BACKGROUND: Accurate determination of islet purity and mass before transplantation is an essential part of quality control. The standard method is based on manual evaluation of these parameters and thus subjective and prone to errors. Therefore, we developed a computerized approach aimed at evaluating more objectively the number and purity of isolated human islets. METHODS: Islets were isolated and purified from human pancreata according to a standard method. For each preparation, two samples were dithizone stained. One sample was analyzed manually by microscopy, following the standard procedure, and the other was digitally photographed for both digital manual and computerized analyses. Computerized analysis was performed using the MetaMorph and ImageJ softwares to automatically quantify purity and size of islets. Islet equivalent (IEQ) number was calculated using the Ricordi algorithm or considering the individual volume of each islet. Computerized analysis was validated using calibrated red glass microspheres. RESULTS: When digital manual and computerized analyses were compared, mean values of total islet number, IEQ number calculated using the Ricordi algorithm, and purity were similar. Comparisons of individual values showed good correlations (r>or=0.89). By standard manual analysis, total islet number and purity were higher and IEQ number similar compared with digital manual and computerized analyses. IEQ number was 10% lower (P<0.0001) when calculated using individual sphere volumes compared with the Ricordi algorithm. Measurement of red glass microspheres showed identical values comparing standard manual and computerized analyses. CONCLUSIONS: Computer-assisted digital image analysis is an objective and a reliable method for analyzing pancreatic islets before transplantation.
BACKGROUND: Accurate determination of islet purity and mass before transplantation is an essential part of quality control. The standard method is based on manual evaluation of these parameters and thus subjective and prone to errors. Therefore, we developed a computerized approach aimed at evaluating more objectively the number and purity of isolated human islets. METHODS: Islets were isolated and purified from human pancreata according to a standard method. For each preparation, two samples were dithizone stained. One sample was analyzed manually by microscopy, following the standard procedure, and the other was digitally photographed for both digital manual and computerized analyses. Computerized analysis was performed using the MetaMorph and ImageJ softwares to automatically quantify purity and size of islets. Islet equivalent (IEQ) number was calculated using the Ricordi algorithm or considering the individual volume of each islet. Computerized analysis was validated using calibrated red glass microspheres. RESULTS: When digital manual and computerized analyses were compared, mean values of total islet number, IEQ number calculated using the Ricordi algorithm, and purity were similar. Comparisons of individual values showed good correlations (r>or=0.89). By standard manual analysis, total islet number and purity were higher and IEQ number similar compared with digital manual and computerized analyses. IEQ number was 10% lower (P<0.0001) when calculated using individual sphere volumes compared with the Ricordi algorithm. Measurement of red glass microspheres showed identical values comparing standard manual and computerized analyses. CONCLUSIONS: Computer-assisted digital image analysis is an objective and a reliable method for analyzing pancreatic islets before transplantation.
Authors: K Lemaire; M A Ravier; A Schraenen; J W M Creemers; R Van de Plas; M Granvik; L Van Lommel; E Waelkens; F Chimienti; G A Rutter; P Gilon; P A in't Veld; F C Schuit Journal: Proc Natl Acad Sci U S A Date: 2009-08-18 Impact factor: 11.205
Authors: Y Wang; K K Danielson; A Ropski; T Harvat; B Barbaro; D Paushter; M Qi; J Oberholzer Journal: Cell Transplant Date: 2013-01-28 Impact factor: 4.064
Authors: A N Balamurugan; B Naziruddin; A Lockridge; M Tiwari; G Loganathan; M Takita; S Matsumoto; K Papas; M Trieger; H Rainis; T Kin; T W Kay; S Wease; S Messinger; C Ricordi; R Alejandro; J Markmann; J Kerr-Conti; M R Rickels; C Liu; X Zhang; P Witkowski; A Posselt; P Maffi; A Secchi; T Berney; P J O'Connell; B J Hering; F B Barton Journal: Am J Transplant Date: 2014-10-02 Impact factor: 8.086
Authors: Raphael P H Meier; Jörg D Seebach; Philippe Morel; Redouan Mahou; Sophie Borot; Laurianne Giovannoni; Geraldine Parnaud; Elisa Montanari; Domenico Bosco; Christine Wandrey; Thierry Berney; Leo H Bühler; Yannick D Muller Journal: PLoS One Date: 2014-03-13 Impact factor: 3.240