Bajcsy Peter, Yoon Soweon, Florczyk Stephen J, Hotaling Nathan A, Simon Mylene, Szczypinski Piotr M, Schaub Nicholas J, Simon Carl G, Brady Mary, Sriram Ram D
Information Technology Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA.
Dakota Consulting Inc, Silver Spring, MD, USA.
BMC Bioinformatics. 2017 Nov 28;18(1):526. doi: 10.1186/s12859-017-1928-x.
Cell-scaffold contact measurements are derived from pairs of co-registered volumetric fluorescent confocal laser scanning microscopy (CLSM) images (z-stacks) of stained cells and three types of scaffolds (i.e., spun coat, large microfiber, and medium microfiber). Our analysis of the acquired terabyte-sized collection is motivated by the need to understand the nature of the shape dimensionality (1D vs 2D vs 3D) of cell-scaffold interactions relevant to tissue engineers that grow cells on biomaterial scaffolds.
We designed five statistical and three geometrical contact models, and then down-selected them to one from each category using a validation approach based on physically orthogonal measurements to CLSM. The two selected models were applied to 414 z-stacks with three scaffold types and all contact results were visually verified. A planar geometrical model for the spun coat scaffold type was validated from atomic force microscopy images by computing surface roughness of 52.35 nm ±31.76 nm which was 2 to 8 times smaller than the CLSM resolution. A cylindrical model for fiber scaffolds was validated from multi-view 2D scanning electron microscopy (SEM) images. The fiber scaffold segmentation error was assessed by comparing fiber diameters from SEM and CLSM to be between 0.46% to 3.8% of the SEM reference values. For contact verification, we constructed a web-based visual verification system with 414 pairs of images with cells and their segmentation results, and with 4968 movies with animated cell, scaffold, and contact overlays. Based on visual verification by three experts, we report the accuracy of cell segmentation to be 96.4% with 94.3% precision, and the accuracy of cell-scaffold contact for a statistical model to be 62.6% with 76.7% precision and for a geometrical model to be 93.5% with 87.6% precision.
The novelty of our approach lies in (1) representing cell-scaffold contact sites with statistical intensity and geometrical shape models, (2) designing a methodology for validating 3D geometrical contact models and (3) devising a mechanism for visual verification of hundreds of 3D measurements. The raw and processed data are publicly available from https://isg.nist.gov/deepzoomweb/data/ together with the web -based verification system.
细胞-支架接触测量是从成对的共配准的体积荧光共聚焦激光扫描显微镜(CLSM)图像(z轴堆叠)中获得的,这些图像来自染色细胞和三种类型的支架(即旋涂支架、大型微纤维支架和中型微纤维支架)。我们对获取的数TB大小的数据集进行分析,是出于理解与在生物材料支架上培养细胞的组织工程师相关的细胞-支架相互作用的形状维度性质(一维与二维与三维)的需要。
我们设计了五个统计接触模型和三个几何接触模型,然后使用基于与CLSM物理正交测量的验证方法,从每个类别中筛选出一个模型。将这两个选定的模型应用于414个z轴堆叠,涉及三种支架类型,所有接触结果都经过了视觉验证。通过计算表面粗糙度为52.35 nm±31.76 nm,从原子力显微镜图像验证了旋涂支架类型的平面几何模型,该粗糙度比CLSM分辨率小2至8倍。从多视图二维扫描电子显微镜(SEM)图像验证了纤维支架的圆柱模型。通过比较SEM和CLSM的纤维直径,评估纤维支架分割误差在SEM参考值的0.46%至3.8%之间。为了进行接触验证,我们构建了一个基于网络的视觉验证系统,其中包含414对细胞及其分割结果的图像,以及4968个带有细胞、支架和接触叠加动画的视频。基于三位专家的视觉验证,我们报告细胞分割的准确率为96.4%,精确率为94.3%,统计模型的细胞-支架接触准确率为62.6%,精确率为76.7%,几何模型的准确率为93.5%,精确率为87.6%。
我们方法的新颖之处在于:(1)用统计强度和几何形状模型表示细胞-支架接触位点;(2)设计一种验证三维几何接触模型的方法;(3)设计一种对数百个三维测量进行视觉验证的机制。原始数据和处理后的数据可从https://isg.nist.gov/deepzoomweb/data/以及基于网络的验证系统公开获取。