Skip to content

Development and Application of an Artificial Intelligence–Based Imaging-Assisted Diagnostic System for Gastric Cancer Using Automatic Lesion Detection and Segmentation Technology

Development and Application of an Artificial Intelligence–Based Imaging-Assisted Diagnostic System for Gastric Cancer Using Automatic Lesion Detection and Segmentation Technology

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500112205
Enrollment
Unknown
Registered
2025-11-11
Start date
2025-11-20
Completion date
Unknown
Last updated
2025-11-17

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

Conditions

Patients diagnosed with gastric adenocarcinoma

Interventions

Index test:An Artificial Intelligence–Based Imaging-Assisted Diagnostic System for Gastric Cancer Using Automatic Lesion Detection and Segmentation Technology

Sponsors

Beijing Cancer Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 90 Years

Inclusion criteria

Inclusion criteria: 1.patients with gastric adenocarcinoma confirmed by endoscopic pathology; 2.For patients undergoing direct surgery, contrast-enhanced abdominal CT is performed preoperatively to obtain DICOM imaging files; for patients receiving preoperative drug treatment, DICOM imaging data are collected both before and after neoadjuvant chemotherapy; 3.CT with adequate gastric distension; 4.No previous gastric surgery; 5.Complete follow-up information available;

Exclusion criteria

Exclusion criteria: 1.Fewer than 15 lymph nodes dissected; 2.Lacking clinical information and follow-up data;

Design outcomes

Primary

MeasureTime frame
Sensitivity;Accuracy;

Secondary

MeasureTime frame
Specificity;

Countries

China

Contacts

Public ContactZiyu Li

Beijing Cancer Hospital

ligregory@outlook.com+86 10 8819 6605

Outcome results

None listed

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