Artificial Intelligence in Coronary Computed Tomography: Current Applications, Future Potentials, and Real-world...

Area of Science:

• Cardiovascular Imaging
• Artificial Intelligence
• Medical Diagnostics

Background:

• Cardiac computed tomography (CT) imaging is crucial for diagnosing coronary artery disease (CAD).
• Traditional methods face challenges in efficiency, accuracy, and comprehensive risk assessment.
• Advancements in artificial intelligence (AI) offer potential solutions to these limitations.

Purpose of the Study:

• To review the transformative impact of AI on cardiac CT imaging.
• To highlight AI's role in enhancing image acquisition, reconstruction, analysis, and clinical workflow.
• To discuss current and future applications of AI in cardiovascular imaging and precision medicine.

Main Methods:

• Deep learning reconstruction (DLR) for image quality optimization and dose reduction.
• AI algorithms for coronary artery segmentation and CAD-RADS classification.
• AI in functional imaging (CT-FFR, CT perfusion) and plaque characterization.
• Radiomics and machine learning on pericoronary adipose tissue (PCAT) for inflammation biomarkers.
• Fusion models integrating diverse data for risk prognostication.

Main Results:

• AI significantly improves diagnostic accuracy and workflow efficiency in cardiac CT.
• DLR reduces radiation and contrast media doses while enhancing image quality.
• AI enables precise CAD assessment, functional evaluation, and comprehensive plaque phenotyping.
• Novel AI-driven biomarkers from PCAT refine risk stratification.
• Integrated data fusion models surpass traditional risk scores for cardiovascular prognostication.

Conclusions:

• AI is revolutionizing cardiac CT, improving diagnostic capabilities and patient care.
• Future AI applications, including generative AI and digital twins, promise further workflow automation and personalized treatment strategies.
• Addressing challenges in data, interpretability, and regulation is key for widespread AI integration in cardiovascular medicine.