Artificial intelligence and imaging: Opportunities in cardio-oncology

Area of Science:

• Cardio-oncology
• Medical Imaging
• Artificial Intelligence

Background:

• Cardiovascular disease is a major cause of mortality in cancer survivors.
• Early detection and predictive methods are crucial for cardiovascular treatment and surveillance in this population.
• Cardiotoxic cancer therapies necessitate advanced monitoring of cardiac health.

Purpose of the Study:

• To discuss the application of artificial intelligence (AI) in cardiovascular imaging within cardio-oncology.
• To highlight AI's role in preventing and treating cardiovascular conditions in cancer patients.
• To explore AI's potential in improving prediction and diagnosis of cardiac dysfunction.

Main Methods:

• Review of current AI applications in echocardiography for left ventricular ejection fraction (LVEF) and global longitudinal strain (GLS) assessment.
• Exploration of emerging AI uses in cardiovascular magnetic resonance imaging (CMR), computed tomography (CT), SPECT, and PET.
• Integration of AI for enhanced precision, accuracy, and data analysis in cardiac imaging.

Main Results:

• AI is improving the precision, throughput, and accuracy of LVEF and GLS measurements.
• AI aids in guiding point-of-care image acquisition and integrating diverse clinical data.
• Early-stage AI analysis shows potential in predicting and assessing cardiac tumors and adverse events across various imaging modalities.

Conclusions:

• AI in cardio-oncology imaging presents significant opportunities for clinical practice improvement.
• AI-driven advancements can lead to better patient care and outcomes for cancer survivors with cardiovascular concerns.
• The integration of AI promises to optimize the prediction, diagnosis, and management of cardiovascular issues in cancer patients.