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Artificial intelligence for coronary artery disease screening using routine chest CT

Deep learning-based opportunistic screening of coronary artery disease on non-contrast chest CT: a multicenter study

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500112910
Enrollment
Unknown
Registered
2025-11-20
Start date
2025-11-28
Completion date
Unknown
Last updated
2025-11-24

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

Conditions

Coronary artery disease (CAD)

Interventions

Coronary artery calcification:None
Coronary artery stenosis:None

Sponsors

The First Affiliated Hospital of Zhejiang Chinese Medical University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1.Age >=18 years; 2.Both non-contrast chest CT and coronary CTA performed within 30 days; 3.Coronary segments clearly visualized on non-contrast chest CT with diagnostic-quality CCTA images.

Exclusion criteria

Exclusion criteria: 1.Motion, metal, or stent artifacts precluding analysis; 2.Severely small vessel diameter or complete calcification obscuring lumen; 3.Inability to achieve accurate segment matching between non-contrast chest CT and CCTA.

Design outcomes

Primary

MeasureTime frame
Significant stenosis (>=50%) prediction accuracy;Plaque composition prediction accuracy;—

Countries

China

Contacts

Public ContactYifan Guo

The First Affiliated Hospital of Zhejiang Chinese Medical University

20193071@zcmu.edu.cn+86 571 87077272

Outcome results

None listed

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