Artificial Intelligence in Cardiovascular Imaging: Current Applications and New Horizons.

Area of Science:

• Cardiovascular Imaging
• Artificial Intelligence
• Medical Technology

Background:

• Artificial intelligence (AI) is increasingly integrated into medical imaging.
• Cardiovascular imaging (CVI) encompasses echocardiography (Echo), cardiac computed tomography (CCT), and cardiac magnetic resonance (CMR).
• AI offers potential to improve accuracy, efficiency, and diagnostic capabilities in CVI.

Purpose of the Study:

• To review the transformative impact of AI across various CVI modalities.
• To highlight AI's role in enhancing image acquisition, analysis, and interpretation.
• To discuss the challenges and future directions for AI in CVI.

Main Methods:

• Review of AI applications in Echo, CCT, and CMR.
• Analysis of AI's impact on image segmentation, quantification, and disease detection.
• Discussion of AI's role in workflow optimization and telemedicine.

Main Results:

• AI improves image acquisition, segmentation, and quantification in Echo, aiding diagnosis and prognosis.
• In CCT, AI optimizes protocols, reduces radiation, and enhances plaque analysis and ischemia evaluation.
• AI accelerates CMR acquisition, reduces artifacts, automates segmentation, and aids in fibrosis detection and prognosis prediction.
• AI tools streamline reporting, enhance telemedicine, and assist less experienced users.

Conclusions:

• AI is significantly enhancing accuracy and efficiency across cardiovascular imaging modalities.
• Addressing challenges like data diversity, interpretability, and regulation is crucial for widespread AI adoption in CVI.
• AI is poised to become an essential tool for personalized medicine and improved patient care in CVI.