For CD8 quantification, pancreas sections were stained, and an average of 10–15 images (surface area of 1.215 mm2) from each tissue section were acquired using a Nikon digital DXM1200C camera and Nikon ACT-1C Camera Controller Software unless otherwise indicated. To determine the number of CD8 T cells infiltrating the pancreas, image analysis was performed by using a custom macro developed in MATLAB (The Mathworks, Inc., Natick, MA) and ImageJ (National Institutes of Health). Briefly, islet regions were identified as contiguous areas of insulin or glucagon staining at or above a threshold intensity value. The periphery of the islet was defined using a dilation tool and expanding its perimeter by 100 × 100 pixels (15–20 µm). CD8+ cells were identified as areas of CD8 staining using optimized and identical threshold values for intensity and size for all the images. A comparison between manual counts and software-assisted counts was performed in 15 images in order to validate the macro used to quantify CD8+ cells. In addition, all software-processed images were manually checked to identify any possible errors. For CD4 and CD11c counts, five images from each donor were analyzed manually. Average infiltration rates (cells/mm2) were calculated for each donor and used as individual and independent samples in the subsequent statistical analyses.β- and α-cell areas were determined as the percentage of the total area of the image that was positive for insulin or glucagon staining using a custom macro developed for ImageJ (National Institutes of Health).