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Ultrasound in cardiovascular care: a perspective on preventive, diagnostic, and monitoring applications
Yoram Chaiter1, Daniel Lyon Fink2, Yossy Machluf3
1The Israeli Center for Emerging Technologies in Hospitals and Hospital-Based Health Technology Assessment, Shamir (Assaf Harofeh) Medical Center, Zerifin, Israel.
Insights
Ultrasound imaging offers a safe, non-invasive method for early cardiovascular disease detection and monitoring. Advances in artificial intelligence and mobile health platforms are making this technology more accessible for personalized cardiovascular care.
Area of Science:
- Cardiovascular Medicine
- Medical Imaging
- Preventive Cardiology
Background:
- Cardiovascular disease (CVD) is the leading global cause of death, with conventional risk models often missing individuals with subclinical vascular damage.
- Atherosclerosis, the primary cause of CVD, develops silently, necessitating advanced imaging for early detection.
- Ultrasound provides a safe, non-invasive, radiation-free method for real-time visualization of vascular structure, function, and hemodynamics.
Purpose of the Study:
- To reframe ultrasound as a cornerstone technology in preventive and diagnostic vasculature and cardiovascular medicine.
- To highlight key ultrasound modalities and their applications in early risk stratification and monitoring of atherosclerosis.
- To discuss the role of emerging technologies like AI and telemedicine in expanding ultrasound's reach.
Main Methods:
- Review and synthesis of current ultrasound modalities including point-of-care ultrasonography (POCUS), Doppler, Duplex, contrast-enhanced ultrasound (CEUS), elastography, and pulse wave velocity (PWV).
- Exploration of ultrasound's application across various arterial systems (carotid, aortic, peripheral, coronary, cerebral, renal).
- Discussion of the impact of artificial intelligence (AI), machine learning (ML), and deep learning (DL) on ultrasound interpretation and accessibility.
Main Results:
- Ultrasound techniques enable early risk stratification, monitoring of atherosclerotic progression, and evaluation of therapeutic response.
- Ultrasound enhances patient awareness and engagement, acting as a behavioral catalyst.
- AI, ML, and DL are automating plaque quantification, improving reproducibility, and enabling portable systems.
Conclusions:
- Ultrasound is evolving into a frontline technology for cardiovascular disease prevention, diagnosis, and monitoring.
- Integration with AI-driven interpretation and mobile health platforms enhances personalized and equitable cardiovascular care.
- Standardized protocols, training, and ethical oversight are crucial for widespread and equitable adoption.
Abstract:
Cardiovascular disease (CVD) remains the leading global cause of death, underscoring the need for improved strategies for early detection and prevention. Conventional risk models such as Framingham and SCORE estimate population-level risk but often fail to identify individuals with subclinical vascular damage. Atherosclerosis, the underlying cause of most CVDs, develops silently for decades, emphasizing the importance of imaging modalities capable of detecting early vascular changes. Ultrasound offers a safe, non-invasive, and radiation-free means to visualize vascular structure, function, and hemodynamics in real time. This perspective reframes ultrasound as a cornerstone of preventive and diagnostic vasculature medicine in general, and cardiovascular medicine in particular, emphasizing major modalities-point-of-care ultrasonography (POCUS), Doppler, Duplex, contrast-enhanced ultrasound (CEUS), elastography, and pulse wave velocity (PWV). These techniques enable early risk stratification, monitoring of atherosclerotic progression, and evaluation of therapeutic response across carotid, aortic, peripheral, coronary, cerebral, and renal arteries. Ultrasound also serves as a behavioral catalyst, enhancing patient awareness and engagement. However, widespread adoption requires standardized protocols, provider training, ethical oversight, and equitable implementation to avoid global disparities. Recent advances in artificial intelligence (AI), machine learning (ML), and deep learning (DL) are revolutionizing ultrasound by automating plaque quantification, improving reproducibility, and expanding access through portable and handheld systems. Cloud-based interpretation and telemedicine integration further extend cardiovascular screening into community and home settings. As ultrasound evolves into a frontline technology for prevention, diagnosis, and monitoring, its integration with AI-driven interpretation and mobile health platforms positions it as a pivotal tool in personalized and equitable cardiovascular care.
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