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CCTA as a Screening Tool (Invited Commentary).

Yuxin Wang1, Yan Yi1, Yining Wang1

  • 1From the Department of Radiology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.

The British Journal of Radiology
|January 25, 2026
PubMed
Summary
This summary is machine-generated.

Coronary computed tomography angiography (CCTA) is a valuable non-invasive tool for detecting coronary artery disease and assessing risk. While promising for screening, challenges like cost and radiation exposure need further research, especially with AI integration.

Keywords:
Cardiovascular DiseasesComputed Tomography AngiographyScreening

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Area of Science:

  • Cardiovascular Imaging
  • Radiology
  • Preventive Cardiology

Background:

  • Coronary computed tomography angiography (CCTA) is a crucial non-invasive diagnostic tool for coronary artery disease (CAD).
  • Current guidelines support CCTA for symptomatic patients and select asymptomatic high-risk individuals.
  • CCTA offers high sensitivity, detailed anatomical insights, and prognostic information.

Purpose of the Study:

  • To evaluate the role and potential of CCTA in screening for coronary artery disease.
  • To explore the benefits and challenges of CCTA screening, including early detection and risk stratification.
  • To assess the impact of artificial intelligence on CCTA screening efficiency and adoption.

Main Methods:

  • Review of current guidelines and literature on CCTA for CAD evaluation and screening.
  • Analysis of CCTA's advantages, such as detecting subclinical atherosclerosis and high-risk plaque features.
  • Consideration of challenges including procedural complexity, radiation/contrast exposure, cost, and psychological impact.

Main Results:

  • CCTA demonstrates significant potential for early CAD detection and personalized prevention through plaque analysis.
  • Screening with CCTA faces hurdles related to cost, radiation, and complexity.
  • Artificial intelligence integration may enhance CCTA's efficiency, accuracy, and cost-effectiveness.

Conclusions:

  • CCTA is a powerful tool for CAD assessment, with emerging potential in screening.
  • Further research, including randomized controlled trials, is essential to validate CCTA screening's clinical and economic impact.
  • AI-driven advancements may overcome current limitations and improve CCTA adoption for cardiovascular risk reduction.