Literature DB >> 24806436

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

Ling-Jia Wang1, 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.   

Abstract

Pancreatic islet mass, represented by islet equivalent (IEQ), is the most important parameter in decision making for clinical islet transplantation. To obtain IEQ, the sample of islets is routinely counted under a microscope and discarded thereafter. Islet purity, another parameter in islet processing, is routinely assessed by estimation only. In this study, we validated our digital image analysis (DIA) system by using the software of Image Pro Plus and a custom-designed Excel template to assess islet mass and purity to better comply with current good manufacturing practice (cGMP) standards. Human islet samples (60 collected from a single isolation and 24 collected from 12 isolations) were captured as calibrated digital images for the permanent record. Seven trained technicians participated in determination of IEQ and purity by the manual counting method (manual image counting, Manual I) and DIA. IEQ count showed statistically significant correlations between the Manual I and DIA in all sample comparisons (r > 0.819 and p < 0.0001). A statistically significant difference in IEQ between Manual I and DIA was not found in all sample groups (p > 0.05). In terms of purity determination, statistically significant differences between assessment and DIA measurement were found in high-purity 100-µl samples (p < 0.005) and low-purity 100-µl samples (p < 0.001) of the single isolation. In addition, islet particle number (IPN) and the IEQ/IPN ratio did not differ statistically between Manual I and DIA. In conclusion, the DIA used in this study is a reliable technique to determine IEQ and purity. Islet sample preserved as a digital image and results produced by DIA can be permanently stored for verification, technical training, and information exchange among islet centers. Therefore, DIA complies better with cGMP requirements than the manual counting method. We propose DIA as a quality control tool to supplement the established standard manual method for islet counting and purity estimation.

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Year:  2014        PMID: 24806436      PMCID: PMC4436081          DOI: 10.3727/096368914X681612

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


  10 in total

1.  Areal density measurement is a convenient method for the determination of porcine islet equivalents without counting and sizing individual islets.

Authors:  N Lembert; J Wesche; P Petersen; M Doser; H D Becker; H P T Ammon
Journal:  Cell Transplant       Date:  2003       Impact factor: 4.064

2.  Computer-assisted digital image analysis to quantify the mass and purity of isolated human islets before transplantation.

Authors:  Nadja Niclauss; Antonino Sgroi; Philippe Morel; Reto Baertschiger; Mathieu Armanet; Anne Wojtusciszyn; Geraldine Parnaud; Yannick Muller; Thierry Berney; Domenico Bosco
Journal:  Transplantation       Date:  2008-12-15       Impact factor: 4.939

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

Authors:  Peter Girman; Jan Kríz; Jozef Friedmanský; Frantisek Saudek
Journal:  Cell Transplant       Date:  2003       Impact factor: 4.064

4.  Quantitative assessment of islet cell products: estimating the accuracy of the existing protocol and accounting for islet size distribution.

Authors:  Peter Buchwald; Xiaojing Wang; Aisha Khan; Andres Bernal; Chris Fraker; Luca Inverardi; Camillo Ricordi
Journal:  Cell Transplant       Date:  2009-10-09       Impact factor: 4.064

5.  Quantification of the islet product: presentation of a standardized current good manufacturing practices compliant system with minimal variability.

Authors:  Andrew S Friberg; Heide Brandhorst; Peter Buchwald; Masafumi Goto; Camillo Ricordi; Daniel Brandhorst; Olle Korsgren
Journal:  Transplantation       Date:  2011-03-27       Impact factor: 4.939

6.  International trial of the Edmonton protocol for islet transplantation.

Authors:  A M James Shapiro; Camillo Ricordi; Bernhard J Hering; Hugh Auchincloss; Robert Lindblad; R Paul Robertson; Antonio Secchi; Mathias D Brendel; Thierry Berney; Daniel C Brennan; Enrico Cagliero; Rodolfo Alejandro; Edmond A Ryan; Barbara DiMercurio; Philippe Morel; Kenneth S Polonsky; Jo-Anna Reems; Reinhard G Bretzel; Federico Bertuzzi; Tatiana Froud; Raja Kandaswamy; David E R Sutherland; George Eisenbarth; Miriam Segal; Jutta Preiksaitis; Gregory S Korbutt; Franca B Barton; Lisa Viviano; Vicki Seyfert-Margolis; Jeffrey Bluestone; Jonathan R T Lakey
Journal:  N Engl J Med       Date:  2006-09-28       Impact factor: 91.245

7.  Automated digital image analysis of islet cell mass using Nikon's inverted eclipse Ti microscope and software to improve engraftment may help to advance the therapeutic efficacy and accessibility of islet transplantation across centers.

Authors:  Valery Gmyr; Caroline Bonner; Bruno Lukowiak; Valerie Pawlowski; Nathalie Dellaleau; Sandrine Belaich; Isanga Aluka; Ericka Moermann; Julien Thevenet; Rimed Ezzouaoui; Gurvan Queniat; Francois Pattou; Julie Kerr-Conte
Journal:  Cell Transplant       Date:  2013-05-15       Impact factor: 4.064

8.  Islet autotransplant outcomes after total pancreatectomy: a contrast to islet allograft outcomes.

Authors:  David E R Sutherland; Angelika C Gruessner; Annelisa M Carlson; Juan J Blondet; A N Balamurugan; Katie F Reigstad; Gregory J Beilman; Melena D Bellin; Bernhard J Hering
Journal:  Transplantation       Date:  2008-12-27       Impact factor: 4.939

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

Authors:  J P Stegemann; J J O'Neil; D T Nicholson; C J Mullon
Journal:  Cell Transplant       Date:  1998 Sep-Oct       Impact factor: 4.139

10.  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

  10 in total
  5 in total

1.  Effect of Manufacturing Procedures on Human Islet Isolation From Donor Pancreata Standardized by the North American Islet Donor Score.

Authors:  Chun-Chieh Yeh; Ling-Jia Wang; James J McGarrigle; Yong Wang; Chien-Chang Liao; Mustafa Omami; Arshad Khan; Mohammad Nourmohammadzadeh; Joshua Mendoza-Elias; Benjamin McCracken; Enza Marchese; Barbara Barbaro; Jose Oberholzer
Journal:  Cell Transplant       Date:  2016-08-12       Impact factor: 4.064

Review 2.  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

3.  Pancreatic human islets and insulin-producing cells derived from embryonic stem cells are rapidly identified by a newly developed Dithizone.

Authors:  Bashar Khiatah; Meirigeng Qi; Youjun Wu; Kuan-Tsen Chen; Rachel Perez; Luis Valiente; Keiko Omori; Jeffrey S Isenberg; Fouad Kandeel; Jiing-Kuan Yee; Ismail H Al-Abdullah
Journal:  Sci Rep       Date:  2019-06-26       Impact factor: 4.379

Review 4.  The Landscape of Digital Pathology in Transplantation: From the Beginning to the Virtual E-Slide.

Authors:  Ilaria Girolami; Anil Parwani; Valeria Barresi; Stefano Marletta; Serena Ammendola; Lavinia Stefanizzi; Luca Novelli; Arrigo Capitanio; Matteo Brunelli; Liron Pantanowitz; Albino Eccher
Journal:  J Pathol Inform       Date:  2019-07-01

Review 5.  Building Biomimetic Potency Tests for Islet Transplantation.

Authors:  Aaron L Glieberman; Benjamin D Pope; Douglas A Melton; Kevin Kit Parker
Journal:  Diabetes       Date:  2021-02       Impact factor: 9.461

  5 in total

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