Lawson Matthew J, Katsamenis Orestis L, Chatelet David, Alzetani Aiman, Larkin Oliver, Haig Ian, Lackie Peter, Warner Jane, Schneider Philipp
School of Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK.
μ-VIS X-ray Imaging Centre, Faculty of Engineering and Physical Sciences, University of Southampton, Southampton, UK.
R Soc Open Sci. 2021 Nov 3;8(11):211067. doi: 10.1098/rsos.211067. eCollection 2021 Nov.
Micro-computed tomography (µCT) provides non-destructive three-dimensional (3D) imaging of soft tissue microstructures. Specific features in µCT images can be identified using correlated two-dimensional (2D) histology images allowing manual segmentation. However, this is very time-consuming and requires specialist knowledge of the tissue and imaging modalities involved. Using a custom-designed µCT system optimized for imaging unstained formalin-fixed paraffin-embedded soft tissues, we imaged human lung tissue at isotropic voxel sizes less than 10 µm. Tissue sections were stained with haematoxylin and eosin or cytokeratin 18 in columnar airway epithelial cells using immunofluorescence (IF), as an exemplar of this workflow. Novel utilization of tissue autofluorescence allowed automatic alignment of 2D microscopy images to the 3D µCT data using scripted co-registration and automated image warping algorithms. Warped IF images, which were accurately aligned with the µCT datasets, allowed 3D segmentation of immunoreactive tissue microstructures in the human lung. Blood vessels were segmented semi-automatically using the co-registered µCT datasets. Correlating 2D IF and 3D µCT data enables accurate identification, localization and segmentation of features in fixed soft lung tissue. Our novel correlative imaging workflow provides faster and more automated 3D segmentation of µCT datasets. This is applicable to the huge range of formalin-fixed paraffin-embedded tissues held in biobanks and archives.
微计算机断层扫描（µCT）可对软组织微观结构进行无损三维（3D）成像。利用相关的二维（2D）组织学图像可识别µCT图像中的特定特征，从而实现手动分割。然而，这非常耗时，并且需要所涉及组织和成像方式的专业知识。我们使用专为未染色的福尔马林固定石蜡包埋软组织成像而优化设计的定制µCT系统，以小于10 µm的各向同性体素大小对人肺组织进行成像。作为该工作流程的一个示例，组织切片用苏木精和伊红染色，或使用免疫荧光（IF）对柱状气道上皮细胞中的细胞角蛋白18进行染色。利用组织自发荧光的新方法，通过脚本化配准和自动图像变形算法，可将二维显微镜图像自动与三维µCT数据对齐。与µCT数据集精确对齐的变形IF图像，可对人肺中免疫反应性组织微观结构进行三维分割。利用配准后的µCT数据集对血管进行半自动分割。将二维IF数据与三维µCT数据相关联，能够准确识别、定位和分割固定肺软组织中的特征。我们新颖的相关成像工作流程为µCT数据集提供了更快、更自动化的三维分割。这适用于生物样本库和档案室中保存的大量福尔马林固定石蜡包埋组织。
