Scholarlink

<p>Percutaneous needle insertion, a minimally invasive procedure widely used in medical applications, requires precise needle targeting for successful results. However, the interaction between the needle and soft tissue can cause needle deflection, resulting in deviations from the target. This study introduces a robust finite element model employing the coupled Eulerian-Lagrangian method to predict needle deflection during insertion into multilayer soft tissues. The model includes multilayer elastic components to capture the nonlinear behavior of soft tissues, providing an accurate representation of needle-tissue interaction. A multilayer phantom mimicking human tissue was fabricated using polyvinyl alcohol. Needle insertion experiments with varying depths and needle types were conducted to validate the simulation results. The prediction model demonstrated an average deflection error of (1.38 ± 0.25) mm. This research enhances understanding of needle-tissue interaction and provides a valuable tool for optimizing percutaneous puncture procedures. The model has potential for integration into realtime puncture navigation systems, improving precision, enhancing safety, and minimizing complications caused by needle deflection.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Prediction of Needle Deflection During Insertion into Multilayer Tissues

  • 期刊论文

  • 发表日期：

    2025年4月4日

查看全文
  • Xu Yang,
  • Yanping Lin

摘要

Percutaneous needle insertion, a minimally invasive procedure widely used in medical applications, requires precise needle targeting for successful results. However, the interaction between the needle and soft tissue can cause needle deflection, resulting in deviations from the target. This study introduces a robust finite element model employing the coupled Eulerian-Lagrangian method to predict needle deflection during insertion into multilayer soft tissues. The model includes multilayer elastic components to capture the nonlinear behavior of soft tissues, providing an accurate representation of needle-tissue interaction. A multilayer phantom mimicking human tissue was fabricated using polyvinyl alcohol. Needle insertion experiments with varying depths and needle types were conducted to validate the simulation results. The prediction model demonstrated an average deflection error of (1.38 ± 0.25) mm. This research enhances understanding of needle-tissue interaction and provides a valuable tool for optimizing percutaneous puncture procedures. The model has potential for integration into realtime puncture navigation systems, improving precision, enhancing safety, and minimizing complications caused by needle deflection.