Moon InKyu, Ahmadzadeh Ezat, Jaferzadeh Keyvan, Kim Namgon
Department of Robotics Engineering, DGIST, 333 Techno Jungang-daero, Hyeonpung-myeon, Dalseong-gun, Daegu 42988, South Korea.
Department of Computer Engineering, Chosun University, 309 Pilmun-daero, Dong-gu, Gwangju 61452, South Korea.
Biomed Opt Express. 2019 Jan 16;10(2):610-621. doi: 10.1364/BOE.10.000610. eCollection 2019 Feb 1.
This paper investigates the rhythm strip and parameters of synchronization of human induced pluripotent stem cell (iPS) derived cardiomyocytes. The synchronization is evaluated from quantitative phase images of beating cardiomyocytes which are obtained using the time-lapse digital holographic imaging method. By quantitatively monitoring the dry mass redistribution, digital holography provides the physical contraction-relaxation signal caused by autonomous cardiac action potential. In order to analyze the synchronicity at the cell-to-cell level, we extracted single cardiac muscle cells, which contain the nuclei, from the phase images of cardiomyocytes containing multiple cells resulting from the fusion of clustering and watershed segmentation algorithms. We demonstrate that mature cardiomyocyte cell synchronization can be automatically evaluated by time-lapse microscopic holographic imaging. Our proposed method can be applied for studies on cardiomyocyte disorders and drug safety testing systems.
本文研究了人诱导多能干细胞（iPS）衍生心肌细胞的节律条和同步参数。同步性是通过使用延时数字全息成像方法获得的跳动心肌细胞的定量相位图像来评估的。通过定量监测干质量再分布，数字全息术提供了由自主心脏动作电位引起的物理收缩-舒张信号。为了在细胞间水平分析同步性，我们从通过聚类和分水岭分割算法融合产生的包含多个细胞的心肌细胞相位图像中提取了包含细胞核的单个心肌细胞。我们证明，成熟心肌细胞的细胞同步性可以通过延时显微全息成像自动评估。我们提出的方法可应用于心肌细胞疾病研究和药物安全测试系统。
