BACKGROUND: Quantification of islet mass is a crucial criterion for defining the quality of the islet product ensuring a potent islet transplant when used as a therapeutic intervention for select patients with type I diabetes. METHODS: This multi-center study involved all eight member institutions of the National Institutes of Health-supported Islet Cell Resources Consortium. The study was designed to validate the standard counting procedure for quantifying isolated, dithizone-stained human islets as a reliable methodology by ascertaining the accuracy, repeatability (intra-observer variability), and intermediate precision (inter-observer variability). The secondary aim of the study was to evaluate a new software-assisted digital image analysis method as a supplement for islet quantification. RESULTS: The study demonstrated the accuracy, repeatability and intermediate precision of the standard counting procedure for isolated human islets. This study also demonstrated that software-assisted digital image analysis as a supplemental method for islet quantification was more accurate and consistent than the standard manual counting method. CONCLUSIONS: Standard counting procedures for enumerating isolated stained human islets is a valid methodology, but computer-assisted digital image analysis assessment of islet mass has the added benefit of providing a permanent record of the isolated islet product being evaluated that improves quality assurance operations of current good manufacturing practice.
BACKGROUND: Quantification of islet mass is a crucial criterion for defining the quality of the islet product ensuring a potent islet transplant when used as a therapeutic intervention for select patients with type I diabetes. METHODS: This multi-center study involved all eight member institutions of the National Institutes of Health-supported Islet Cell Resources Consortium. The study was designed to validate the standard counting procedure for quantifying isolated, dithizone-stained human islets as a reliable methodology by ascertaining the accuracy, repeatability (intra-observer variability), and intermediate precision (inter-observer variability). The secondary aim of the study was to evaluate a new software-assisted digital image analysis method as a supplement for islet quantification. RESULTS: The study demonstrated the accuracy, repeatability and intermediate precision of the standard counting procedure for isolated human islets. This study also demonstrated that software-assisted digital image analysis as a supplemental method for islet quantification was more accurate and consistent than the standard manual counting method. CONCLUSIONS: Standard counting procedures for enumerating isolated stained human islets is a valid methodology, but computer-assisted digital image analysis assessment of islet mass has the added benefit of providing a permanent record of the isolated islet product being evaluated that improves quality assurance operations of current good manufacturing practice.
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