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前言

各位好！随着三维重建的开展，在打通胸外科肺段手术可视化的最后一步便是——展现出萎陷肺的血管结构。肺组织在不同形变状况下血管与支气管结构也展现出了不同的毗邻关系。通气肺和萎陷肺到底在数据上有哪些差异呢？一起来欣赏此篇小样本狗肺计算机可视化研究~！

本 文 约3049 字 多图预警

阅 读 需 要 5-10 min

Megumi Nakao, Kotaro Kobayashi, Junko Tokuno, Toyofumi Chen-Yoshikawa, Hiroshi Date, Tetsuya Matsuda

Medical Image Analysis 2021 July 15, 73: 102181

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 intraoperative 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 deformation model that could be used as prior knowledge to predict pneumothorax. To address the difficulties 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.

摘要：由于胸外科手术中肺的萎陷，肺内结节的位置会随之发生变化，气胸相关肺形变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，我们介绍了膨胀/萎陷肺的空间和几何分析方法，并讨论了气胸相关肺形变的异质性。模拟术中条件的增强 CT影像是从活的比格犬获得的。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，并对以上图像数据进行分析以提供可用作预测气胸的先验统计形变模型。为了解决拓扑变化的可变性和CT辐射强度变化造成气胸 CT 图像成像的困难，我们为混合数据结构设计了可变形网格配准技术，包括肺叶表面和支气管中心线。在变形空间连续和平滑的约束下执行三个全局到局部的配准步骤，同时尽可能匹配可见的支气管树结构。开发的框架实现了小于 1 mm 的 Hausdorff 距离和小于 5 mm 的目标配准误差的稳定配准，并且可视化的形变图显示了每个叶的收缩和旋转，但受试🐕之间具有高度可变性。形变分析结果表明，肺实质的形变比支气管高35%，萎陷后肺的形变是不均匀的。

Highlights

•A complete model-based deformable registration solution for mapping inflated/deflated lungs.

•A mapping function design for mixed data structures of lobe surfaces and bronchial tree structures with incomplete correspondence derived from CT intensity shifts.

•Visualization of deformation fields including per-lobe contractions and rotations.

•Numerical analysis of heterogeneity in pneumothorax-associated deformation of whole lungs.

• 基于模型的形变配准可用以绘制通气/萎陷肺。

• 不同CT强度偏移下，混合数据结构的映射函数设计可对肺叶表面和支气管树结构进行重建。

• 形变场进一步可视化，可展现每个叶的收缩和旋转。

• 基于此模型可进行  “气胸相关肺形变”  异质性的定量分析。

思考

1.首先切除前定位的优缺点已不必多言，而对于术中定位在临床实践中的确有不少胸外科医生基于术前CT与术中胸腔镜图片来在脑海里进行建模进而寻找结节。

无论是钝角线、锐角线，周围组织结构做参照，亦或是层面比例计算，都有以下缺点：定位不够直观简洁；对术者要求较高，对于深部小结节往往束手无策，肺组织发育异常者更倾向于依赖经验；多是范围定位，定位范围不够精确；初次定位失败后在扩切范围上有较大的模糊性。

　10.11855/j.issn.0577-7402.2019.12.09

PMCID: PMC7417760

2. 此文的目的就是基于试验动物对术中萎陷肺进行增强CT检查，进一步进行模型构建来探索实现对于膨胀肺与萎陷肺的初步研究。你说作者有没有想在研究肺内不同位置在膨胀与萎陷状况下的改变？特别是对于位置深在的小结节/段间结节，无论是杂交手术室还是结合生物力学，同时兼顾简洁与可靠似乎是不可能完成的任务。

3.目前市场上常见的定位方法基本上可以满足临床需求，但~！数学建模的简洁真的让人眼红。那么还有哪些另辟蹊径，惊艳到你的定位方法呢？一起去留言板挖宝吧~！

目录 (盲猜大家从来不看英文~这次就放上中文渣翻了)

1. 背景

2. 方法

   2.1. 数据获取和预处理（Fig.1）

   2.2. 问题定义 (Fig. 2)

   2.3. 肺部表面和支气管结构的DMR(网格形变配准)（Fig. 3）

      第1步 全局仿生变换

      第2步 分形仿生(PWA)形变配准

      第3步 基于拉普拉斯的局部网格配准

   2.4. 目标函数(Fig.4)

   表面距离

   单向中心线距离

   全部目标

   2.5. 收缩和旋转模块（Fig.5）

   2.6. 定义支气管和肺实质的表面应变（Fig.6）

3. 实验

   3.1. DMR的定量比较（Fig.7）

   3.2. 气胸相关的形变分析（Fig.8-9）

4. 讨论

5. 结论

— 图表汇总—

（限于篇幅，此处仅放上文中图片，附表略去）

Graphical abstract

方法概览 (Fig. 1)

Fig. 1. CT slice images and extracted bronchial structures in the inflated/deflated states.

(a) Intensity shift and topological changes inside the thoracic cavity, and

(b) the paired bronchial labels extracted using the same CT values. (Arrows indicate estimated corresponding points).

解决个什么问题呢？

Fig. 2. A typical example of the mesh models and DMR results. 

(a) Tetrahedral meshes in the inflated (translucent) and deflated states (opaque), 

(b) bronchial centerlines in the inflated state, 

(c) bronchial centerlines in the deflated state, 

(d) overlapping images and 

(e) deformed centerlines (blue) using conventional DMR and linear mapping. 

(For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

步骤一：先把参照线找对了 (Fig. 3)，从这点上看数学家找参考线简直能比外科医师多一倍

Fig. 3. Proposed three-step DMR framework for mixed data structures with lung surfaces and centerlines. The registration process is applied to each lobe independently to cope with rotational components or sliding motion of pneumothorax-associated deformation.

步骤二：根据参照对数据进行函数构建(Fig. 4)

Fig. 4. Local distance measures for lung surfaces and bronchial centerlines with missing parts.

(a) initial setup of the inflated and deflated models,

(b) deformed and deflated models after global affine transformation,

(c) bidirectional surface distance, and

(d) one-way centerline distance.

步骤三：舒张旋转模块构建(Fig. 5)

Fig. 5. Contraction and rotational components in pneumothorax-associated lung deformation.

(a) Homogeneous deformation with zero rotational components,

(b) a real example of pneumothorax-associated deformation with rotation,

(c) the contraction component extracted from the deformation field, and

(d) its geometrical description.

Fig. 6. Definition of the Cauchy strain for bronchi and parenchyma in each lobe. 

(a) The positional relationship between the hilum, bronchial junctions, and terminal and corresponding surface point. 

(b) 2D plots and strain calculation for bronchi (blue line) and parenchyma (red line). 

(For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

是骡子是马拉出来溜溜，模型也得学会可视化

Fig. 7. Typical registration results with variations in bronchial anatomy and lobe deformation.

(a) visual comparison between the proposed DMR and surface registration with linear mapping,

(b) enlarged images of the local bronchial shapes,

(c) 24 points for evaluating target registration error.

然后呢？还能用来干啥？气胸相关的肺形变异质性分析

Fig. 8. The relationship between the Euclidean distance from the pulmonary hilum and the contraction components for bronchi and parenchyma. The gradient of the regression line represents the strain.

力场、电场、磁场~肺组织的形变场~！

Fig. 9. Visualization results of four deformation fields, contractions, and rotational components. The displacement vectors represent the corresponding points of the inflated/deflated models. The colors show the magnitude of the displacements.

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