Literature DB >> 9786067

Improved assessment of isolated islet tissue volume using digital image analysis.

J P Stegemann1, J J O'Neil, D T Nicholson, C J Mullon.   

Abstract

Accurate and consistent measurement of tissue volume is critical to performing many types of islet research; however, conventional visual determination of isolated islet yields through a microscope is heavily operator dependent. An improved method of islet volume determination using digital image analysis (DIA) was developed to remove operator bias and automate the islet counting process. A series of 140 porcine islet isolations were used to evaluate the DIA method in three separate stages. In Stage 1 (n = 29 isolations), the conventional and DIA methods were correlated with two other independent islet quantitation methods: insulin extraction, and DNA extraction. It was found that volumes determined by DIA correlated more closely with insulin content and DNA content than did conventionally determined volumes. In Stages 2 and 3 (n = 54 and 57 isolations, respectively), it was shown that an increase in the number of fields analyzed by DIA did not significantly improve the quality of the correlations. Inclusion of very small tissue (<50 microm in diameter), which is ignored in the conventional protocol affected yields by less than 10% and did not significantly improve the correlation with insulin or DNA content. Quantitation of isolated islet tissue volume using DIA has been shown to be rapid, consistent, and objective. In the laboratory, use of this method as the standard for islet volume measurement will allow more meaningful comparison of experimental results between centers. In the clinic, its use will allow more accurate dosing of transplanted tissue.

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Year:  1998        PMID: 9786067     DOI: 10.1177/096368979800700506

Source DB:  PubMed          Journal:  Cell Transplant        ISSN: 0963-6897            Impact factor:   4.139


  4 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.  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

  4 in total

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