Integration of artificial intelligence into cardiac ultrasonography practice

Area of Science:

• Cardiovascular Imaging
• Medical Artificial Intelligence
• Echocardiography

Background:

• Echocardiography has undergone significant technological advancements.
• Artificial intelligence (AI) integration is a key development, aiding image acquisition and analysis.

Purpose of the Study:

• To review AI integration in various echocardiographic modalities.
• To examine AI's role in enhancing image acquisition, analysis, and diagnostic performance.
• To highlight clinical relevance and practical applications of AI in cardiac ultrasonography.

Main Methods:

• Literature search of PubMed using targeted keywords.
• Focus on peer-reviewed articles from 2020 onwards, including foundational earlier studies.
• Thematic organization of findings for clinical relevance.

Main Results:

• AI assists in acquiring diagnostic-quality echocardiographic images.
• AI automates complex cardiac analyses across multiple modalities.
• AI improves diagnostic performance in routine, critical care, and complex imaging.

Conclusions:

• AI integration offers unparalleled potential to revolutionize cardiovascular care.
• Overcoming challenges like algorithmic bias and ensuring clinician training are crucial for successful implementation.
• The benefits of AI in cardiac ultrasonography are expected to outweigh obstacles with proper application.