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

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 0.05). 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.