NDLI: Cell Number Quantification of USPIO-labeled Stem Cells by MRI: An In Vitro Study

Content Provider	IEEE Xplore Digital Library
Author	Cheung, J.S. Chow, A.M. Hui, E.S. Yang, J. Hung-Fat Tse Wu, Ed.X.
Copyright Year	2006
Description	Author affiliation: Dept. of Electr. & Electron. Eng., Hong Kong Univ. (Cheung, J.S.; Chow, A.M.; Hui, E.S.; Yang, J.)
Abstract	MRI plays an expanding role in stem cell therapies. The non-invasive nature and high spatial resolution of MR imaging make MR imaging a powerful tool to investigate biologic processes at the molecular and cellular level in vivo longitudinally. Quantitative detection of stem cells after transplantation may allow assessment of stem cell localization and migration, and monitoring of the therapeutic effectiveness of stem cell therapy. In this study, we present a technique for MR quantification of magnetically labeled mouse embryonic stem cells distributed or injected in agarose gel phantoms. Apparent transverse relaxation rate enhancements (DeltaR2) were measured by gradient echo sequences. The linear relationship between DeltaR2 and the concentration of USPIO-labeled mouse embryonic stem cells was observed and used for quantifying cell density and cell number after injection or transplantation. The MRI acquisition and analysis protocol were validated by good agreement between actual cell numbers and MRI-estimated cell numbers over a wide range of cell numbers. This MR technique for cell number and cell density quantification is applicable to future in vivo studies
Sponsorship	IEEE EMB
Starting Page	476
Ending Page	479
File Size	302502
Page Count	4
File Format	PDF
ISBN	1424400325
ISSN	1557170X
DOI	10.1109/IEMBS.2006.259696
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-08-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Stem cells Magnetic resonance imaging In vitro Medical treatment High-resolution imaging In vivo Mice Embryo Spatial resolution Monitoring
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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