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Image Quality Evaluation of Coronary CT Angiography Using Deep Learning-Based Spectral Precise Image Reconstruction

Image Quality Evaluation of Coronary CT Angiography Using Deep Learning-Based Spectral Precise Image Reconstruction

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600120366
Enrollment
Unknown
Registered
2026-03-12
Start date
2026-03-12
Completion date
Unknown
Last updated
2026-03-16

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

Conditions

Data will be collected from patients who underwent spectral coronary CT angiography (CCTA) for suspected coronary artery disease (CAD) or other diagnosis needs as part of their routine clinical evaluation and scanned by Philips Spectral CT 7500.

Interventions

Group A(120kVp, DRI=30):None intervention
GroupB(100kVp, DRI=24):None intervention

Sponsors

The First Affiliated Hospital of Zhengzhou University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 80 Years

Inclusion criteria

Inclusion criteria: 1.Datasets from patients who underwent spectral coronary CT angiography (CCTA). 2.Datasets from study participants with age = 18 years old. 3.Scan parameters that meet the criteria defined in the 5.4.3.

Exclusion criteria

Exclusion criteria: 1.The clinical data information is considered incomplete after evaluation by the investigator. 2.The investigator determined that poor image quality (e.g. obvious artifacts, missing critical scan layers) would not satisfy post-processing analysis. 3.Data of patients deemed inappropriate for inclusion after evaluation by the investigator.

Design outcomes

Primary

MeasureTime frame
Objective image quality,;diagnosis confidence;

Countries

China

Contacts

Public ContactJie Liu

The First Affiliated Hospital of Zhengzhou University

liujieict@163.com+86 13613852079

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Mar 20, 2026