Color subtractive-computer-assisted image analysis for quantification of cutaneous nerves in a diabetic mouse model

Immunohistochemistry (IHC) is a valuable tool for labeling structures in tissue samples. Quantification of immunolabeled structures using traditional approaches has proved to be difficult. Manual counts of IHC-stained structures are inherently biased, require multiple observers, and generate qualitative data. Stereological methods provide accurate quantification but are complex and labor-intensive when staining must be compared among large numbers of samples. In an effort to quickly, objectively, and reproducibly quantify cutaneous innervation in a large number of counterstained tissue sections, we developed a color subtractive-computer-assisted image analysis (CS-CAIA) system. To develop and test the CS-CAIA method, tissue sections of diabetic (db/db) mouse skin and their wild-type (db/-) littermates were stained by IHC for the neural marker PGP 9.5. The brown-red PGP 9.5 peroxidase stain was colorimetrically isolated through a scripted process of color background removal. The remaining stain was thresholded and binarized for computer determination of nerve profile counts (number of stained regions), area fraction (total area of nerve profiles per unit area of tissue), and area density (total number of nerve profiles per unit area of tissue). Using CS-CAIA, epidermal nerve profile counts, area fraction, and area density were significantly lower in db/db compared to db/- mice.