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An observational diagnostic test study combining deep learning to realize the detection of acute aortic syndrome in non-contrast CT

An observational diagnostic test study combining deep learning to realize the detection of acute aortic syndrome in non-contrast CT

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2400088472
Enrollment
Unknown
Registered
2024-08-20
Start date
2024-08-20
Completion date
Unknown
Last updated
2025-01-13

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

Conditions

Acute Aortic Syndrome

Interventions

Gold Standard:The diagnosis of aortic lesions was made according to the relevant authoritative international guidelines or standards, combined with medical history and relevant examination results.
Index test:The model inference results based on non-contrast CT, the reading results of human doctors alone based on non-contrast CT, and the AI-assisted reading results based on non-contrast CT

Sponsors

The First Affiliated Hospital of Zhejiang University School of Medicine
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1. Presented to the emergency department with nontraumatic acute chest pain; 2. Age >18 years old, male or female;

Exclusion criteria

Exclusion criteria: 1. Initial suspicion of acute aortic syndrome; 2. No CT scan involving the aortic region was performed; 3. Poor CT image quality.

Design outcomes

Primary

MeasureTime frame
Receiver Operating Characteristic curve, ROC;—

Secondary

MeasureTime frame
sensitivity;specificity;Positive predictive value;Negative predictive value;—

Countries

China

Contacts

Public ContactHongkun Zhang

The First Affiliated Hospital of Zhejiang University School of Medicine

1198050@zju.edu.cn+86 135 8823 0962

Outcome results

None listed

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