Literature DB >> 26610269

Digital Image Analysis to Assess Quantity and Morphological Quality of Isolated Pancreatic Islets.

Ling-Jia Wang1, Dixon B Kaufman.   

Abstract

Quantity and quality assessment of human pancreatic islets are essential processes to define a safe and potent quality product used for clinical transplantation. The conventional method of manual assessment has been used in the field for longer than two decades. The high degree of variability in product quantity and lack of archival imaging records of the product for verification are two major disadvantages of using the manual method for quantity and quality assessment of human pancreatic islets. Investigators have developed promising new methods for technical improvement. In this study, we briefly review the published methods and highlight the advantages of digital imaging analysis (DIA) when compared to the manual method. The application of DIA reduces measurement variability and increases the precision of islet equivalent (IEQ) determination for batch analysis. It produces images that can be archived for retrospective analysis and validation, and the data can be transmitted electronically for off-site analysis. These features are important for quality pancreatic islet assessment and are consistent with FDA requirements of current good manufacturing practice for clinical islet transplantation.

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Year:  2015        PMID: 26610269     DOI: 10.3727/096368915X689947

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


  5 in total

1.  Pancreatic beta cell/islet mass and body mass index.

Authors:  Michael P Dybala; Scott K Olehnik; Jonas L Fowler; Karolina Golab; J Michael Millis; Justyna Golebiewska; Piotr Bachul; Piotr Witkowski; Manami Hara
Journal:  Islets       Date:  2019-01-22       Impact factor: 2.694

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.  A Multiparametric Assessment of Human Islets Predicts Transplant Outcomes in Diabetic Mice.

Authors:  Hirotake Komatsu; Meirigeng Qi; Nelson Gonzalez; Mayra Salgado; Leonard Medrano; Jeffrey Rawson; Chris Orr; Keiko Omori; Jeffrey S Isenberg; Fouad Kandeel; Yoko Mullen; Ismail H Al-Abdullah
Journal:  Cell Transplant       Date:  2021 Jan-Dec       Impact factor: 4.064

Review 4.  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.  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
  5 in total

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