Improved assessment of isolated islet tissue volume using digital image analysis

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

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.

A replacement for islet equivalents with improved reliability and validity

Islet equivalent (IE), the standard estimate of isolated islet volume, is an essential measure to determine the amount of transplanted islet tissue in the clinic and is used in research laboratories to normalize results, yet it is based on the false assumption that all islets are spherical. Here, we developed and tested a new easy-to-use method to quantify islet volume with greater accuracy. Isolated rat islets were dissociated into single cells, and the total cell number per islet was determined by using computer-assisted cytometry. Based on the cell number per islet, we created a regression model to convert islet diameter to cell number with a high R2 value (0.8) and good validity and reliability with the same model applicable to young and old rats and males or females. Conventional IE measurements overestimated the tissue volume of islets. To compare results obtained using IE or our new method, we compared Glut2 protein levels determined by Western Blot and proinsulin content via ELISA between small (diameter≤100 μm) and large (diameter≥200 μm) islets. When normalized by IE, large islets showed significantly lower Glut2 level and proinsulin content. However, when normalized by cell number, large and small islets had no difference in Glut2 levels, but large islets contained more proinsulin. In conclusion, normalizing islet volume by IE overestimated the tissue volume, which may lead to erroneous results. Normalizing by cell number is a more accurate method to quantify tissue amounts used in islet transplantation and research.

Enumeration of islets by nuclei counting and light microscopic analysis

Islet enumeration in impure preparations by conventional dithizone staining and visual counting is inaccurate and operator dependent. We examined nuclei counting for measuring the total number of cells in islet preparations, and we combined it with morphological analysis by light microscopy (LM) for estimating the volume fraction of islets in impure preparations. Cells and islets were disrupted with lysis solution and shear, and accuracy of counting successively diluted nuclei suspensions was verified with (1) visual counting in a hemocytometer after staining with crystal violet, and automatic counting by (2) aperture electrical resistance measurement and (3) flow cytometer measurement after staining with 7-aminoactinomycin-D. DNA content averaged 6.5 and 6.9 pg of DNA per cell for rat and human islets, respectively, in agreement with literature estimates. With pure rat islet preparations, precision improved with increasing counts, and samples with about ≥160 islets provided a coefficient of variation of about 6%. Aliquots of human islet preparations were processed for LM analysis by stereological point counting. Total nuclei counts and islet volume fraction from LM analysis were combined to obtain the number of islet equivalents (IEs). Total number of IE by the standard method of dithizone staining/manual counting was overestimated by about 90% compared with LM/nuclei counting for 12 freshly isolated human islet research preparations. Nuclei counting combined with islet volume fraction measurements from LM is a novel method for achieving accurate islet enumeration.

Validation of methodologies for quantifying isolated human islets: an Islet Cell Resources study

BACKGROUND

Quantification of islet mass is a crucial criterion for defining the quality of the islet product ensuring a potent islet transplant when used as a therapeutic intervention for select patients with type I diabetes.

METHODS

This multi-center study involved all eight member institutions of the National Institutes of Health-supported Islet Cell Resources Consortium. The study was designed to validate the standard counting procedure for quantifying isolated, dithizone-stained human islets as a reliable methodology by ascertaining the accuracy, repeatability (intra-observer variability), and intermediate precision (inter-observer variability). The secondary aim of the study was to evaluate a new software-assisted digital image analysis method as a supplement for islet quantification.

RESULTS

The study demonstrated the accuracy, repeatability and intermediate precision of the standard counting procedure for isolated human islets. This study also demonstrated that software-assisted digital image analysis as a supplemental method for islet quantification was more accurate and consistent than the standard manual counting method.

CONCLUSIONS

Standard counting procedures for enumerating isolated stained human islets is a valid methodology, but computer-assisted digital image analysis assessment of islet mass has the added benefit of providing a permanent record of the isolated islet product being evaluated that improves quality assurance operations of current good manufacturing practice.

How to use image analysis for islet counting

AIM

Assessment of islet mass before islet transplantation requires a reliable technique to enable exact analysis of islet volume. This study aimed to test the applicability of digital image analysis (DIA) for evaluation of samples of purified and non-purified islets.

METHODS

Pancreatic islets were isolated from 10 Lewis rats. Samples of purified (n = 10) and non-purified islets (n = 30) were counted conventionally and by using a computerized method. The equipment for the computerized counting consisted of a digital camera installed on a stereomicroscope and connected to a personal computer. Images of 2272x1704 pixels were processed using a previously described non-commercial program originally developed for this purpose. Islets were converted to equivalents using globe and ellipsoid models. The insulin content of purified islets was assessed using radioimmunoassay and was correlated to the absolute and standardized islet number.

RESULTS

Mean absolute numbers of purified islets +/- SD were 908 +/- 130 and 1049 +/- 230 (manually and DIA respectively). Mean insulin content +/- SD obtained from purified islets was 161 +/- 45 mU. The mean equivalents of purified islets (1589 +/- 555 for globe and 1219 +/- 452 for ellipsoid) significantly correlated with insulin content. However, this correlation was not significant when absolute islet numbers were used, counted using either method. There was no significant difference in absolute non-purified islet numbers assessed by manual and computerized methods (average +/- SD in 50 microl samples; 12.6 +/- 4.1 and 13.3 +/- 5.3 respectively; p = 0.22). The manual method showed a significantly higher yield of islet equivalents (IE; p < 0.001 for both globe and ellipsoid).

CONCLUSION

The computer-based system for islet counting correlated better to insulin content than conventional islet estimation and prevented overestimation. Reproducibility and ease of assessment make it potentially applicable to clinical islet transplantation.

Comparison of analytical methods for quantitation of isolated porcine hepatocyte yields

As cell-based therapies receive approval for clinical evaluation and use, the development of reliable methods to quantify cell number and control the dose of therapy delivered is becoming increasingly important. An example is the determination of the number and volume of primary porcine hepatocytes used in an extracorporeal treatment for patients with liver disease. Conventional cell counting using optical microscopy was compared against two alternate methods to quantify isolated porcine hepatocytes: (1) automated cell counting using a commercially available particle characterization instrument, and (2) quantitation by cell mass. Methods were compared based on accuracy, precision, specificity, linear range, and ruggedness. The automated method delivered substantially improved accuracy, precision, and ruggedness when compared to the conventional optical method. It also provided valuable information about the size distribution of cell preparations, which often contained clumps of cells, and showed that processing steps such as cryopreservation can alter the size characteristics of a cell population. The automated method was also faster, and was well suited to use in a commercial manufacturing process. The mass-based method was simple and inexpensive, but suffered from nonlinearity at low cell concentrations. Automated cell quantitation using a commercially available particle characterization instrument proved to be the preferred method for obtaining accurate and consistent porcine hepatocyte counts in a timely manner.