Dynamic Image Analysis of Human Embryonic Stem Cells to Monitor Pluripotency

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DESCRIPTION (provided by applicant): Human embryonic stem cells (hESC) have great potential for cellular therapy because they are pluripotent. Analytical reliable methodologies for the non-destructive non-invasive quality evaluation and assurance for hESC production would be of great benefit to cellular therapy, drug screening and other uses of hESC. We have found that hESC colony texture and border characteristics provide useful features for determining the colony's level of pluripotency (Mangoubi et al., submitted to IEEE Trans. Biomed. Eng.). Cellular characteristics of pluripotent hESC include nuclear hyperdynamics and lack of chromatin condensation. We propose to develop image based texture and border analysis analytical algorithms that would measure 1) the kinetics of whole hESC colony texture and borders and 2) the kinetics of cell nuclei texture. The methodology is to be used as a quality assurance tool for hESC production by measuring the kinetics of single cell nuclei, chromatin dynamics and heterochromatin formation as pluripotent cells differentiate into neuronal lineages. Our objective is to apply and continue to develop our new signal and image processing methodologies for application to hESC biology. These image processing based methods will be specifically used to 1) evaluate the pluripotency of multicell colonies and single cell nuclei, 2) predict the time history of colony fate, and 3) predict the dynamics of cell production. Development of the stem cell non-destructive evaluation methodology would require beyond state of the art analytical algorithms in the following areas: Parametric and non-Parametric classification, efficient variational segmentation and curve evolution methods, innovative border crispness and diffusivity analysis, non-Gaussian subspace learning and detection methods, and multi-resolution hierarchical dynamic models. Our objective is to develop these analytical tools for quantitative measurement of amorphous cellular and subcellular structures, though these innovations will benefit areas of medical imaging ranging from fMRI to tissue engineering. Our aims include: 1) The development of mathematical image processing methods for quantitatively distinguishing the texture and border of pluripotent from differentiated individual stem cells and colonies, 2) the extension of these methods to kinetic images for measuring dynamic changes in stem cell textures and borders, and 3) the development of spatio-temporal dynamic and control models that predict and help maintain the quality of hESC.