Key result
Multimodality etiological workup refines heart failure phenotyping beyond LVEF to guide targeted therapy.
Why the study?
LVEF provides only a limited representation of the biological heterogeneity underlying HF, making identification of the underlying etiology through multimodality imaging, biomarkers, genetics, and artificial intelligence essential for precision management.
Highlights the critical shift beyond LVEF toward comprehensive etiological diagnosis using multimodality imaging, genetics, biomarkers, and AI to enable precision medicine and disease-specific therapy in heart failure.
Answers are grounded in this paper and cite their sources.
May support etiology-based HF phenotyping beyond LVEF; leaves open prospective validation before practice change.
Heart failure (HF) is not a single disease but a complex clinical syndrome representing the final common pathway of multiple cardiovascular disorders and remains one of the leading causes of morbidity, mortality and healthcare expenditure worldwide Although left ventricular ejection fraction (LVEF) remains fundamental for clinical classification and therapeutic decision-making, it provides only a limited representation of the biological heterogeneity underlying HF. Increasing evidence demonstrates that HF encompasses a heterogeneous spectrum of disorders characterized by distinct pathophysiological mechanisms, prognostic profiles and therapeutic responses. Consequently, identification of the underlying etiology has become a cornerstone of contemporary HF management. Recent advances in cardiovascular imaging, molecular biology and cardiovascular genetics have profoundly transformed the diagnostic approach to HF. Multimodality imaging – including echocardiography, cardiovascular magnetic resonance (CMR), cardiac computed tomography and nuclear imaging – allows accurate tissue characterization and facilitates recognition of infiltrative, inflammatory, ischemic and inherited cardiomyopathies . Likewise, the integration of circulating biomarkers, genetic testing and artificial intelligence has enabled increasingly refined phenotypic characterization beyond conventional LVEF-based classification. Etiological diagnosis directly influences therapeutic decision-making by identifying reversible causes of ventricular dysfunction, guiding disease-specific therapies, improving prognostic stratification and enabling family screening in inherited cardiomyopathies. Conditions such as transthyretin cardiac amyloidosis, inflammatory cardiomyopathies and genetically determined cardiomyopathies illustrate how early recognition may substantially modify clinical outcomes This review aims to highlight how the etiological diagnosis is reshaping contemporary HF management and the emerging role of multimodality imaging, cardiovascular genetics, biomarkers and artificial intelligence in the transition toward precision cardiovascular medicine.
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Luzzi et al. (2026) conducted a review in Heart failure and cardiomyopathies. Etiological diagnosis utilizing multimodality imaging, cardiovascular genetics, circulating biomarkers, and artificial intelligence vs. Conventional left ventricular ejection fraction (LVEF)-based classification was evaluated. Etiological diagnosis using multimodality imaging, genetics, biomarkers, and AI refines heart failure characterization beyond LVEF to guide precision therapy and improve outcomes.
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