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对于3D:3D全器官重建,一种用于解读淋巴器官复杂性的自动化工具。

For3D: Full organ reconstruction in 3D, an automatized tool for deciphering the complexity of lymphoid organs.

作者信息

Sergé Arnauld, Bailly Anne-Laure, Aurrand-Lions Michel, Imhof Beat A, Irla Magali

机构信息

Centre de Recherche en Cancérologie de Marseille, Institut Paoli-Calmettes, Inserm U1068, CNRS UMR7258, Aix-Marseille Université UM105, France.

Centre de Recherche en Cancérologie de Marseille, Institut Paoli-Calmettes, Inserm U1068, CNRS UMR7258, Aix-Marseille Université UM105, France.

出版信息

J Immunol Methods. 2015 Sep;424:32-42. doi: 10.1016/j.jim.2015.04.019. Epub 2015 May 5.

DOI:10.1016/j.jim.2015.04.019
PMID:25956038
Abstract

To decipher the complex topology of lymphoid structures, we developed an automated process called Full Organ Reconstruction in 3D (For3D). A dedicated image-processing pipeline is applied to entire collections of immunolabeled serial sections, acquired with a slide-scanning microscope. This method is automated, flexible and readily applicable in two days to frozen or paraffin-embedded organs stained by fluorescence or brightfield immunohistochemistry. 3D-reconstructed organs can be visualized, rotated and analyzed to quantify substructures of interest. Usefulness of For3D is exemplified here through topological analysis of several mouse lymphoid organs exhibiting a complex organization: (i) the thymus, composed of two compartments, a medulla intricately imbricated into a surrounding cortex, (ii) lymph nodes, also highly compartmentalized into cortex, paracortex and medulla and (iii) the vascularization of an EG7 primary thymoma. This open-source algorithm, based on ImageJ and Matlab scripts, offers a user-friendly interface and is widely applicable to any organ or tissue, hence readily adaptable to a broad range of biomedical samples.

摘要

为了解析淋巴结构的复杂拓扑结构,我们开发了一种名为三维全器官重建(For3D)的自动化流程。将专门的图像处理管道应用于通过玻片扫描显微镜获取的免疫标记连续切片的整个数据集。该方法具有自动化、灵活性高的特点,并且在两天内即可轻松应用于经荧光或明场免疫组织化学染色的冷冻或石蜡包埋器官。三维重建的器官可以进行可视化、旋转和分析,以量化感兴趣的亚结构。本文通过对几个组织结构复杂的小鼠淋巴器官进行拓扑分析,例证了For3D的实用性:(i)胸腺,由两个部分组成,髓质错综复杂地交织在周围的皮质中;(ii)淋巴结,也高度分隔为皮质、副皮质和髓质;(iii)EG7原发性胸腺瘤的血管化。这种基于ImageJ和Matlab脚本的开源算法提供了用户友好的界面,并且广泛适用于任何器官或组织,因此很容易适用于广泛的生物医学样本。

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