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Can AI read heart scans to predict the next heart attack?

NCT ID NCT07832175

NEW Diagnosis Sponsor: Nanjing First Hospital, Nanjing Medical University Source: ClinicalTrials.gov ↗

What the study statuses mean

This study's is highlighted.

Recruitment status, easiest to join first

Recruiting now
This trial is taking on new participants right now.
Not yet recruiting
Registered, but not yet taking participants.
By invitation only
Not open to general applications. Only people the study team invites can take part.
Paused
Paused for now. It may or may not start again.
Ongoing This study
Running, but no longer taking on new participants.
Completed
The trial has finished. Results may not be published yet.
Stopped early
Stopped early, before it reached the end. That can be for many reasons, including safety.
Cancelled
Cancelled before anyone took part.

Expanded access (not trials)

Expanded access
Not a trial. This treatment can be requested outside a study, case by case, for people who qualify.
Expanded access (paused)
Not a trial. The treatment can normally be requested outside a study, but is unavailable right now.
Expanded access (ended)
Not a trial. The treatment could once be requested outside a study, but no longer can.
Approved
The treatment has been approved, so it is available normally rather than through this programme.

When the status isn't known

Details not published
The full record has not been published yet, so there is little to show here.
Status unknown
This status has not been confirmed recently, so it may be out of date.

First seen Sep 21, 2026 · Last updated Sep 21, 2026

Summary

Researchers are studying whether artificial intelligence can extract useful warning signs from coronary CT angiography (CCTA) scans in people with coronary artery disease. The study reviews existing medical records from 3,000 patients across five hospitals who had both a CCTA and an invasive coronary angiogram within 90 days. The team compares different AI software platforms and checks whether AI-derived measurements, such as plaque features and blood flow estimates, are linked to heart attacks and other cardiac events over the following two years.

What this could mean

Our plain-language read of the trial. This is informational only, not medical advice or a prediction.

What this could lead to
If the approach works, doctors could use AI-read CT scans to spot which patients with coronary artery disease face the highest risk of future heart attacks and tailor their care accordingly.
What could go wrong
This is a retrospective study of existing records, so it can show patterns but cannot prove that acting on AI scan results improves outcomes. The findings may not apply to patients outside the five hospitals studied.

This is an AI summary of the original study and may miss details. Read our disclaimer.

Study facts

What this study's own registry entry says, in plain language.

Participants

About 3,000 people

The number the study aims to enrol. It can still change while the study runs.

Started

Jun 2026

Expected to finish

Oct 2026

An estimate. End dates often move.

Lead sponsor

Other sponsor

The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Who is studied

This multicenter retrospective registry evaluates AI-derived CCTA metrics in 3,000 adults with suspected or confirmed CAD undergoing CCTA and ICA within 90 days across six Chinese tertiary centers. Inclusion criteria: age ≥18 years, ≥12 months follow-up. AI platforms will quantify stenosis, high-risk plaque, CT-FFR, and pericoronary FAI. Baseline demographics, cardiovascular risk factors, biomarkers (lipids, hs-CRP, NT-proBNP), and pharmacotherapies will be assessed. The primary endpoint is MACE over a median 2-year follow-up. Secondary objectives include comparing AI diagnostic accuracy against ICA/QFR and assessing the modifying effects of lipid-lowering intensity and antiplatelet regimens on prognostic stratification. This study aims to establish an integrated anatomical-functional-inflammatory framework for personalized CAD management.

Ages

18 years and older

Sex

Anyone

Healthy volunteers

Not accepted

This study is not open to healthy volunteers. The entry requirements below say who it is open to.

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

Inclusion Criteria: 1. Age ≥18 years at the time of index coronary CT angiography (CCTA). 2. Clinically suspected or confirmed coronary artery disease (CAD). 3. Underwent both CCTA and invasive coronary angiography (ICA) within 90 days. 4. Availability of clinical follow-up data for at least 12 months after the index CCTA. 5. Sufficient image quality of CCTA and ICA to allow AI-based analysis and quantitative assessment. 6. Signed informed consent or waiver of informed consent approved by the Institutional Review Board (IRB). Exclusion Criteria: 1. Age \<18 years. 2. Poor CCTA image quality precluding reliable AI analysis (e.g., severe motion artifacts, inadequate contrast opacification). 3. History of prior coronary artery bypass grafting (CABG). 4. Follow-up duration \<12 months or incomplete follow-up records. 5. Known hypersensitivity to iodinated contrast media, hyperthyroidism, severe hepatic or renal dysfunction (eGFR \<30 mL/min/1.73m²), or malignancy. 6. Pregnancy or lactation at the time of CCTA. 7. Incomplete or missing core baseline data (e.g., lack of CCTA/ICA images, key clinical variables, or lipid profiles).

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Conditions

The condition(s) this trial relates to.

atherosclerosis atherosclerotic cardiovascular disease coronary artery disorder

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Atherosclerotic cardiovascular disease Coronary artery disease

Contacts and locations

Locations

  • Nanjing First Hospital, Nanjing Medical University

    Nanjing, Jiangsu, 210006, China

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Other studies related to the condition(s) this trial covers.