From Reduced Order Models to ATLAS: A Real‐Time Platform for Hemodynamics

ABSTRACT Cardiovascular diseases represent one of the leading causes of death worldwide, leading to the development of advanced research in numerical analysis to create decision‐support tools for the clinical community. The main objective is to develop advanced numerical frameworks for accurate diagnosis and personalized treatment planning. While high‐fidelity computational fluid dynamics (CFD) simulations provide detailed hemodynamic insights, their high computational cost, due to the large number of degrees of freedom and complex morphologies involved, limits their use in real‐time clinical routine. Reduced order models (ROMs) have emerged as a powerful framework to overcome these limitations by providing accurate approximations at a significantly reduced computational cost. In this paper, we provide a high‐level overview of the main ROM methodological categories, including linear and nonlinear approaches, and refer to relevant literature for more comprehensive treatments. Despite their potential, the technical complexity and specialized expertise required to implement these methods often hinder their direct application in clinical settings. To overcome these limitations, we introduce ATLAS, a cloud‐native open‐access platform designed to bridge the gap between complex numerical modeling and clinical practice through an intuitive web interface. The potential of the platform is demonstrated through a case study on the left atrial appendage (LAA), focusing on blood stasis as a key indicator of stroke risk. Finally, we discuss the role of ROMs as a key enabling technology for the development of cardiovascular digital twins, highlighting the potential for bidirectional communication between physical patients and their virtual counterparts.