title: Combining quantitative 2D and 3D image analysis in the serial block face SEM: application to secretory organelles of pancreatic islet cells.
abstract: A combination of two-dimensional (2D) and three-dimensional (3D) analyses of tissue volume ultrastructure acquired by serial block face scanning electron microscopy can greatly shorten the time required to obtain quantitative information from big data sets that contain many billions of voxels. Thus, to analyse the number of organelles of a specific type, or the total volume enclosed by a population of organelles within a cell, it is possible to estimate the number density or volume fraction of that organelle using a stereological approach to analyse randomly selected 2D block face views through the cells, and to combine such estimates with precise measurement of 3D cell volumes by delineating the plasma membrane in successive block face images. The validity of such an approach can be easily tested since the entire 3D tissue volume is available in the serial block face scanning electron microscopy data set. We have applied this hybrid 3D/2D technique to determine the number of secretory granules in the endocrine α and β cells of mouse pancreatic islets of Langerhans, and have been able to estimate the total insulin content of a β cell.
authors.affiliation: National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, Maryland, U.S.A.
authors.forename: A
authors.initials: A
authors.lastname: Shomorony
authors.affiliation: National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, Maryland, U.S.A.
authors.forename: C R
authors.initials: CR
authors.lastname: Pfeifer
authors.affiliation: National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, Maryland, U.S.A.
authors.forename: M A
authors.initials: MA
authors.lastname: Aronova
authors.affiliation: National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, Maryland, U.S.A.
authors.forename: G
authors.initials: G
authors.lastname: Zhang
authors.affiliation: National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, Maryland, U.S.A.
authors.forename: T
authors.initials: T
authors.lastname: Cai
authors.affiliation: National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, Maryland, U.S.A.
authors.forename: H
authors.initials: H
authors.lastname: Xu
authors.affiliation: National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, Maryland, U.S.A.
authors.forename: A L
authors.initials: AL
authors.lastname: Notkins
authors.affiliation: National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, Maryland, U.S.A.
authors.forename: R D
authors.initials: RD
authors.lastname: Leapman
mesh_terms: D000818:Animals; D050416:Glucagon-Secreting Cells / Q000648:ultrastructure*; D021621:Imaging, Three-Dimensional; D007328:Insulin / Q000032:analysis*; D050417:Insulin-Secreting Cells / Q000737:chemistry / Q000648:ultrastructure*; D008297:Male; D051379:Mice; D008855:Microscopy, Electron, Scanning / Q000379:methods*; D022142:Secretory Vesicles / Q000648:ultrastructure*
chemical_list: D007328:Insulin
keywords: pancreatic islets; secretory granules; serial block face SEM; stereology; α cells; β cells