title: Characterization of time-course morphological features for efficient prediction of osteogenic potential in human mesenchymal stem cells.
abstract: Human bone marrow mesenchymal stem cells (hBMSCs) represents one of the most frequently applied cell sources for clinical bone regeneration. To achieve the greatest therapeutic effect, it is crucial to evaluate the osteogenic differentiation potential of the stem cells during their culture before the implantation. However, the practical evaluation of stem cell osteogenicity has been limited to invasive biological marker analysis that only enables assaying a single end-point. To innovate around invasive quality assessments in clinical cell therapy, we previously explored and demonstrated the positive predictive value of using time-course images taken during differentiation culture for hBMSC bone differentiation potential. This initial method establishes proof of concept for a morphology-based cell evaluation approach, but reveals a practical limitation when considering the need to handle large amounts of image data. In this report, we aimed to scale-down our proposed method into a more practical, efficient modeling scheme that can be more broadly implemented by physicians on the frontiers of clinical cell therapy. We investigated which morphological features are critical during the osteogenic differentiation period to assure the performance of prediction models with reduced burden on image acquisition. To our knowledge, this is the first detailed characterization that describes both the critical observation period and the critical number of time-points needed for morphological features to adequately model osteogenic potential. Our results revealed three important observations: (i) the morphological features from the first 3 days of differentiation are sufficiently informative to predict bone differentiation potential, both activities of alkaline phosphatase and calcium deposition, after 3 weeks of continuous culture; (ii) intervals of 48 h are sufficient for measuring critical morphological features; and (iii) morphological features are most accurately predictive when early morphological features from the first 3 days of differentiation are combined with later features (after 10 days of differentiation).
authors.affiliation: Department of Biotechnology, Graduate School of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Aichi, 464-8603, Japan.
authors.forename: Fumiko
authors.initials: F
authors.lastname: Matsuoka
authors.forename: Ichiro
authors.initials: I
authors.lastname: Takeuchi
authors.forename: Hideki
authors.initials: H
authors.lastname: Agata
authors.forename: Hideaki
authors.initials: H
authors.lastname: Kagami
authors.forename: Hirofumi
authors.initials: H
authors.lastname: Shiono
authors.forename: Yasujiro
authors.initials: Y
authors.lastname: Kiyota
authors.forename: Hiroyuki
authors.initials: H
authors.lastname: Honda
authors.forename: Ryuji
authors.initials: R
authors.lastname: Kato
mesh_terms: D002454:Cell Differentiation; D003584:Cytological Techniques / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D059630:Mesenchymal Stem Cells / Q000166:cytology* / Q000502:physiology*; D061848:Optical Imaging / Q000379:methods*; D010012:Osteogenesis; D013997:Time Factors
keywords: image-based analysis; mesenchymal stem cell; non-invasive analysis; osteogenic differentiation; prediction