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Updated: May 28, 2026
In vitro Assessment of Aortic Regurgitation Using Four-Dimensional Flow Magnetic Resonance Imaging
Published on: February 25, 2022
Noise-Pressure Constrained Liutex method for robust vortex identification in 4D Flow MRI of abdominal aortic
Chengxin Weng1, Daiyang He2, Siquan Cheng3
1Division of Vascular Surgery, Department of General Surgery and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Department of General Surgery 1 (Hepato-Pancreato-Biliary Surgery & Vascular Surgery), West China Tianfu Hospital, Sichuan University, Chengdu, Sichuan, China.
Introduction:
Accurate identification of vortices is critical for predicting the rupture risk of abdominal aortic aneurysms (AAA). However, existing vortex identification methods perform poorly in noisy 4D Flow MRI data. This study aims to develop a robust vortex identification framework to address these limitations.
Methods:
A new vortex identification method based on Liutex method is proposed that integrates relative pressure information and divergence-based noise estimation to enhance the accuracy and robustness of vortex identification in noisy environments. The performance of the proposed method was validated against conventional techniques (vorticity, Q-criterion, Δ-criterion) and original Liutex using 4D Flow MRI data from 10 AAA patients, with the Fβ score as the evaluation metric.
Results:
Qualitative visualization and quantitative analysis demonstrated the superior performance of the Noise-Pressure Constrained Liutex (NPC-Liutex) method. It achieved clearer delineation of vortical structures across diverse hemodynamic patterns, with significantly higher Fβ scores (average improvement: 0.058), lower spatial entropy (average improvement: 65.8%) and lower false identification rates (average reduced false identification: 78.6%) compared to existing methods.
Conclusion:
The NPC-Liutex method enables reliable extraction of vortical structures, accurate quantification of vortex intensity, and robust tracking of their dynamic evolution in AAA. By addressing noise sensitivity and shear contamination, this approach offers a clinically viable tool for enhancing hemodynamic risk assessment in AAA using 4D Flow MRI.
