AI-Powered heart scans could sharpen diagnosis
NCT ID NCT07620457
First seen Jun 25, 2026 · Last updated Jun 27, 2026 · Updated 2 times
Summary
This study will test whether a deep learning-based image reconstruction method can improve the quality of coronary CT scans. Researchers will look at existing scans from 200 patients who had a CT angiogram for suspected heart disease. Two radiologists will rate the images on a scale of 1 to 5 to see if the new method makes them clearer.
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 successful, this could lead to clearer heart CT scans, helping doctors diagnose coronary artery disease more accurately.
- What could go wrong
- This is an early observational study, not a treatment trial. The new image reconstruction may not improve diagnosis in practice.
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
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About 200 people
The number the study aims to enrol. It can still change while the study runs.
- Expected to start
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Jun 2026
An estimate. Start dates often move.
- Expected to finish
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Dec 2026
An estimate. End dates often move.
- Lead sponsor
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A company
The lead sponsor is a pharmaceutical, biotech, or medical-device company.
Who can take part
This study's own entry requirements. Only the study team can say for certain whether you qualify.
Who is studied
Patients completed CCTA scan aged 18.
- Ages
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18 years and older
- Sex
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Anyone
- Healthy volunteers
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Accepted
You do not need to have the condition being studied to take part.
Show the full entry requirements Hide 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. 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: 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.
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Conditions
The condition(s) this trial relates to.
As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.
How to take part
Only the study team decides who joins. These are the ways to reach them.
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The places running it
1 site. The list below names each one and where it is.
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The official record
ClinicalTrials.gov lists the study team's own contact details, including names and phone numbers. We don't republish those.
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A doctor treating you
A doctor who knows your case can contact a study site on your behalf, and can tell you whether this study is worth pursuing at all.
Contacts and locations
Locations
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Zhengzhou Universtidy 1st Affiliated Hospital
Zhengzhou, Henan, China
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