Imaging Challenges in Patients with Severe Aortic Stenosis and Heart Failure: Did We Find a Way Out of the Labyrinth?

Aortic stenosis (AS) is the most frequent degenerative valvular disease in developed countries. Its incidence has been constantly rising due to population aging. The diagnosis of AS was considered straightforward for a very long time. High gradients and reduced aortic valve area were considered as “sine qua non” in diagnosis of AS until a growing body of evidence showed that patients with low gradients could also have severe AS with the same or even worse outcome. This completely changed the paradigm of AS diagnosis and involved large numbers of parameters that had never been used in the evaluation of AS severity. Low gradient AS patients may present with heart failure (HF) with preserved or reduced left ventricular ejection fraction (LVEF), associated with changes in cardiac output and flow across the aortic valve. These patients with low-flow low-gradient or paradoxical low-flow low-gradient AS are particularly challenging to diagnose, and cardiac output and flow across the aortic valve have become the most relevant parameters in evaluation of AS, besides gradients and aortic valve area. The introduction of other imaging modalities in the diagnosis of AS significantly improved our knowledge about cardiac mechanics, tissue characterization of myocardium, calcium and inflammation burden of the aortic valve, and their impact on severity, progression and prognosis of AS, not only in symptomatic but also in asymptomatic patients. However, a variety of novel parameters also brought uncertainty regarding the clinical relevance of these indices, as well as the necessity for their validation in everyday practice. The aim of this review is to summarize the prevalence of HF in patients with severe AS and elaborate on the diagnostic challenges and advantages of comprehensive multimodality cardiac imaging to identify the patients that may benefit from surgical or transcatheter aortic valve replacement, as well as parameters that may help during follow-up.