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2 November 2017 Method for evaluation of human induced pluripotent stem cell quality using image analysis based on the biological morphology of cells
Takashi Wakui, Tsuyoshi Matsumoto, Kenta Matsubara, Tomoyuki Kawasaki, Hiroshi Yamaguchi, Hidenori Akutsu
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Journal of Medical Imaging, Vol. 4, Issue 4, 044003 (November 2017). https://doi.org/10.1117/1.JMI.4.4.044003
Abstract
We propose an image analysis method for quality evaluation of human pluripotent stem cells based on biologically interpretable features. It is important to maintain the undifferentiated state of induced pluripotent stem cells (iPSCs) while culturing the cells during propagation. Cell culture experts visually select good quality cells exhibiting the morphological features characteristic of undifferentiated cells. Experts have empirically determined that these features comprise prominent and abundant nucleoli, less intercellular spacing, and fewer differentiating cellular nuclei. We quantified these features based on experts’ visual inspection of phase contrast images of iPSCs and found that these features are effective for evaluating iPSC quality. We then developed an iPSC quality evaluation method using an image analysis technique. The method allowed accurate classification, equivalent to visual inspection by experts, of three iPSC cell lines.
CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
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Takashi Wakui, Tsuyoshi Matsumoto, Kenta Matsubara, Tomoyuki Kawasaki, Hiroshi Yamaguchi, and Hidenori Akutsu "Method for evaluation of human induced pluripotent stem cell quality using image analysis based on the biological morphology of cells," Journal of Medical Imaging 4(4), 044003 (2 November 2017). https://doi.org/10.1117/1.JMI.4.4.044003
Received: 30 May 2017; Accepted: 16 October 2017; Published: 2 November 2017
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Cited by 27 scholarly publications and 2 patents.
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KEYWORDS
Optical inspection
Image analysis
Image quality
Stem cells
Sensors
Image processing
Inspection
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