Computer methods and programs in biomedicine · 2026
Noise-Pressure Constrained Liutex method for robust vortex identification in 4D Flow MRI of abdominal aortic aneurysms.
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Weng Chengxin, He Daiyang, Cheng Siquan, Yuan Ding, Wang Tiehao, Zeng Wen, Luo Yi, Wang Jiarong, Li Kang, Qiu Yue
Аннотация
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.
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.