Image-Based Cell Quality Assessment: Modeling of Cell Morphology and Quality for Clinical Cell Therapy - Computational Modeling in Tissue Engineering - page 199

Image-Based Cell Quality Assessment:
Modeling of Cell Morphology and Quality
for Clinical Cell Therapy

Hiroto Sasaki, Fumiko Matsuoka, Wakana Yamamoto,
Kenji Kojima, Hiroyuki Honda and Ryuji Kato

Abstract In clinical tissue engineering, both safety and effectiveness are definite
requirements that should be satisfied. Conventional cell biology techniques are
facing limitations in the quality assurance step of cell production for clinical
therapy. Image-based cell quality assessment offers a great potential, because it is
the only way to non-destructively and repeatedly assess cellular phenotypes and
irregularities. To effectively assess cell quality using the multiple parameters
derived from time course cell imaging, machine learning models, which have been
effectively used to connect biological phenomena with biological measurements in
the field of bioinformatics, are promising approaches for achieving high accuracy.
Here, we present the recent results of our successful cell quality modeling and
discuss its possibility and considerations on further application in clinical cell
therapy.

1 Introduction

In clinical tissue engineering and cell therapy, although the cell is a ''live mate-
rial'' with great variety and a highly sensitive nature, its production should be
strictly controlled for safe and effective therapy.
If cellular irregularity is overlooked, it could cause serious side-effects such as
tumorigenesis [ 14 ]. If cell yields do not fulfill the criteria on the day of the
operation, the operation has to be cancelled or the cells be used with less activity.

H. Sasaki F. Matsuoka W. Yamamoto
K. Kojima H. Honda R. Kato ( )

Department of Biotechnology, Graduate School of Engineering,
Nagoya University, Furocho, Chikusaku, Nagoya 464-8603, Japan
e-mail: [e-mail]

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