Artificial Intelligence - Based Opportunistic Coronary Artery Calcium Scoring on Routine Chest-CT Scan

September 1, 2026 updated by: Volker Burst, University of Cologne

Opportunistic Screening of Coronary Artery Calcium on Non-Gated Routine Chest CT Using Artificial Intelligence: Retrospective External Validation and Clinical Risk Stratification

This retrospective, non-interventional study externally validates a pre-trained open-weight deep-learning algorithm (Swin-UNETR) for the opportunistic quantification of coronary artery calcium (CAC) on non-gated routine chest CT scans acquired at a German academic center, and evaluates the prognostic value of this automated imaging biomarker for cardiovascular risk stratification. Coronary calcium is an established predictor of cardiovascular risk, but is not routinely quantified on the tens of thousands of non-cardiac chest CTs performed each year. Because existing high-performing AI models were trained almost exclusively on U.S. cohorts, external validation on a European scanner fleet is required to exclude scanner bias (domain shift). The study comprises three linked analytic cohorts: (1) a validation cohort comparing the AI-CAC score against the ECG-gated cardiac CT Agatston reference; (2) a dialysis cohort assessing calcification progression and mortality; and (3) an emergency department cohort assessing short-term cardiovascular events. This is an investigator-initiated trial with no intervention on patients.

Study Overview

Status

Status

Indicates the current recruitment status or the expanded access status.
Not yet recruiting

Conditions

Conditions

The disease, disorder, syndrome, illness, or injury that is being studied. On ClinicalTrials.gov, conditions may also include other health-related issues, such as lifespan, quality of life, and health risks.

Detailed Description

The study analyzes a retrospective cohort of routine clinical CT examinations at University Hospital Cologne. Data originate from the hospital information system and Picture Archiving and Communication System (PACS) and are provided in pseudonymized form via the Medical Data Integration Center (MeDIC), acting as an independent trusted third party; the re-identification key remains under the sole control of MeDIC. Deep-learning inference is performed locally on isolated, access-controlled graphics processing unit (GPU) clusters of the institution (privacy by design / zero data retention); an open-weight model (Swin-UNETR) is used.

Three research questions are addressed in three analytic cohorts:

  • Validation (n ≈ 150): diagnostic agreement of the automatically extracted AI-CAC score (from the non-gated CT) with the reference Agatston score from a paired ECG-gated cardiac CT acquired within ≤ 12 months.
  • Dialysis (n ≈ 300): 150 hemodialysis patients plus 150 matched kidney-healthy controls with serial non-gated CTs; annualized calcification progression rate and all-cause mortality.
  • Emergency department (n ≈ 1,500): patients > 50 years with non-gated chest CTs from the Emergency Department (without a primary cardiac focus); occurrence of in-hospital major adverse cardiac event (MACE) or cardiovascular readmission within 12 months.

Extracted data include demographics (age at examination, sex), cardiovascular risk factors and comorbidities (ICD-10), long-term medication, laboratory values, examination metadata (date, scanner manufacturer, kilovolt peak (kVp), slice thickness), and outcome data (mortality, cardiovascular events, readmissions). Statistical analysis uses Spearman correlation, Cohen's kappa and Bland-Altman analysis for method comparison; t-test / Mann-Whitney-U for group differences in progression; and Kaplan-Meier (log-rank) plus multivariable Cox proportional-hazards and logistic regression for outcome prediction. Legal basis: § 6 (1) no. 2 Health Data Use Act of Germany (GDNG) in conjunction with Art. 9 (2) (j) and Art. 89 (1) GDPR (research privilege); no individual consent (disproportionate effort, Art. 14 (5) (b) GDPR). The AI (artificial intelligence) model carries no CE-marking and is used strictly as a research tool; AI-CAC scores are not systematically fed back into clinical care.

Study Type

Study Type

Describes the nature of a clinical study. Study types include interventional studies (also called clinical trials), observational studies (including patient registries), and expanded access.
Observational

Enrollment (Estimated)

Enrollment

The number of participants in a clinical study. The "anticipated" enrollment is the target number of participants that the researchers need for the study.
1950

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact

The name and contact information for the person who can answer enrollment questions for a clinical study. Each location where the study is being conducted may also have a specific contact, who may be better able to answer those questions.

Study Contact Backup

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Eligibility Criteria

The key requirements that people who want to participate in a clinical study must meet or the characteristics they must have. Eligibility criteria consist of both inclusion criteria (which are required for a person to participate in the study) and exclusion criteria (which prevent a person from participating). Types of eligibility criteria include whether a study accepts healthy volunteers, has age or age group requirements, or is limited by sex.

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

Retrospective patients at University Hospital Cologne with routine clinical CT imaging (01 January 2015 - 31 December 2025), across three analytic cohorts (validation, dialysis, emergency department); approximately 1,950 cases.

Description

Inclusion Criteria:

  • Validation cohort: patients with a paired non-gated chest CT and an ECG-gated cardiac CT acquired within ≤ 12 months.
  • Dialysis cohort: hemodialysis patients with serial non-gated CTs, plus matched kidney-healthy controls.
  • Emergency department cohort: patients > 50 years with non-gated chest CTs from the Emergency Department without a primary cardiac focus.

Exclusion Criteria:

  • Documented objection to the scientific use of the data pursuant to Art. 21 GDPR.
  • Cases lacking the minimum data required for analysis (insufficient image quality or missing reference/outcome data).

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort

Group / Cohort

A group or subgroup of participants in an observational study that is assessed for biomedical or health outcomes.
Validation Cohort
Paired non-gated chest CT and ECG-gated cardiac CT (≤ 12 months apart). AI-CAC score compared against the reference Agatston score. n ≈ 150.
Dialysis Cohort
150 hemodialysis patients plus 150 matched kidney-healthy controls with serial non-gated CTs. Calcification progression and all-cause mortality. n ≈ 300.
Emergency Department Cohort
Patients > 50 years with non-gated chest CTs from the emergency department without primary cardiac focus. In-hospital MACE / cardiovascular readmission within 12 months. n ≈ 1,500

What is the study measuring?

Primary Outcome Measures

Primary Outcome Measures

In a clinical study's protocol, the planned outcome measure that is the most important for evaluating the effect of an intervention/treatment. Most clinical studies have one primary outcome measure, but some have more than one.
Outcome Measure
Measure Description
Time Frame
Diagnostic agreement of the AI-CAC score with the reference Agatston score
Time Frame: At the index non-contrast chest CT (Day 0) and at the paired ECG-gated cardiac CT obtained within 12 months after the index CT.
Agreement between the automatically extracted AI-CAC score from the non-gated chest CT and the reference Agatston score from a paired ECG-gated cardiac CT, reported as Spearman correlation coefficient, Cohen's kappa across established risk classes (0, 1-100, 101-400, > 400), and Bland-Altman limits of agreement; supplemented by sensitivity, specificity, positive predictive value(PPV)/negative predictive value(NPV) and F1 score
At the index non-contrast chest CT (Day 0) and at the paired ECG-gated cardiac CT obtained within 12 months after the index CT.
Annualized calcification progression rate and all-cause mortality
Time Frame: From the index non-contrast chest CT (Day 0) through the last available serial non-gated chest CT and the end of individual follow-up, up to 10 years per participant.
Difference in the mean annual increase in AI-CAC between hemodialysis patients (dialysis cohort) and matched kidney-healthy controls measured on serial non-gated CTs (t-test / Mann-Whitney-U), and all-cause mortality analyzed by Kaplan-Meier (log-rank) and multivariable Cox proportional-hazards models (hazard ratios adjusted for confounders
From the index non-contrast chest CT (Day 0) through the last available serial non-gated chest CT and the end of individual follow-up, up to 10 years per participant.
In-hospital Major Adverse Cardiac Event or cardiovascular readmission within 12 months (Emergency Department cohort).
Time Frame: 12 months after the index emergency department visit
Occurrence of in-hospital Major Adverse Cardiovascular Events (myocardial infarction, stroke, resuscitation) or cardiovascular readmission within 12 months of the index Emergency Department visit, in relation to an unrecognized high AI calcium score (> 400); reported as adjusted odds ratios and hazard ratios from logistic regression and Cox models
12 months after the index emergency department visit

Secondary Outcome Measures

Secondary Outcome Measures

In a clinical study's protocol, a planned outcome measure that is not as important as the primary outcome measure for evaluating the effect of an intervention but is still of interest. Most clinical studies have more than one secondary outcome measure.
Outcome Measure
Measure Description
Time Frame
Technical feasibility and inference time of the open-source AI model on local GPU clusters
Time Frame: At the index non-contrast chest CT (Day 0)
Inference time per case and technical feasibility of running the open-weight deep-learning model (Swin-UNETR) as an isolated container on the institution's local GPU infrastructure
At the index non-contrast chest CT (Day 0)

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Sponsor

The organization or person who initiates the study and who has authority and control over the study.
University of Cologne

Collaborators

Collaborators

An organization other than the sponsor that provides support for a clinical study. This support may include activities related to funding, design, implementation, data analysis, or reporting.
Institute for Diagnostic and Interventional Radiology, University Hospital Cologne
Medical Data Integration Center (MeDIC), University Hospital Cologne

Investigators

Investigators

A researcher involved in a clinical study. Related terms include site principal investigator, site sub-investigator, study chair, study director, and study principal investigator.
  • Principal Investigator: Cem Özel, MD, Department of Internal Medicine II, University Hospital Cologne

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

Study Start

The actual date on which the first participant was enrolled in a clinical study. The "anticipated" study start date is the date that the researchers think will be the study start date.
November 1, 2026

Primary Completion (Estimated)

Primary Completion

The date on which the last participant in a clinical study was examined or received an intervention to collect final data for the primary outcome measure. Whether the clinical study ended according to the protocol or was terminated does not affect this date. For clinical studies with more than one primary outcome measure with different completion dates, this term refers to the date on which data collection is completed for all the primary outcome measures. The "anticipated" primary completion date is the date that the researchers think will be the primary completion date for the study.
November 1, 2027

Study Completion (Estimated)

Study Completion

The date on which the last participant in a clinical study was examined or received an intervention/treatment to collect final data for the primary outcome measures, secondary outcome measures, and adverse events (that is, the last participant's last visit). The "anticipated" study completion date is the date that the researchers think will be the study completion date.
December 1, 2027

Study Registration Dates

First Submitted

First Submitted

The date on which the study sponsor or investigator first submitted a study record to ClinicalTrials.gov. There is typically a delay of a few days between the first submitted date and the record's availability on ClinicalTrials.gov (the first posted date).
September 1, 2026

First Submitted That Met QC Criteria

First Submitted That Met QC Criteria

The date on which the study sponsor or investigator first submits a study record that is consistent with National Library of Medicine (NLM) quality control (QC) review criteria. The sponsor or investigator may need to revise and submit a study record one or more times before NLM's QC review criteria are met. It is the responsibility of the sponsor or investigator to ensure that the study record is consistent with the NLM QC review criteria.
September 1, 2026

First Posted (Actual)

First Posted

The date on which the study record was first available on ClinicalTrials.gov after National Library of Medicine (NLM) quality control (QC) review has concluded. There is typically a delay of a few days between the date the study sponsor or investigator submitted the study record and the first posted date.
September 9, 2026

Study Record Updates

Last Update Posted (Actual)

Last Update Posted

The most recent date on which changes to a study record were made available on ClinicalTrials.gov. There may be a delay between when the changes were submitted to ClinicalTrials.gov by the study's sponsor or investigator (the last update submitted date) and the last update posted date.
September 9, 2026

Last Update Submitted That Met QC Criteria

Last Update Submitted That Met QC Criteria

The most recent date on which the study sponsor or investigator submitted changes to a study record that are consistent with National Library of Medicine (NLM) quality control (QC) review criteria. It is the responsibility of the sponsor or investigator to ensure that the study record is consistent with the NLM QC review criteria.
September 1, 2026

Last Verified

Last Verified

The most recent date on which the study sponsor or investigator confirmed the information about a clinical study on ClinicalTrials.gov as accurate and current. If a study with a recruitment status of recruiting; not yet recruiting; or active, not recruiting has not been confirmed within the past 2 years, the study's recruitment status is shown as unknown.
September 1, 2026

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

Other Study ID Numbers

Identifiers or ID numbers other than the NCT number that are assigned to a clinical study by the study's sponsor, funders, or others. These numbers may include unique identifiers from other trial registries and National Institutes of Health grant numbers.
  • AI-CAC-DE
  • 22-1182 (Other Identifier: Ethics Committee)

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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