Automated 4D flow MRI pipeline for the quantification of advanced hemodynamic parameters in the left atrium

X Xabier Morales A Ayah Elsayed D Debbie Zhao F Filip Loncaric A Ainhoa Aguado M Mireia Masias G Gina Quill M Marc Ramos A Adelina Doltra A Ana García-Álvarez (Centro Nacional de Investigaciones Cardiovasculares Carlos III, Madrid) M Marta Sitges D David Marlevi A Alistair Young M Martyn Nash B Bart Bijnens O Oscar Camara

Abstract

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.

Article Details

Volume / Issue Vol. 16, Issue 1
Published January 16, 2026
ISSN 2045-2322
Publisher Nature Portfolio

Journal Info

Scientific Reports

Nature Portfolio

ISSN: 2045-2322 Open Access Life Sciences

Authors (16)

X

Xabier Morales

A

Ayah Elsayed

D

Debbie Zhao

F

Filip Loncaric

A

Ainhoa Aguado

M

Mireia Masias

G

Gina Quill

M

Marc Ramos

A

Adelina Doltra

A

Ana García-Álvarez

Centro Nacional de Investigaciones Cardiovasculares Carlos III, Madrid

M

Marta Sitges

D

David Marlevi

A

Alistair Young

M

Martyn Nash

B

Bart Bijnens

O

Oscar Camara