title: Non-invasive quality evaluation of confluent cells by image-based orientation heterogeneity analysis.
abstract: In recent years, cell and tissue therapy in regenerative medicine have advanced rapidly towards commercialization. However, conventional invasive cell quality assessment is incompatible with direct evaluation of the cells produced for such therapies, especially in the case of regenerative medicine products. Our group has demonstrated the potential of quantitative assessment of cell quality, using information obtained from cell images, for non-invasive real-time evaluation of regenerative medicine products. However, image of cells in the confluent state are often difficult to evaluate, because accurate recognition of cells is technically difficult and the morphological features of confluent cells are non-characteristic. To overcome these challenges, we developed a new image-processing algorithm, heterogeneity of orientation (H-Orient) processing, to describe the heterogeneous density of cells in the confluent state. In this algorithm, we introduced a Hessian calculation that converts pixel intensity data to orientation data and a statistical profiling calculation that evaluates the heterogeneity of orientations within an image, generating novel parameters that yield a quantitative profile of an image. Using such parameters, we tested the algorithm's performance in discriminating different qualities of cellular images with three types of clinically important cell quality check (QC) models: remaining lifespan check (QC1), manipulation error check (QC2), and differentiation potential check (QC3). Our results show that our orientation analysis algorithm could predict with high accuracy the outcomes of all types of cellular quality checks (>84% average accuracy with cross-validation).
authors.affiliation: Graduate School of Science and Engineering, Yamagata University, Jonan, Yonezawa, Yamagata 992-8510, Japan.
authors.forename: Kei
authors.initials: K
authors.lastname: Sasaki
authors.affiliation: Graduate School of Engineering, Nagoya University, Furocho, Chikusa-ku, Aichi 466-8602, Japan.
authors.forename: Hiroto
authors.initials: H
authors.lastname: Sasaki
authors.affiliation: Graduate School of Pharmaceutical Sciences, Nagoya University, Furocho, Chikusa-ku, Aichi 466-8601, Japan.
authors.forename: Atsuki
authors.initials: A
authors.lastname: Takahashi
authors.affiliation: Graduate School of Science and Engineering, Yamagata University, Jonan, Yonezawa, Yamagata 992-8510, Japan.
authors.forename: Siu
authors.initials: S
authors.lastname: Kang
authors.affiliation: Graduate School of Science and Engineering, Yamagata University, Jonan, Yonezawa, Yamagata 992-8510, Japan.
authors.forename: Tetsuya
authors.initials: T
authors.lastname: Yuasa
authors.affiliation: Graduate School of Pharmaceutical Sciences, Nagoya University, Furocho, Chikusa-ku, Aichi 466-8601, Japan. Electronic address: kato-r@ps.nagoya-u.ac.jp.
authors.forename: Ryuji
authors.initials: R
authors.lastname: Kato
mesh_terms: D000328:Adult; D000465:Algorithms; D048430:Cell Shape; D002478:Cells, Cultured; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D044968:Regenerative Medicine / Q000379:methods; D015203:Reproducibility of Results
keywords: Cellular quality; Confluent cells; Image-based analysis; Microscopic image; Orientation complexity