Deformation analysis of surface and bronchial structures in intraoperative pneumothorax using deformable mesh registration
Deformation analysis of surface and bronchial structures in intraoperative pneumothorax using deformable mesh registration
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DOI：
10.1016/j.media.2021.102181
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发表时间：
2021-07-22
影响因子：
10.9
通讯作者：
Matsuda, Tetsuya
中科院分区：
文献类型：
--
作者：
Nakao, Megumi;Kobayashi, Kotaro;Matsuda, Tetsuya
由于术中肺放气，结节的位置可能发生变化，气胸相关变形的建模仍然是术中肿瘤定位的一个具有挑战性的问题。在这项研究中，我们介绍了空间和几何分析方法的充气/放气的肺，并讨论气胸相关的肺变形的异质性。对比增强CT图像模拟术中条件下获得的活比格犬。这些图像包含肺部的整体形状，包括所有肺叶和内部支气管结构，并进行分析以提供可用作预测气胸的先验知识的统计变形模型。为了解决气胸CT图像的拓扑变化和CT强度偏移的映射困难，我们设计了用于包括肺叶表面和支气管中心线的混合数据结构的可变形网格配准技术。三个全局到局部的配准步骤进行的约束下，变形是空间连续和平滑的，同时尽可能匹配可见的支气管树结构。所开发的框架实现了稳定的配准，Hausdorff距离小于1 mm，目标配准误差小于5 mm，并且可视化变形场显示了受试者之间具有高变异性的每叶收缩和旋转。变形分析结果表明，肺实质的应变比支气管的应变高35%，并且在放气的肺中变形是不均匀的。(c)2021作者（S）由Elsevier B. V.发布。这是CC BY许可下的开放获取文章（http：//creativecommons.org/licenses/by/4.0/）
The positions of nodules can change because of intraoperative lung deflation, and the modeling of pneumothorax-associated deformation remains a challenging issue for intraoperative tumor localization. In this study, we introduce spatial and geometric analysis methods for inflated/deflated lungs and discuss heterogeneity in pneumothorax-associated lung deformation. Contrast-enhanced CT images simulating in-traoperative conditions were acquired from live Beagle dogs. The images contain the overall shape of the lungs, including all lobes and internal bronchial structures, and were analyzed to provide a statistical de-formation model that could be used as prior knowledge to predict pneumothorax. To address the difficul-ties of mapping pneumothorax CT images with topological changes and CT intensity shifts, we designed deformable mesh registration techniques for mixed data structures including the lobe surfaces and the bronchial centerlines. Three global-to-local registration steps were performed under the constraint that the deformation was spatially continuous and smooth, while matching visible bronchial tree structures as much as possible. The developed framework achieved stable registration with a Hausdorff distance of less than 1 mm and a target registration error of less than 5 mm, and visualized deformation fields that demonstrate per-lobe contractions and rotations with high variability between subjects. The deformation analysis results show that the strain of lung parenchyma was 35% higher than that of bronchi, and that deformation in the deflated lung is heterogeneous. (c) 2021 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)