Automated quantification of pancreatic β-cell mass

Maria L. Golson, William S. Bush, Marcela Brissova

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish (US)
Pages (from-to)E1460-E1467
JournalAmerican Journal of Physiology - Endocrinology and Metabolism
Volume306
Issue number12
DOIs
StatePublished - Jun 15 2014
Externally publishedYes

Keywords

  • Automated analysis
  • Diabetes
  • Pancreatic islets
  • β-cell mass

ASJC Scopus subject areas

  • Endocrinology, Diabetes and Metabolism
  • Physiology
  • Physiology (medical)

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