The role of multimodality imaging in patients with heart failure with reduced and preserved ejection fraction

Artificial Intelligence and Its Role in Diagnosing Heart Failure: A Narrative Review

Heart failure (HF) is prevalent globally. It is a dynamic disease with varying definitions and classifications due to multiple pathophysiologies and etiologies. The diagnosis, clinical staging, and treatment of HF become complex and subjective, impacting patient prognosis and mortality. Technological advancements, like artificial intelligence (AI), have been significant roleplays in medicine and are increasingly used in cardiovascular medicine to transform drug discovery, clinical care, risk prediction, diagnosis, and treatment. Medical and surgical interventions specific to HF patients rely significantly on early identification of HF. Hospitalization and treatment costs for HF are high, with readmissions increasing the burden. AI can help improve diagnostic accuracy by recognizing patterns and using them in multiple areas of HF management. AI has shown promise in offering early detection and precise diagnoses with the help of ECG analysis, advanced cardiac imaging, leveraging biomarkers, and cardiopulmonary stress testing. However, its challenges include data access, model interpretability, ethical concerns, and generalizability across diverse populations. Despite these ongoing efforts to refine AI models, it suggests a promising future for HF diagnosis. After applying exclusion and inclusion criteria, we searched for data available on PubMed, Google Scholar, and the Cochrane Library and found 150 relevant papers. This review focuses on AI's significant contribution to HF diagnosis in recent years, drastically altering HF treatment and outcomes.

Diagnosis of heart failure with preserved ejection fraction: a systematic narrative review of the evidence

Heart failure (HF) with preserved ejection fraction (HFpEF) is a common condition in clinical practice, affecting more than half of patients with HF. HFpEF is associated with morbidity and mortality and with considerable healthcare resource utilization and costs. Therefore, early diagnosis is crucial to facilitate prompt management, particularly initiation of sodium-glucose co-transporter 2 inhibitors. Although European guidelines define HFpEF as the presence of symptoms with or without signs of HF, left ventricular EF ≥ 50%, and objective evidence of cardiac structural and/or functional abnormalities, together with elevated natriuretic peptide levels, the diagnosis of HFpEF remains challenging. First, there is no clear consensus on how HFpEF should be defined. Furthermore, diagnostic tools, such as natriuretic peptide levels and resting echocardiogram findings, are significantly limited in the diagnosis of HFpEF. As a result, some patients are overdiagnosed (i.e., elderly people with comorbidities that mimic HF), although in other cases, HFpEF is overlooked. In this manuscript, we perform a systematic narrative review of the diagnostic approach to patients with HFpEF. We also propose a comprehensible algorithm that can be easily applied in daily clinical practice and could prove useful for confirming or ruling out a diagnosis of HFpEF.

Multimodality Imaging in Advanced Heart Failure for Diagnosis, Management and Follow-Up: A Comprehensive Review

Advanced heart failure (AHF) presents a complex landscape with challenges spanning diagnosis, management, and patient outcomes. In response, the integration of multimodality imaging techniques has emerged as a pivotal approach. This comprehensive review delves into the profound significance of these imaging strategies within AHF scenarios. Multimodality imaging, encompassing echocardiography, cardiac magnetic resonance imaging (CMR), nuclear imaging and cardiac computed tomography (CCT), stands as a cornerstone in the care of patients with both short- and long-term mechanical support devices. These techniques facilitate precise device selection, placement, and vigilant monitoring, ensuring patient safety and optimal device functionality. In the context of orthotopic cardiac transplant (OTC), the role of multimodality imaging remains indispensable. Echocardiography offers invaluable insights into allograft function and potential complications. Advanced methods, like speckle tracking echocardiography (STE), empower the detection of acute cell rejection. Nuclear imaging, CMR and CCT further enhance diagnostic precision, especially concerning allograft rejection and cardiac allograft vasculopathy. This comprehensive imaging approach goes beyond diagnosis, shaping treatment strategies and risk assessment. By harmonizing diverse imaging modalities, clinicians gain a panoramic understanding of each patient's unique condition, facilitating well-informed decisions. The aim is to highlight the novelty and unique aspects of recently published papers in the field. Thus, this review underscores the irreplaceable role of multimodality imaging in elevating patient outcomes, refining treatment precision, and propelling advancements in the evolving landscape of advanced heart failure management.

Positron Emission Tomography in Heart Failure: From Pathophysiology to Clinical Application

Imaging modalities are increasingly being used to evaluate the underlying pathophysiology of heart failure. Positron emission tomography (PET) is a non-invasive imaging technique that uses radioactive tracers to visualize and measure biological processes in vivo. PET imaging of the heart uses different radiopharmaceuticals to provide information on myocardial metabolism, perfusion, inflammation, fibrosis, and sympathetic nervous system activity, which are all important contributors to the development and progression of heart failure. This narrative review provides an overview of the use of PET imaging in heart failure, highlighting the different PET tracers and modalities, and discussing fields of present and future clinical application.