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November 1, 2025JACC Case ReportsOpen Access

Computational Fluid Dynamics in Predicting Renal Malperfusion After Aortic Dissection Repair

Chengwei Yang Shujing Shao Xiaochang Leng Weiwei Qi Ying Chen Lian-Jun Huang Lei Xu Yuanming Luo Chengwei Yang Shujing Shao Xiaochang Leng Weiwei Qi Ying Chen Lian-Jun Huang Lei Xu Yuanming Luo

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Key Points

This research aims to use computational fluid dynamics to predict renal malperfusion following aortic dissection repair.
Patient-specific CFD simulations are performed.
Computed tomography angiography is utilized for imaging.
Hemodynamic profiling is conducted to assess perfusion status.
CFD simulations accurately detect perfusion compromise.
Profiles generated can indicate renal malperfusion in preclinical phases.

Implication

CFD simulations show hemodynamic profiling for detecting renal malperfusion post-aortic dissection, implying early intervention importance.

Abstract

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Cite This Study

Yang et al. (2025) studied this question.

synapsesocial.com/papers/69254f7dc0ce034ddc35904e https://doi.org/10.1016/j.jaccas.2025.106060

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Keep reading

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5Patient-specific haemodynamic simulations of complex aortic dissections informed by commonly available clinical datasetsother · 2019 · 4 citations

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