Artificial intelligence in aortic CT angiography: current applications and future perspectives.

Area of Science:

• Cardiovascular Imaging
• Medical Artificial Intelligence

Background:

• Aortic computed tomography angiography (CTA) is crucial for diagnosing and managing aortic diseases.
• Conventional CTA has limitations including radiation exposure, contrast risks, and manual interpretation challenges.

Purpose of the Study:

• To review the current applications of AI in aortic CTA.
• To analyze emerging AI techniques and their clinical potential in cardiovascular imaging.
• To identify challenges and future research directions for AI in aortic CTA.

Main Methods:

• Review of current literature on AI applications in aortic CTA.
• Analysis of emerging AI techniques such as image synthesis, Vision Transformers, multi-task learning, and Foundation Models.
• Discussion of AI's role in image enhancement, segmentation, diagnostics, and prognostic evaluation.

Main Results:

• AI enhances image quality and automates segmentation in aortic CTA.
• AI improves diagnostic accuracy for aortic emergencies and aids prognostic evaluation post-intervention.
• Emerging AI techniques show significant potential for clinical translation in cardiovascular imaging.

Conclusions:

• AI offers innovative solutions to limitations of conventional aortic CTA.
• AI integration promises to advance cardiovascular imaging, diagnostics, and patient management.
• Further research is needed to address challenges and fully realize AI's potential in aortic CTA.