagnostic colonoscopy 18-75 years old

Exclusion criteria

Exclusion criteria: 1. history of colon cancer, colon surgery,familial adenomatous polyposis, inflamatory bowel disease, lower intestinal bleeding; 2. Patients with biopsy contraindications; 3. colonoscopy procedures that failed to insert to cecum; 4. difficult procedures(insertion time >7 minutes); 5. with severe complications of cardiovascular and respiratory system and cachexy patients who can stand a long-duration colonoscopy.

Design outcomes

Primary

MeasureTime frame
adenoma miss rate;—

Secondary

MeasureTime frame
polyp miss rate;—

Countries

China

Contacts

Public ContactLiangping Li

Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital

18981838872@163.com+86 18981838872

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 27, 2026