Abstract
Adipose tissue is a highly dynamic endocrine organ that serves as the body's primary energy reservoir through the storage and mobilization of lipids. Adipocyte cellular size has been recognized as an indicator of cellular status; hypertrophic adipocytes are more prone to insulin resistance and the secretion of pro-inflammatory cytokines. Thus, the size and number of lipids is important to consider both in the clinic with a biopsy and when developing disease models and regenerative tissue constructs. Tools available to analyze adipocyte size are finely tuned for hematoxylin-eosin images and tend to be challenged by confocal derived z-stack images which contain intensity gradients. Therefore, ImageJ manual analysis is the commonly utilized tool to measure these images. With there being heterogeneity in different researcher's analytical approach when conducted manually, the MATLAB script, PixCell, was developed to reduce the subjectivity and time involved in adipocyte size analysis. Given its stepwise thresholding and masking steps, PixCell retains on average a >80% accuracy when tested on excised human adipose tissue, adipocyte-laden collagen gels, and lipoaspirate seeded silk scaffolds. PixCell is able to consistently detect and measure lipids within regions of varying pixel intensities. This makes PixCell an appealing tool for use in both the clinical and pre-clinical setting, while greatly enhancing and streamlining the user experience of analyzing lipid sizes.