PDF(Pubmed)
Abstract：
OBJECTIVE: The pathological diagnosis of organizing pneumonia (OP) relies on conventional traditional histopathological analysis, which involves examining stained thin slices of tissue. However, this method often results in suboptimal diagnostic objectivity due to low tissue sampling rates. This study aimed to assess the efficacy of tissue-clearing and infiltration-enhanced 3D spatial imaging techniques for elucidating the tissue architecture of OP.
METHODS: H&E staining, 3D imaging technology, and AI-assisted analysis were employed to facilitate the construction of a multidimensional tissue architecture using six OP patient specimens procured from Taichung Veterans General Hospital, enabling a comprehensive morphological assessment.
RESULTS: Specimens underwent H&E staining and exhibited Masson bodies and varying degrees of interstitial fibrosis. Furthermore, we conducted a comprehensive study of 3D images of the pulmonary histology reconstructed through an in-depth pathology analysis, and uncovered heterogenous distributions of fibrosis and Masson bodies across different depths of the OP specimens.
CONCLUSIONS: Integrating 3D imaging for OP with AI-assisted analysis permits a substantially enhanced visualization and delineation of complex histological pulmonary disorders such as OP. The synergistic application of conventional histopathology with novel 3D imaging elucidated the sophisticated spatial configuration of OP, revealing the presence of Masson bodies and interstitial fibrosis. This methodology transcends conventional pathology constraints and paves the way for advanced algorithmic approaches to enhance precision in the detection, classification, and clinical management of lung pathologies.
METHODS: H&E staining, 3D imaging technology, and AI-assisted analysis were employed to facilitate the construction of a multidimensional tissue architecture using six OP patient specimens procured from Taichung Veterans General Hospital, enabling a comprehensive morphological assessment.
RESULTS: Specimens underwent H&E staining and exhibited Masson bodies and varying degrees of interstitial fibrosis. Furthermore, we conducted a comprehensive study of 3D images of the pulmonary histology reconstructed through an in-depth pathology analysis, and uncovered heterogenous distributions of fibrosis and Masson bodies across different depths of the OP specimens.
CONCLUSIONS: Integrating 3D imaging for OP with AI-assisted analysis permits a substantially enhanced visualization and delineation of complex histological pulmonary disorders such as OP. The synergistic application of conventional histopathology with novel 3D imaging elucidated the sophisticated spatial configuration of OP, revealing the presence of Masson bodies and interstitial fibrosis. This methodology transcends conventional pathology constraints and paves the way for advanced algorithmic approaches to enhance precision in the detection, classification, and clinical management of lung pathologies.
摘要：
目的：机化性肺炎（OP）的病理诊断依赖于传统的组织病理学分析，这包括检查染色的组织薄片。然而,由于组织采样率较低,这种方法通常导致诊断客观性欠佳.本研究旨在评估组织清除和浸润增强的3D空间成像技术对阐明OP的组织结构的功效。
方法：H&E染色，三维成像技术,和人工智能辅助分析被用来促进多维组织结构的构建使用六个OP患者标本从台中退伍军人总医院采购,能够进行全面的形态学评估。
结果：标本经H&E染色，显示Masson体和不同程度的间质纤维化。此外，我们通过深入的病理学分析，对重建的肺组织学的3D图像进行了全面的研究，并在OP标本的不同深度发现了纤维化和Masson体的异质分布。
结论：将OP的3D成像与AI辅助分析相结合，可以显着增强复杂的组织学肺部疾病如OP的可视化和描绘。传统组织病理学与新型3D成像的协同应用阐明了OP的复杂空间配置，揭示了Masson体和间质纤维化的存在。这种方法超越了传统的病理学限制，为提高检测精度的先进算法方法铺平了道路。分类，和肺部病变的临床管理。
方法：H&E染色，三维成像技术,和人工智能辅助分析被用来促进多维组织结构的构建使用六个OP患者标本从台中退伍军人总医院采购,能够进行全面的形态学评估。
结果：标本经H&E染色，显示Masson体和不同程度的间质纤维化。此外，我们通过深入的病理学分析，对重建的肺组织学的3D图像进行了全面的研究，并在OP标本的不同深度发现了纤维化和Masson体的异质分布。
结论：将OP的3D成像与AI辅助分析相结合，可以显着增强复杂的组织学肺部疾病如OP的可视化和描绘。传统组织病理学与新型3D成像的协同应用阐明了OP的复杂空间配置，揭示了Masson体和间质纤维化的存在。这种方法超越了传统的病理学限制，为提高检测精度的先进算法方法铺平了道路。分类，和肺部病变的临床管理。
