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MRI-Based Artificial Intelligence for Surgical Difficulty: Assessing the Effect of Pelvis in Laparoscopic Rectal Surgery

MRI-Based Artificial Intelligence for Surgical Difficulty: Assessing the Effect of Pelvis in Laparoscopic Rectal Surgery

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2200059831
Enrollment
Unknown
Registered
2022-05-12
Start date
2022-04-28
Completion date
Unknown
Last updated
2024-04-01

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

Conditions

Rectal cancer

Interventions

Gold Standard:Surgical diffculty scaling system
Index test:The prediction model established by artificial intelligence

Sponsors

Peking Union Medical College Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 80 Years

Inclusion criteria

Inclusion criteria: 1. Tumor within 12 cm from the anal verge; 2. Adenocarcinoma confirmed by postoperative pathological examinations; 3. Sufficient preoperative MRI data; 4. The depth of tumor invasion was T1-T4a.

Exclusion criteria

Exclusion criteria: 1. Surgical difficulty grade was not rated; 2. Narrow pelvis wasn't the main reason for difficulty; 3. Medical records were incomplete.

Design outcomes

Primary

MeasureTime frame
Surgical difficulty grade;—

Countries

China

Contacts

Public ContactYi Xiao

Peking Union Medical College Hospital

xiaoy@pumch.cn+86 18910598831

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026