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

## TL;DR

A new automated pipeline for 4D flow MRI improves the analysis of blood flow in the left atrium, offering better insights into heart health.

## Contribution

A robust computational framework for analyzing 4D Flow MRI data in the left atrium is introduced.

## Key findings

- The framework enables accurate segmentation and analysis of advanced hemodynamic parameters in the left atrium.
- 4D Flow MRI-derived parameters outperform conventional tools in distinguishing healthy from pathological states.
- The pipeline is robust across multicenter data with varying quality.

## 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.