β-Cell mass is a parameter commonly measured in studies of islet biology and diabetes. However, the rigorous quantification of pancreatic β-cell mass using conventional histological methods is a time-consuming process. Rapidly evolving virtual slide technology with high-resolution slide scanners and newly developed image analysis tools has the potential to transform β-cell mass measurement. To test the effectiveness and accuracy of this new approach, we assessed pancreata from normal C57Bl/6J mice and from mouse models of β-cell ablation (streptozotocin-treated mice) and β-cell hyperplasia (leptin-deficient mice), using a standardized systematic sampling of pancreatic specimens. Our data indicate that automated analysis of virtual pancreatic slides is highly reliable and yields results consistent with those obtained by conventional morphometric analysis. This new methodology will allow investigators to dramatically reduce the time required for β-cell mass measurement by automating high-resolution image capture and analysis of entire pancreatic sections.
Posted in featured publications and tagged Animals, Artificial Intelligence, Automation, Laboratory, Cell Size, Computational Biology, Diabetes Mellitus, Experimental, Expert Systems, Hyperplasia, Image Processing, Computer-Assisted, Insulin-Secreting Cells, Mice, Mice, Inbred C57BL, Mice, Inbred Strains, Mice, Obese, Microtomy, Models, Biological, Obesity, Pancreas, Reproducibility of Results, Software.