Characterization of the complete fiber network topology of planar fibrous tissues and scaffolds.
Characterization of the complete fiber network topology of planar fibrous tissues and scaffolds.
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DOI：
10.1016/j.biomaterials.2010.03.052
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发表时间：
2010-07
期刊：
影响因子：
14
通讯作者：
Sacks MS
中科院分区：
文献类型：
--
作者：
D'Amore A;Stella JA;Wagner WR;Sacks MS
理解工程化组织支架结构如何影响细胞形态、代谢、表型表达以及预测材料的力学行为，近来受到了越来越多的关注。在本研究中，提出了一种基于图像的分析方法，该方法提供了一种自动工具来表征工程化组织纤维网络拓扑结构。对完全定义纤维网络拓扑结构的微观结构特征进行了检测和量化，包括纤维取向、连通性、交叉点空间密度和直径。使用电纺聚（酯氨酯）脲（ES - PEUU）支架的扫描电子显微镜（SEM）图像对算法性能进行了测试。还分析了接种兔间充质干细胞（MSC）的胶原凝胶支架和脱细胞大鼠颈动脉的SEM图像，以进一步评估该算法无论支架类型和所评估的尺寸尺度如何都能捕捉纤维网络形态的能力。通过将人工操作员（n = 5）手动检测的纤维网络拓扑结构与算法自动检测的结果进行定性和定量比较，对图像分析过程进行了验证。纤维角度分布和纤维连通性分布的手动检测结果与算法检测结果之间的相关值分别为0.86和0.93。算法检测到的纤维交叉点和纤维直径值与人工操作员检测到的值相当（在平均值±标准差范围内）。这种自动化方法识别并量化了纤维网络形态，如对三种相关支架类型所展示的那样，并提供了一种手段来：（1）保证客观性，（2）显著减少分析时间，以及（3）促进对支架结构在体外和体内对细胞行为和组织发育影响的更广泛分析。
Understanding how engineered tissue scaffold architecture affects cell morphology, metabolism, phenotypic expression, as well as predicting material mechanical behavior have recently received increased attention. In the present study, an image-based analysis approach that provides an automated tool to characterize engineered tissue fiber network topology is presented. Micro-architectural features that fully defined fiber network topology were detected and quantified, which include fiber orientation, connectivity, intersection spatial density, and diameter. Algorithm performance was tested using scanning electron microscopy (SEM) images of electrospun poly(ester urethane)urea (ES-PEUU) scaffolds. SEM images of rabbit mesenchymal stem cell (MSC) seeded collagen gel scaffolds and decellularized rat carotid arteries were also analyzed to further evaluate the ability of the algorithm to capture fiber network morphology regardless of scaffold type and the evaluated size scale. The image analysis procedure was validated qualitatively and quantitatively, comparing fiber network topology manually detected by human operators (n=5) with that automatically detected by the algorithm. Correlation values between manual detected and algorithm detected results for the fiber angle distribution and for the fiber connectivity distribution were 0.86 and 0.93 respectively. Algorithm detected fiber intersections and fiber diameter values were comparable (within the mean ± standard deviation) with those detected by human operators. This automated approach identifies and quantifies fiber network morphology as demonstrated for three relevant scaffold types and provides a means to: (1) guarantee objectivity, (2) significantly reduce analysis time, and (3) potentiate broader analysis of scaffold architecture effects on cell behavior and tissue development both in vitro and in vivo.
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影响因子：
14
作者：
Hashizume, Ryotaro;Fujimoto, Kazuro L.;Hong, Yi;Amoroso, Nicholas J.;Tobita, Kimimasa;Miki, Toshio;Keller, Bradley B.;Sacks, Michael S.;Wagner, William R.
通讯作者：
Wagner, William R.
影响因子：
14
作者：
Bashur, Chris A.;Dahlgren, Linda A.;Goldstein, Aaron S.
通讯作者：
Goldstein, Aaron S.
DOI：
10.1002/jbm.10204
发表时间：
2002-09-05
期刊：
JOURNAL OF BIOMEDICAL MATERIALS RESEARCH
影响因子：
--
作者：
Guan, JJ;Sacks, MS;Wagner, WR
通讯作者：
Wagner, WR
DOI：
10.1115/1.1385843
发表时间：
2001-08-01
影响因子：
1.7
作者：
Agoram, B;Barocas, VH
通讯作者：
Barocas, VH
影响因子：
3.5
作者：
Burd, Harvey John
通讯作者：
Burd, Harvey John