Functional cardiac CT-Going beyond Anatomical Evaluation of Coronary Artery Disease with Cine CT, CT-FFR, CT Perfusion and Machine Learning

Area of Science:

• Cardiovascular Imaging
• Radiology
• Medical Technology

Background:

• Coronary artery stenosis assessment often requires invasive procedures.
• Non-invasive functional cardiac CT offers a promising alternative.
• Accurate stenosis significance determination is crucial for patient management.

Purpose of the Study:

• To review functional cardiac CT techniques for assessing coronary artery stenosis.
• To highlight the role of cine-CT, CT-FFR, and CT-myocardial perfusion.
• To explore the impact of machine learning on these techniques.

Main Methods:

• Review of existing literature on functional cardiac CT.
• Focus on cine-CT, computed tomography-derived fractional flow reserve (CT-FFR), and CT-myocardial perfusion.
• Discussion of machine learning applications in cardiac CT analysis.

Main Results:

• Functional cardiac CT techniques provide valuable non-invasive insights.
• CT-FFR and CT-myocardial perfusion offer quantitative assessments of stenosis severity.
• Machine learning shows potential to improve accuracy and efficiency.

Conclusions:

• Functional cardiac CT is evolving as a key tool in non-invasive cardiology.
• These techniques aid in establishing the significance of coronary artery stenoses.
• Integration of machine learning promises further advancements in cardiac CT analysis.