TY - JOUR
T1 - Automated quantification study of human cardiomyocyte synchronization using holographic imaging
AU - Moon, Inkyu
AU - Ahmadzadeh, Ezat
AU - Jaferzadeh, Keyvan
AU - Kim, Namgon
N1 - Publisher Copyright:
© 2019 Optical Society of America.
PY - 2019
Y1 - 2019
N2 - 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 k-means 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.
AB - 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 k-means 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.
UR - http://www.scopus.com/inward/record.url?scp=85061556787&partnerID=8YFLogxK
U2 - 10.1364/BOE.10.000610
DO - 10.1364/BOE.10.000610
M3 - Article
AN - SCOPUS:85061556787
SN - 2156-7085
VL - 10
SP - 610
EP - 621
JO - Biomedical Optics Express
JF - Biomedical Optics Express
IS - 2
ER -