AI-driven prediction of non-target coronary lesion progression after PCI
Official title: DeVelopment of an Artificial Intelligence-Driven Dynamic Prediction and Precision Stratification System for Coronary Non-Target LesIon ProgressiON After Percutaneous Coronary Intervention: A Multimodal Data-Enabled Multicenter Cohort Study in China
Run by China-Japan Friendship Hospital · NCT07312318 · Data updated 2026-11-12
This project will test an AI tool that uses clinical data, blood biomarkers, and coronary imaging to see if it can predict which adults treated with PCI are likely to have progression of non-target coronary lesions.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 12000 (estimated) |
| Sponsor | China-Japan Friendship Hospital Academic / other |
| Locations | 1 site (Beijing, Beijing Municipality) |
| Status | Recruiting |
| Started | September 1, 2025 |
| Main results expected | August 31, 2026 |
| Study ends | August 31, 2026 |
| Registry record updated | December 31, 2025 |
| Trial ID | NCT07312318 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Adults aged 18 or older who are scheduled for or have undergone PCI, can provide a baseline plasma sample, and are able to give informed consent are appropriate candidates.
✕Probably not a fit
People who are pregnant or breastfeeding, have severe hepatic or renal dysfunction, active autoimmune disease, missing critical data, or who cannot attend participating Chinese centers are unlikely to benefit from this prediction-focused effort.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This multicenter observational cohort will combine clinical records, coronary imaging, and multi-omics blood biomarkers from over 52,000 Chinese patients who have undergone or are scheduled for PCI to build predictive models of non-target lesion (NTL) progression. Researchers plan to identify 2–3 blood biomarkers associated with future NTL progression and integrate those markers with imaging and clinical features. Machine learning models will be trained and validated on longitudinal follow-up data to generate a dynamic risk stratification and early-warning system. The work aims to produce a precision prediction tool for monitoring and guiding care rather than testing a therapeutic intervention.
Why it matters
Potential benefit: If successful, this could help identify patients at higher risk of lesion progression earlier so they can receive closer monitoring or targeted interventions to reduce future major cardiac events.
How similar studies have gone: Prior smaller AI and imaging studies have shown promise for predicting coronary events after PCI, but combining large-scale multi-omics, imaging, and clinical data in this way is relatively novel and not yet proven at scale.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: 1. Aged 18 years or older; 2. Scheduled for or having undergone PCI; 3. Baseline plasma sample obtainable; 4. Informed consent obtained Exclusion Criteria: 1. Pregnancy or lactation; 2. Severe hepatic or renal dysfunction; 3. Active autoimmune disease; 4. Missing critical data
Where it's running
-
China-Japan Friendship Hospital
Beijing, Beijing Municipality, China Recruiting
Study contacts
- Principal investigator: Fang Wang — China-Japan Friendship Hospital
- Study coordinator: Fang Wang
- Email: wangfang@cjfh.org.cn
- Phone: +86 13683173633
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.