Iron-Based Contrast Agents in Cardiovascular MRI: Current Applications, Emerging Biomarkers, and Future Directions

Cardiovascular magnetic resonance (CMR) increasingly relies on advanced contrast strategies to characterize vascular anatomy, hemodynamics, and biological disease activity. Although gadolinium-based contrast agents remain the clinical standard, iron oxide nanoparticles offer distinctive magnetic and pharmacokinetic properties that enable applications extending beyond conventional contrast enhancement. Among these agents, ultrasmall superparamagnetic iron oxide particles (USPIOs), particularly ferumoxytol, combine prolonged intravascular persistence with delayed uptake by cells of the mononuclear phagocyte system. This review distinguishes three levels of evidence. First, ferumoxytol-enhanced blood-pool magnetic resonance angiography is a clinically feasible, although off-label, application, with particular value in congenital heart disease and in patients with impaired renal function. Second, T2*/R2* imaging of macrophage-associated inflammation in atherosclerotic plaques, abdominal aortic aneurysms, and, to a lesser extent, the myocardium is an exploratory biomarker approach supported mainly by small studies; in the largest cohort (MA3RS), USPIO enhancement did not improve prediction of clinical events beyond conventional risk factors, and ΔR2* reflects nanoparticle accumulation rather than a direct measure of macrophage burden. Third, surface-functionalized iron oxide nanoparticles for active molecular targeting of endothelial activation, thrombosis, and vascular remodeling, and for targeted drug delivery, remain at a preclinical stage; they represent a future direction rather than an additional temporal phase of conventional ferumoxytol imaging. This review summarizes the physical and pharmacokinetic principles of iron-based contrast agents, their cardiovascular applications, and their safety considerations and discusses the requirements (standardization, multicenter reproducibility, and outcome-based validation) for their integration into multiparametric cardiovascular imaging.