Artificial intelligence in cardiovascular magnetic resonance imaging.

Area of Science:

• Cardiovascular Imaging
• Artificial Intelligence
• Medical Technology

Background:

• Artificial intelligence (AI) offers transformative potential in medical imaging.
• Cardiac magnetic resonance imaging (CMR) is a key modality for cardiovascular assessment.
• The integration of AI into CMR is rapidly advancing.

Purpose of the Study:

• To provide a comprehensive overview of current AI applications in CMR.
• To highlight AI's impact on image acquisition, segmentation, and tissue characterization.
• To anticipate future developments and imminent changes in AI-driven CMR.

Main Methods:

• Review of current AI applications in cardiac magnetic resonance imaging.
• Analysis of AI's role in image acquisition, segmentation, tissue characterization, diagnosis, and prognostic stratification.
• Exploration of radiomic techniques and non-contrast fibrosis assessment.

Main Results:

• AI significantly improves CMR image acquisition speed and quality.
• AI enhances segmentation accuracy, saving time and improving reproducibility.
• AI facilitates tissue characterization, including non-contrast myocardial fibrosis assessment and radiomics.
• AI supports automatic diagnosis and prognostic stratification in cardiac conditions.

Conclusions:

• AI is revolutionizing cardiac magnetic resonance imaging across multiple applications.
• Current AI integration in CMR focuses on efficiency, accuracy, and diagnostic capabilities.
• The field is poised for significant advancements, necessitating preparedness for future AI innovations.