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Background <p>Accurate diagnosis and evaluation of Williams Syndrome (WS) are essential yet challenging for effective surgical management. This study aimed to quantify the hemodynamic changes of surgical repair for WS through virtual surgery and computational fluid dynamics (CFD) for surgical guidance and postoperative evaluation.</p> Methods <p>A patient preliminarily diagnosed with WS was included in this study. 3D model alongside hemodynamic analysis was used to guide and evaluate the surgical procedure. Preoperative, predictive and postoperative models were created and analyzed using CFD. Key parameters, including blood flow velocity, pressure differences, wall shear stress, and other critical factors, were assessed to evaluate the surgery’s effectiveness.</p> Results <p>In the hemodynamics analysis, the CFD results of predictive model and postoperative model demonstrated a high level of consistency, and showed significant differences compared to the preoperative model. The velocity at the stenosis on the aorta decreased from 5.6&#xa0;m/s before the operation to 1.6&#xa0;m/s in the virtual model and 1.5&#xa0;m/s in the postoperative model. Surgical repair increased the proportion of outlet flow of the descending aorta (dAo) from 28.7% to 35.5%.</p> Conclusions <p>Virtual surgery and CFD can predict surgical outcomes, enabling doctors to optimize and rehearse the procedure before the actual surgery. The method of predicting surgery through virtual surgery and CFD is accurate and feasible.</p> Trial registration <p>Registered by the Ethics Committee of Peking University International Hospital (No. IRB2019-062).</p>

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Application feasibility of virtual models and computational fluid dynamics for the planning and evaluation of aortic repair surgery for Williams syndrome

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年3月4日

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  • Jixiang Liang,
  • Xuewei Fang,
  • Dianyuan Li,
  • Guangyu Pan,
  • Gen Zhang,
  • Bingheng Lu

摘要

Background

Accurate diagnosis and evaluation of Williams Syndrome (WS) are essential yet challenging for effective surgical management. This study aimed to quantify the hemodynamic changes of surgical repair for WS through virtual surgery and computational fluid dynamics (CFD) for surgical guidance and postoperative evaluation.

Methods

A patient preliminarily diagnosed with WS was included in this study. 3D model alongside hemodynamic analysis was used to guide and evaluate the surgical procedure. Preoperative, predictive and postoperative models were created and analyzed using CFD. Key parameters, including blood flow velocity, pressure differences, wall shear stress, and other critical factors, were assessed to evaluate the surgery’s effectiveness.

Results

In the hemodynamics analysis, the CFD results of predictive model and postoperative model demonstrated a high level of consistency, and showed significant differences compared to the preoperative model. The velocity at the stenosis on the aorta decreased from 5.6 m/s before the operation to 1.6 m/s in the virtual model and 1.5 m/s in the postoperative model. Surgical repair increased the proportion of outlet flow of the descending aorta (dAo) from 28.7% to 35.5%.

Conclusions

Virtual surgery and CFD can predict surgical outcomes, enabling doctors to optimize and rehearse the procedure before the actual surgery. The method of predicting surgery through virtual surgery and CFD is accurate and feasible.

Trial registration

Registered by the Ethics Committee of Peking University International Hospital (No. IRB2019-062).