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MRI-based Deep learning model preoperatively predict microsatellite instability status in rectal cancer

MRI-based Deep learning model preoperatively predict microsatellite instability status in rectal cancer

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2000029372
Enrollment
Unknown
Registered
2020-01-26
Start date
2020-01-31
Completion date
Unknown
Last updated
2020-02-03

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:pathology results
Index test:deep learning

Sponsors

West China Hospital, Sichuan University
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1. Pathology confirmed rectal adenocarcinoma; 2. Rectal MRI was performed within 2 weeks before surgery.

Exclusion criteria

Exclusion criteria: 1. without MSI testing; 2. receiving chemoradiotherapy before MR examination; 3. small tumors (< 5mm) hard to identify on images; 4. insufficient T2WI quality to draw region of interest(ROI).

Design outcomes

Primary

MeasureTime frame
microsatellite instability status;SEN, SPE, ACC, AUC of ROC;—

Countries

China

Contacts

Public ContactBin Song

West China Hospital, Sichuan University

songlab_radiology@163.com+86 28 85423680

Outcome results

None listed

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