Application of deep learning-based 3D reconstruction of magnetic resonance imaging in membrane anatomy-based surgical planning for rectal cancer

Status

Recruiting

Phases

Early Phase 1

Study type

Observational

Source

ChiCTR

Registry ID

ChiCTR2500097606

Enrollment

Unknown

Registered

2025-02-21

Start date

2025-02-24

Completion date

Unknown

Last updated

2025-02-24

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:The results of intraoperative exploration (determine the membrane anatomy classification based on the local staging of rectal tumors and the anatomical relationship between the tumor and

Index test:Deep learning-based 3D reconstruction of magnetic resonance imaging predicts membrane anatomical classification before surgery

Eligibility

Sex/Gender

All

Age

18 Years to 80 Years

Inclusion criteria

Inclusion criteria: 1. Pathologically confirmed rectal cancer; 2. No distant metastasis; 3. Rectal magnetic resonance imaging was performed before surgery; 4. Complete clinical data and follow-up data.

Exclusion criteria

Exclusion criteria: 1. History of previous pelvic surgery; 2. Those who were unable to complete rectal magnetic resonance imaging, or those with poor imaging quality.

Design outcomes

Primary

Measure	Time frame
Sensitivity;Specificity;	—

Countries

China

Contacts

Public ContactHailong Liu

Yangpu Hospital, Tongji University School of Medicine, Shanghai

hailongliu81@163.com+86 21 5566 9260

Outcome results

None listed

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