LBSUN129 Adipose Tissue Analysis Toolkit (at-at): An Imagej Plugin For Automated Analysis Of Adipocyte Number, Size, And Pericellular Fibrosis In Histological Sections

Abstract Obesity-induced pathological expansion of white adipose tissue (WAT) involves adipocyte hypertrophy that occurs in tandem with the development of pericellular fibrosis. Other pathophysiological states, such as cancer and HIV, are also associated with fibrotic transformation of WAT depots. Aging, obesity, inactivity, and estrogen deficiency are also associated with an increase in bone marrow adiposity. Disease-associated changes in WAT morphology are typically assessed using histochemical analysis of WAT sections. However, manual analysis of large histological sections of WAT or bone marrow adipose tissue can be very time-consuming, while digital tools for the analysis of adipocyte size and pericellular fibrosis are limited. In response to this need, we have developed the Adipose Tissue Analysis Toolkit (AT-AT), a plugin for the open-source image analysis software ImageJ. AT-AT employs both local and global differentials in pixel intensity to threshold background apart from adipocyte-free tissue without user input. The AT-AT accurately captures adipocyte perimeter, maximum diameter, minimum diameter, and density per square millimeter of tissue in histological sections stained with common histological dyes, and performs automatic analysis of adipocyte cross-sectional area as well as pericellular fibrosis. AT-AT enables fully-automated analysis of batches of histological images using either default or user-defined adipocyte detection parameters including minimum circularity as well as minimum and maximum cross-sectional area. Likewise, users may set parameters for the thresholding algorithms, including the number of localized thresholds to be calculated in each image. AT-AT's thresholding techniques confer uniquely high resistances to both false-negative and false-positive detection events by comparison to other open-source adipocyte analysis software. They also enable superior measurement of adipocyte morphology, especially in the case of low-magnification images. AT-AT features several quality-of-life features, including automatic summarization of batch-collected data, the implementation of its thresholding algorithms as independent ImageJ commands, and an optional histogram builder. AT-AT can enhance the rigor and reproducibility of adipose tissue research. AT-AT will become available as a plugin for ImageJ in the fall of 2022. Presentation: Sunday, June 12, 2022 12:30 p.m. - 2:30 p.m.