Automated 4D Flow MRI Pipeline for the Quantification of Advanced Hemodynamic Parameters in the Left Atrium
Date
Authors
Morales, Xabier
Elsayed, Ayah
Zhao, Debbie
Loncaric, Filip
Aguado, Ainhoa
Masias, Mireia
Quill, Gina
Ramos, Marc
Doltra, Adelina
García-Alvarez, Ana
Supervisor
Item type
Journal Article
Degree name
Journal Title
Journal ISSN
Volume Title
Publisher
Nature Portfolio
Abstract
The left atrium (LA) plays a pivotal role in modulating left ventricular filling, yet its hemodynamics remain poorly understood due to the limitations of conventional ultrasound analysis. Four-dimensional flow magnetic resonance imaging (4D Flow MRI) holds promise for enhancing our understanding of atrial hemodynamics, but its analysis is hindered by the inherently low velocities within the chamber and the modest spatial resolution of 4D Flow MRI. Heterogeneity in acquisition protocols and MRI vendors, and the lack of standardized computational frameworks further complicates the creation of large, comparable datasets needed to assess the prognostic value of hemodynamic markers provided by 4D Flow MRI. To address these challenges, we introduce a computational framework tailored to the analysis of 4D Flow MRI in the LA, enabling the qualitative and quantitative analysis of advanced hemodynamic parameters (e.g., kinetic energy, vorticity, and pressure). We applied this framework to a diverse cohort spanning different degrees of left ventricular diastolic dysfunction to investigate the prognostic potential of these metrics. Our framework proved robustness across multicenter data of varying quality, producing high-accuracy automated segmentations. Notably, our findings show that 4D Flow MRI-derived parameters provide superior differentiation between healthy and pathological states than those available to conventional hemodynamic analysis tools.Description
Keywords
4D flow MRI, Computational pipeline, Deep learning, Hemodynamics, Left atrium, Left ventricular diastolic dysfunction, 4D flow MRI, Computational pipeline, Deep learning, Hemodynamics, Left atrium, Left ventricular diastolic dysfunction, 4012 Fluid Mechanics and Thermal Engineering, 32 Biomedical and Clinical Sciences, 40 Engineering, 4003 Biomedical Engineering, Biomedical Imaging, Bioengineering, Networking and Information Technology R&D (NITRD), Cardiovascular
Source
Scientific Reports, ISSN: 2045-2322 (Print); 2045-2322 (Online), Nature Portfolio, 16(1), 5426-. doi: 10.1038/s41598-025-34972-7
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