Cardiac amyloidosis (CA) shares similar clinical and imaging characteristics (e.g., hypertrophic phenotype) with aortic stenosis (AS), but its prognosis is generally worse than severe AS alone. Recent studies suggest that the presence of CA is frequent (1 out of 8 patients) in patients with severe AS. The coexistence of the two diseases complicates the prognosis and therapeutic management of both conditions. Thus, there is an urgent need to standardize and optimize the diagnostic process of CA and AS. The aim of this study is to develop a robust and reliable radiomics-based pipeline to differentiate the two pathologies.
Reference: A robust radiomic-based machine learning approach to detect cardiac amyloidosis using cardiac computed tomography.
Lo Iacono F, Maragna R, Pontone G, Corino VDA. Front Radiol. 2023 Jun 16;3:1193046.