AutoTube: a novel software for the automated morphometric analysis of vascular networks in tissues.
AutoTube: a novel software for the automated morphometric analysis of vascular networks in tissues.
复制标题
AutoTube：用于组织血管网络自动形态分析的新型软件。
DOI：
10.1007/s10456-018-9652-3
复制
发表时间：
2019-05
期刊：
影响因子：
9.8
通讯作者：
Halin C
中科院分区：
文献类型：
--
作者：
Montoya-Zegarra JA;Russo E;Runge P;Jadhav M;Willrodt AH;Stoma S;Nørrelykke SF;Detmar M;Halin C
由于它们参与许多生理和病理过程，因此对鉴定介导血管和淋巴管的形成和功能的新分子途径有很大兴趣。血管研究越来越多地涉及基于图像的分析和定量的血管网络在组织整体安装或管状结构形成的培养内皮细胞在体外。虽然这两种类型的实验提供了重要的机械见解（淋巴）血管生成过程中，手动分析和定量的实验通常是劳动密集型的，并受实验者之间的差异。为了绕过这些问题，我们开发了AutoTube，这是一种新的软件，可以量化组织和体外试验中血管覆盖面积，血管宽度，骨骼长度和血管网络的分支或交叉点等参数。AutoTube可免费下载，包括直观的图形用户界面，并有助于以快速、自动和可重复的方式执行其他非常耗时的图像分析。通过分析由不同组织或已知血管异常的基因靶向小鼠制备的整体标本中的淋巴和血管网络，我们证明了AutoTube能够与手动分析密切一致地确定血管参数，并识别组织中血管形态和体外试验中形成的血管网络的统计学显著差异。本文的在线版本（10.1007/s10456-018-9652-3）包含补充材料，可供授权用户使用。
Due to their involvement in many physiologic and pathologic processes, there is a great interest in identifying new molecular pathways that mediate the formation and function of blood and lymphatic vessels. Vascular research increasingly involves the image-based analysis and quantification of vessel networks in tissue whole-mounts or of tube-like structures formed by cultured endothelial cells in vitro. While both types of experiments deliver important mechanistic insights into (lymph)angiogenic processes, the manual analysis and quantification of such experiments are typically labour-intensive and affected by inter-experimenter variability. To bypass these problems, we developed AutoTube, a new software that quantifies parameters like the area covered by vessels, vessel width, skeleton length and branching or crossing points of vascular networks in tissues and in in vitro assays. AutoTube is freely downloadable, comprises an intuitive graphical user interface and helps to perform otherwise highly time-consuming image analyses in a rapid, automated and reproducible manner. By analysing lymphatic and blood vascular networks in whole-mounts prepared from different tissues or from gene-targeted mice with known vascular abnormalities, we demonstrate the ability of AutoTube to determine vascular parameters in close agreement to the manual analyses and to identify statistically significant differences in vascular morphology in tissues and in vascular networks formed in in vitro assays. The online version of this article (10.1007/s10456-018-9652-3) contains supplementary material, which is available to authorized users.
登录
查看更多内容
影响因子：
8
作者：
KITTLER, J;ILLINGWORTH, J
通讯作者：
ILLINGWORTH, J
影响因子：
2.7
作者：
Merks, RMH;Brodsky, SV;Glazier, JA
通讯作者：
Glazier, JA
影响因子：
32.4
作者：
Meier, Dominik;Bornmann, Caroline;Finke, Daniela
通讯作者：
Finke, Daniela
影响因子：
4.6
作者：
Ochsenbein, Alexandra M.;Karaman, Sinem;Detmar, Michael
通讯作者：
Detmar, Michael
影响因子：
7.2
作者：
Dhondt, Stijn;Van Haerenborgh, Dirk;Inze, Dirk
通讯作者：
Inze, Dirk