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Evaluation of in stent restenosis by coronary computed tomography flow reserve fraction (CT-FFR) based on deep learning

Evaluation of in stent restenosis by coronary computed tomography flow reserve fraction (CT-FFR) based on deep learning

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2200058822
Enrollment
Unknown
Registered
2022-04-17
Start date
2022-05-01
Completion date
Unknown
Last updated
2024-01-22

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

Conditions

Coronary artery diease

Interventions

A2:After confirming in stent restenosis, invasive FFR was performed during angiography
A1:Perform CCTA scanning and calculate CT-FFR
B1:Guide the treatment strategy according to CCTA + ct-ffr
B2:Guide the treatment strategy according to ICA + FFR

Sponsors

Beijing Anzhen Hospital, Capital Medical University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 80 Years

Inclusion criteria

Inclusion criteria: 1. Patients aged 18-80 years with coronary heart disease developed angina pectoris at least 3 months after stent implantation.

Exclusion criteria

Exclusion criteria: 1. Thrombus in stent; 2. Acute myocardial infarction; 3. Cardiac insufficiency; 4. Severe aortic coarctation; 5. Liver and kidney insufficiency; 6. Pregnant or women of childbearing age; 7. The patient cannot cooperate with CCTA scanning.

Design outcomes

Primary

MeasureTime frame
Diagnostic accuracy rate of in stent restenosis;—

Secondary

MeasureTime frame
Revascularization decision ratio;—

Countries

China

Contacts

Public ContactDongfeng Zhang

Beijing Anzhen Hospital, Capital Medical University

dongfengdoctor@outloook.com+86 15201119937

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: May 8, 2026