Automated measurement of cardiomyocyte monolayer contraction using the Exeter Multiscope

Alexander D Corbett, David Horsell, Taylor Watters, Shahrum Ghasemi, Lewis Henderson, Sharika Mohanan, Caroline Mullenbroich, Gil Bub, Francis Burton, Godfrey L Smith
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Abstract

We apply a novel microscope architecture, the Exeter Multiscope, to the problem of acquiring image data in rapid succession from nine wells of a 96 well plate. We demonstrate that the new microscope can detect contraction in cardiomyocyte monolayers which have been plated into these wells. Each well is sampled using 500 x 500 pixels across a 1.4 x 1.4 mm field of view, acquired in three colours at 3.7 Hz per well. The use of multiple illumination wavelengths provides post-hoc focus selection, further increasing the level of automation. The performance of the Exeter Multiscope is benchmarked against industry standard methods using a commercial microscope with a motorised stage and demonstrates that the Multiscope can acquire data almost 40 times faster. The data from both Multiscope and the commercial systems are processed by a 'pixel variance' algorithm that uses information from the pixel value variability over time to determine the timing and amplitude of tissue contraction. This algorithm is also benchmarked against an existing algorithm that employs an absolute difference measure of tissue contraction.
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使用 Exeter Multiscope 自动测量心肌细胞单层收缩力
我们应用了一种新型显微镜结构--埃克塞特多孔显微镜(Exeter Multiscope),以解决从 96 孔板的九个孔中快速连续获取图像数据的问题。我们证明,这种新型显微镜可以检测到被放入这些孔中的心肌细胞单层的收缩情况。在 1.4 x 1.4 毫米的视场中,每孔使用 500 x 500 像素采样,以 3.7 Hz 的频率采集三色图像。使用多种照明波长可进行事后聚焦选择,进一步提高了自动化水平。Exeter Multiscope 的性能以使用带电动平台的商用显微镜的行业标准方法为基准,结果表明 Multiscope 的数据采集速度几乎快 40 倍。Multiscope 和商用系统的数据均由 "像素方差 "算法处理,该算法利用像素值随时间变化的信息来确定组织收缩的时间和幅度。该算法还与采用绝对差值测量组织收缩的现有算法进行了比较。
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