[Artificial intelligence in cardiac imaging: status and future developments].

Area of Science:

• Cardiology
• Medical Imaging
• Artificial Intelligence

Background:

• Artificial intelligence (AI) is increasingly vital in medical imaging, particularly for cardiac applications.
• AI transforms the entire cardiac imaging workflow, from acquisition to diagnosis, across modalities like echocardiography, CT, and MRI.
• Current AI applications include automated measurements, noise reduction, and artifact correction, enhancing efficiency and reproducibility.

Purpose of the Study:

• To review the transformative impact of AI on cardiac imaging.
• To highlight current and future applications of AI in cardiovascular diagnostics.
• To discuss the challenges and essential considerations for AI implementation in clinical practice.

Main Methods:

• Review of current literature on AI applications in cardiac imaging.
• Analysis of AI's role in echocardiography, CT, MRI, and nuclear cardiology.
• Discussion of future trends, including multimodal AI models.

Main Results:

• AI demonstrates potential in standardizing measurements, reducing scan times, and improving diagnostic accuracy.
• Specific applications include automated calcium scoring, plaque quantification, and detection of cardiac anomalies.
• Future multimodal AI models promise enhanced risk stratification and personalized therapies.

Conclusions:

• AI offers significant potential to advance cardiac imaging and patient care.
• Addressing challenges in generalizability, validation, and explainability is crucial.
• Clinical validation, quality control, and physician oversight are paramount for responsible AI adoption.