Advanced cardiac imaging and artificial intelligence support precision-guided heart failure interventions across pre-procedural, intra-procedural, and post-procedural pathways.
Advanced cardiac imaging and artificial intelligence are increasingly central to precision-guided heart failure interventions across pre-, intra-, and post-procedural pathways.
Heart failure remains a major driver of hospitalization, morbidity, impaired quality of life, and healthcare expenditure. As disease phenotypes become more diverse and therapeutic options expand beyond pharmacological treatment alone, contemporary heart failure care increasingly includes transcatheter valve therapies, cardiac resynchronization and pacing strategies, complex coronary interventions, invasive hemodynamic assessment, implantable pressure sensors, and advanced heart failure therapies. This evolution has made precision in three domains increasingly important: anatomy, myocardial substrate, and physiology. Advanced cardiac imaging is central to this transition. Echocardiography remains the front-line modality for functional assessment, hemodynamics, and procedural guidance. Cardiac magnetic resonance refines etiologic diagnosis through ventricular quantification, scar assessment, and tissue characterization. Cardiac computed tomography provides high-resolution anatomic planning for structural and coronary interventions. Nuclear imaging offers selected value in perfusion, viability, inflammation, and sympathetic innervation. In parallel, remote hemodynamic monitoring supports earlier recognition of congestion, while artificial intelligence may improve segmentation, standardization, workflow efficiency, and risk prediction. This narrative review synthesizes the role of advanced cardiac imaging and artificial intelligence across the pre-procedural, intra-procedural, and post-procedural pathway in heart failure interventions. We propose a pragmatic precision-care framework that integrates multimodality imaging, invasive physiology, remote monitoring, and patient-centered outcomes. We also highlight current limitations, including heterogeneous evidence, variable access, procedural non-response, data fragmentation, and the need for external validation before broad implementation of artificial intelligence-supported decision-making.
Albulushi et al. (Thu,) conducted a review in Heart failure. Advanced cardiac imaging and artificial intelligence was evaluated. Advanced cardiac imaging and artificial intelligence support precision-guided heart failure interventions across pre-procedural, intra-procedural, and post-procedural pathways.