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Updated: Aug 5, 2026

In Silico Clinical Trials for Cardiovascular Disease
Published on: May 27, 2022
Next-Generation Cardiovascular Imaging in Precision Medicine: Integrating Functional Imaging, Artificial
Carmine Siniscalchi1, Manuela Basaglia1, Vincenzo Russo2
1Internal Medicine Department, Parma University Hospital, 43125 Parma, Italy.
Insights
Cardiovascular imaging advances offer multidimensional patient assessment beyond anatomy. Integrating imaging with AI and biomarkers enables personalized risk stratification for better cardiovascular disease management.
Area of Science:
- Cardiovascular Medicine
- Medical Imaging Technology
- Artificial Intelligence in Healthcare
Background:
- Cardiovascular and vascular diseases are leading global causes of death.
- Traditional imaging focused on anatomy; modern imaging evaluates function, hemodynamics, and inflammation.
- Technological progress drives a shift toward multidimensional cardiovascular assessment.
Purpose of the Study:
- To review current advances in cardiovascular and vascular imaging.
- To discuss the translational implications of these imaging advancements.
- To highlight future directions for integrating imaging, AI, and precision medicine.
Main Methods:
- Review of recent technological progress in echocardiography, cardiovascular magnetic resonance, computed tomography, nuclear imaging, intravascular imaging, and point-of-care ultrasound.
- Discussion of artificial intelligence, radiomics, and predictive analytics in cardiovascular imaging.
- Integration of imaging findings with biomarkers, clinical scores, and machine learning models.
Main Results:
- Advanced echocardiography improves functional and prognostic assessment in coronary artery disease.
- Cardiac MRI provides unique insights into myocardial fibrosis, perfusion, and hemodynamics.
- CT, hybrid imaging, and intravascular techniques enhance plaque characterization, inflammation assessment, and interventional guidance.
- Point-of-care ultrasound expands access to rapid cardiovascular assessment.
- Integration strategies promise personalized risk stratification for complex cardiovascular conditions.
Conclusions:
- Cardiovascular imaging has evolved to a multidimensional approach, integrating function, hemodynamics, and tissue composition.
- Technological innovations, including AI, are revolutionizing cardiovascular disease diagnosis and risk assessment.
- The future lies in integrating advanced imaging, AI, and precision medicine for personalized patient care.
Abstract:
Cardiovascular and vascular diseases remain major causes of morbidity and mortality worldwide, despite substantial advances in prevention, diagnosis, and treatment. In recent years, cardiovascular imaging has moved beyond the traditional assessment of anatomy and morphology toward a multidimensional evaluation of function, tissue composition, haemodynamics, inflammation, and individualized risk. This evolution has been driven by technological progress in echocardiography, cardiovascular magnetic resonance, computed tomography, nuclear imaging, intravascular imaging, and point-of-care ultrasound, together with the rapid development of artificial intelligence, radiomics, and predictive analytics. Advanced echocardiographic techniques, including contrast stress echocardiography and emerging methods for myocardial scar detection, may improve functional and prognostic assessment in patients with suspected or established coronary artery disease. Cardiac magnetic resonance, through tissue mapping, late gadolinium enhancement, and 4D flow imaging, provides unique information on myocardial fibrosis, perfusion, ventricular remodelling, and vascular haemodynamics. Computed tomography, particularly with the introduction of photon-counting technology, is expanding the non-invasive characterization of coronary plaques, vascular calcification, and thromboembolic disease. Hybrid imaging with PET/CT and PET/MR offers additional insight into vascular inflammation, myocardial metabolism, and active disease processes. At the same time, intravascular ultrasound, optical coherence tomography, and augmented-reality-supported imaging are refining interventional guidance, while point-of-care ultrasound is broadening access to rapid bedside cardiovascular and vascular assessment. The integration of imaging findings with circulating biomarkers, clinical scores, lipid profiles, coagulation parameters, and machine-learning models represents a promising strategy for personalized risk stratification, particularly in complex conditions such as coronary artery disease, venous thromboembolism, pulmonary embolism, and bleeding risk during antithrombotic therapy. This review summarizes current advances in cardiovascular imaging, discusses their translational implications, and highlights future directions for integrating imaging, artificial intelligence, and precision medicine into daily clinical practice.
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