Literature DB >> 12797374

Digital imaging as a possible approach in evaluation of islet yield.

Peter Girman1, Jan Kríz, Jozef Friedmanský, Frantisek Saudek.   

Abstract

Digital image analysis (DIA) is a new method in assessment of islet amount, which is expected to provide reliable and consistent results. We compared this method with conventional counting of small numbers of rat islets. Islets were isolated from 8 pancreases and counted in 24 samples in duplicate, first routinely by sizing according to estimated diameters under a calibrated reticule and then by processing of islets pictures taken by camera. As presumed, no significant difference was found in absolute numbers of islets per sample between DIA and conventional assessment. Volumes of islets per sample measured by DIA were on average more than 10% higher than amounts evaluated conventionally, which was statistically significant. DIA has been shown to be an important method to remove operator bias and provide consistent results. Evaluation of only two dimensions of three-dimensional objects still represents a certain limitation of this technique. With lowering of computer prices the system could become easily available for islet laboratories.

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Year:  2003        PMID: 12797374     DOI: 10.3727/000000003108746713

Source DB:  PubMed          Journal:  Cell Transplant        ISSN: 0963-6897            Impact factor:   4.064


  7 in total

1.  How to use image analysis for islet counting.

Authors:  Peter Girman; Zuzana Berkova; Eva Dobolilova; Frantisek Saudek
Journal:  Rev Diabet Stud       Date:  2008-05-10

2.  Application of Digital Image Analysis to Determine Pancreatic Islet Mass and Purity in Clinical Islet Isolation and Transplantation.

Authors:  Ling-Jia Wang; Hermann J Kissler; Xiaojun Wang; Olivia Cochet; Adam Krzystyniak; Ryosuke Misawa; Karolina Golab; Martin Tibudan; Jakub Grzanka; Omid Savari; Dixon B Kaufman; Michael Millis; Piotr Witkowski
Journal:  Cell Transplant       Date:  2014-05-06       Impact factor: 4.064

3.  Enumeration of islets by nuclei counting and light microscopic analysis.

Authors:  Anna Pisania; Klearchos K Papas; Daryl E Powers; Michael J Rappel; Abdulkadir Omer; Susan Bonner-Weir; Gordon C Weir; Clark K Colton
Journal:  Lab Invest       Date:  2010-08-09       Impact factor: 5.662

4.  Culture of equine fibroblast-like synoviocytes on synthetic tissue scaffolds towards meniscal tissue engineering: a preliminary cell-seeding study.

Authors:  Jennifer J Warnock; Derek B Fox; Aaron M Stoker; Mark Beatty; Mary Cockrell; John C Janicek; James L Cook
Journal:  PeerJ       Date:  2014-04-17       Impact factor: 2.984

Review 5.  The Flaws and Future of Islet Volume Measurements.

Authors:  Han-Hung Huang; Stephen Harrington; Lisa Stehno-Bittel
Journal:  Cell Transplant       Date:  2018-06-28       Impact factor: 4.064

6.  Validation of methodologies for quantifying isolated human islets: an Islet Cell Resources study.

Authors:  H J Kissler; J C Niland; B Olack; C Ricordi; B J Hering; A Naji; F Kandeel; J Oberholzer; L Fernandez; J Contreras; T Stiller; J Sowinski; D B Kaufman
Journal:  Clin Transplant       Date:  2009-08-30       Impact factor: 2.863

7.  A Smartphone-Fluidic Digital Imaging Analysis System for Pancreatic Islet Mass Quantification.

Authors:  Xiaoyu Yu; Pu Zhang; Yi He; Emily Lin; Huiwang Ai; Melur K Ramasubramanian; Yong Wang; Yuan Xing; José Oberholzer
Journal:  Front Bioeng Biotechnol       Date:  2021-07-19
  7 in total

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