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. Issue 1 (January 2015)
- Record Type:
- Journal Article
- Title:
- 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. Issue 1 (January 2015)
- Main Title:
- 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:
- Gmyr, Valery
Bonner, Caroline
Lukowiak, Bruno
Pawlowski, Valerie
Dellaleau, Nathalie
Belaich, Sandrine
Aluka, Isanga
Moermann, Ericka
Thevenet, Julien
Ezzouaoui, Rimed
Queniat, Gurvan
Pattou, Francois
Kerr-Conte, Julie - Abstract:
- Reliable assessment of islet viability, mass, and purity must be met prior to transplanting an islet preparation into patients with type 1 diabetes. The standard method for quantifying human islet preparations is by direct microscopic analysis of dithizone-stained islet samples, but this technique may be susceptible to inter-/intraobserver variability, which may induce false positive/negative islet counts. Here we describe a simple, reliable, automated digital image analysis (ADIA) technique for accurately quantifying islets into total islet number, islet equivalent number (IEQ), and islet purity before islet transplantation. Islets were isolated and purified from n = 42 human pancreata according to the automated method of Ricordi et al. For each preparation, three islet samples were stained with dithizone and expressed as IEQ number. Islets were analyzed manually by microscopy or automatically quantified using Nikon's inverted Eclipse Ti microscope with built-in NIS-Elements Advanced Research (AR) software. The AIDA method significantly enhanced the number of islet preparations eligible for engraftment compared to the standard manual method ( p < 0.001). Comparisons of individual methods showed good correlations between mean values of IEQ number ( r 2 = 0.91) and total islet number ( r 2 = 0.88) and thus increased to r 2 = 0.93 when islet surface area was estimated comparatively with IEQ number. The ADIA method showed very high intraobserver reproducibility compared to theReliable assessment of islet viability, mass, and purity must be met prior to transplanting an islet preparation into patients with type 1 diabetes. The standard method for quantifying human islet preparations is by direct microscopic analysis of dithizone-stained islet samples, but this technique may be susceptible to inter-/intraobserver variability, which may induce false positive/negative islet counts. Here we describe a simple, reliable, automated digital image analysis (ADIA) technique for accurately quantifying islets into total islet number, islet equivalent number (IEQ), and islet purity before islet transplantation. Islets were isolated and purified from n = 42 human pancreata according to the automated method of Ricordi et al. For each preparation, three islet samples were stained with dithizone and expressed as IEQ number. Islets were analyzed manually by microscopy or automatically quantified using Nikon's inverted Eclipse Ti microscope with built-in NIS-Elements Advanced Research (AR) software. The AIDA method significantly enhanced the number of islet preparations eligible for engraftment compared to the standard manual method ( p < 0.001). Comparisons of individual methods showed good correlations between mean values of IEQ number ( r 2 = 0.91) and total islet number ( r 2 = 0.88) and thus increased to r 2 = 0.93 when islet surface area was estimated comparatively with IEQ number. The ADIA method showed very high intraobserver reproducibility compared to the standard manual method ( p < 0.001). However, islet purity was routinely estimated as significantly higher with the manual method versus the ADIA method ( p < 0.001). The ADIA method also detected small islets between 10 and 50 μm in size. Automated digital image analysis utilizing the Nikon Instruments software is an unbiased, simple, and reliable teaching tool to comprehensively assess the individual size of each islet cell preparation prior to transplantation. Implementation of this technology to improve engraftment may help to advance the therapeutic efficacy and accessibility of islet transplantation across centers. … (more)
- Is Part Of:
- Cell transplantation. Volume 24:Issue 1(2015)
- Journal:
- Cell transplantation
- Issue:
- Volume 24:Issue 1(2015)
- Issue Display:
- Volume 24, Issue 1 (2015)
- Year:
- 2015
- Volume:
- 24
- Issue:
- 1
- Issue Sort Value:
- 2015-0024-0001-0000
- Page Start:
- 1
- Page End:
- 9
- Publication Date:
- 2015-01
- Subjects:
- Human islets -- Automated digital image analysis (ADIA) -- Standard manual method -- Islet surface area -- Transplantation centers
Cell transplantation -- Periodicals
Cell Transplantation
Cell transplantation
Electronic journals
Periodicals
Periodicals
571.638 - Journal URLs:
- http://journals.sagepub.com/home/cll ↗
http://www.sagepublications.com/ ↗
http://www.cognizantcommunication.com ↗ - DOI:
- 10.3727/096368913X667493 ↗
- Languages:
- English
- ISSNs:
- 0963-6897
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
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- 7465.xml