2011 - CTS-IXA


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SOTA 10- Cell Processing for Transplantation (Cell Track)

41.545 - Quantitative assessment of islet cell products: improving standard and digital image analysis methods

Presenter: Peter, Buchwald, Miami, United States
Authors: Peter Buchwald

545

Quantitative assessment of islet cell products: improving standard and digital image analysis methods

Peter Buchwald

Diabetes Research Institute and Molecular and Cellular Pharmacology, Miller School of Medicine, University of Miami, Miami, FL, United States

The accurate assessment of islet cell preparations used for research and especially transplantation purposes is of crucial relevance; however, a standardized, easy to implement, and reliable method is still lacking. Most of the problem is due to the random distribution of islets and the relatively large contribution to the total volume (IEQ number) by only a few large islets. From the quantitative analysis of more than 200 human isolations performed at our institute, we found that the size distribution of isolated islets is well described by a Weibull distribution function and that larger islets (d>250μm) still contribute a considerable fraction (>25%) to the total IEQ content despite their low numbers (≈5%). By using an ‘artificial islet’ microsphere mixture that reproduces the size-distribution of isolated human islets, we found that the current standard manual method used to quantify islet preparations gives an acceptable reproduction of the IEQ content and frequency distribution. However, the variability in the IEQ estimate is still quite large even with clinical good manufacturing practices (cGMP) trained operators (coefficient of variability, CV≈30%; n=6). Fully computerized digital image analysis-based methods can provide a convenient approach to replace the current manual counting protocol(s), and if adequately standardized, they could provide a reliable and reproducible method that could reduce the existing inter-operator as well as inter-center variability in quantitating islet cell products. Our assessments of a DIA-based automatic ICC using both human and nonhuman primate (NHP) islet samples found that its total IEQ counts were in good agreement with the average of trained operators (r2>0.95). By counting individual islet volume contributions, DIA can provide more accurate estimates than those obtainable by the current practice of grouping in 50μm size-groups; however, this might require a recalibration as the current group-based method seems to give an about 10% overcount of the actual IEQ.


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