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MDCT-based dynamic, subject-specific lung models via image registration for CFD-based interrogation of regional lung function.

机译：基于MDCT的动态，特定于受试者的肺部模型，通过图像配准进行基于CFD的区域肺功能检查。

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摘要

Computational fluid dynamics (CFD) has become an attractive tool in understanding the characteristic of air flow in the human lungs. Due to inter-subject variations, subject-specific simulations are essential for understanding structure-function relationship, assessing lung function and improving drug delivery. However, currently the subject-specific CFD analysis remains challenging due, in large part to, two issues: construction of realistic deforming airway geometry and imposition of physiological boundary conditions. To address these two issues, we develop subject-specific, dynamic lung models by utilizing two or multiple volume multi-detector row computed tomography (MDCT) data sets and image registrations in this thesis. A mass-preserving nonrigid image registration algorithm is first proposed to match a pair of three-dimensional (3D) MDCT data sets with large deformations. A novel similarity criterion, the sum of squared tissue volume difference (SSTVD), is introduced to account for changes in intensity with lung inflation. We then demonstrate the ability to develop dynamic lung models by using a pair of lung volumes to account for deformations of airway geometries and subject-specific boundary conditions. The deformation of the airway geometry is derived by the registration-derived displacement field and subject-specific boundary condition is estimated from registration-predicted regional ventilation in a 3D and one-dimensional (1D) coupled multi-scale framework. Improved dynamic lung models are then proposed from three lung data sets acquired at different inflations by utilizing nonlinear interpolations. The improved lung models account for nonlinear geometry motions and time-varying boundary conditions during breathing. The capability of the proposed dynamic lung model is expected to move the CFD-based interrogation of lung function to the next plateau.
机译：计算流体动力学（CFD）已成为了解人肺中气流特征的一种有吸引力的工具。由于受试者之间的差异，特定于受试者的模拟对于理解结构与功能的关系，评估肺功能和改善药物传递至关重要。但是，目前，特定学科的CFD分析仍然具有挑战性，这在很大程度上归因于两个问题：构造实际的变形气道几何形状和施加生理边界条件。为了解决这两个问题，我们在本文中利用两个或多个容积多探测器行计算机断层扫描（MDCT）数据集和图像配准来开发特定于对象的动态肺模型。首先提出了一种保质非刚性图像配准算法，以匹配一对变形较大的三维（3D）MDCT数据集。引入了一种新颖的相似性标准，即组织体积差平方和（SSTVD），以解决肺膨胀引起的强度变化。然后，我们证明了通过使用一对肺体积来解决气道几何形状的变形和特定于受试者的边界条件来开发动态肺模型的能力。由配准派生的位移场得出气道几何形状的变形，并根据配准预测的区域通风在3D和一维（1D）耦合多尺度框架中估算特定对象的边界条件。然后，通过利用非线性插值，从在不同充气条件下获取的三个肺部数据集提出改进的动态肺部模型。改进的肺部模型考虑了呼吸过程中的非线性几何运动和时变边界条件。所提出的动态肺部模型的功能有望将基于CFD的肺部功能查询移至下一个平台。

著录项

  • 作者

    Yin, Youbing.;

  • 作者单位

    The University of Iowa.;

  • 授予单位 The University of Iowa.;
  • 学科 Engineering Biomedical.;Biology Physiology.;Biophysics Biomechanics.;Engineering Mechanical.
  • 学位 Ph.D.
  • 年度 2011
  • 页码 160 p.
  • 总页数 160
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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