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<p>To develop a predictive model for optimal anastomosis sizing in TAPVC surgery, focusing on the role of pulmonary venous confluence (PVC) size. A patient-specific fluid–structure interaction (FSI) model simulated blood flow through various anastomosis sizes. Key variables included body weight, anastomosis length, and PVC size. The model's predictions were validated against postoperative echocardiographic measurements from nine TAPVC cases. A strong positive correlation was found between flow velocity and the ratio of body weight to anastomosis length and PVC circumference. Including PVC size significantly improved predictive accuracy. No significant difference was observed between predicted and measured velocities. PVC size is a critical factor for planning TAPVC surgery. Incorporating it into computational models enhances the prediction of flow dynamics and supports personalized surgical decision-making.</p> Graphical Abstract <p></p>

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Computational Predictive Modeling of Surgical Outcomes in Total Anomalous Pulmonary Venous Connection: Assessing the Impact of Pulmonary Venous Confluence Size on Preoperative Planning

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月4日

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  • Jie Jin,
  • Zhuo Shi,
  • Qiang Gao,
  • Jing Yu,
  • Irina Jin,
  • Jiawei Liang,
  • Xiangming Fan

摘要

To develop a predictive model for optimal anastomosis sizing in TAPVC surgery, focusing on the role of pulmonary venous confluence (PVC) size. A patient-specific fluid–structure interaction (FSI) model simulated blood flow through various anastomosis sizes. Key variables included body weight, anastomosis length, and PVC size. The model's predictions were validated against postoperative echocardiographic measurements from nine TAPVC cases. A strong positive correlation was found between flow velocity and the ratio of body weight to anastomosis length and PVC circumference. Including PVC size significantly improved predictive accuracy. No significant difference was observed between predicted and measured velocities. PVC size is a critical factor for planning TAPVC surgery. Incorporating it into computational models enhances the prediction of flow dynamics and supports personalized surgical decision-making.

Graphical Abstract