title: Computational Approach to Measuring Myocyte Disarray in Animal Models of Heart Disease.
abstract: In cardiovascular disease research, studies often include measuring cardiac function and performing histological examination of heart tissue. After measuring contractility, hearts from animals such as mice and rats are often frozen or fixed, sliced, and stained to quantify the morphology of various structures such as extracellular matrix proteins, cell nuclei, and F-actin. Traditional scoring methods have largely consisted of assessing sections of images for the presence or absence of myocyte disarray. These approaches require unbiased manual assessment, which can require extra personnel, and are not scalable to the quantity of data that can be generated by modern automated experimental techniques. Here, we describe an automated image analysis approach for unbiased numerical measurement of myocyte disarray. We provide step-by-step instructions for image preparation as well as a basic Matlab script for measurements. © 2017 by John Wiley & Sons, Inc.
authors.affiliation: Biofrontiers Institute, University of Colorado at Boulder, Boulder, Colorado.
authors.forename: William
authors.initials: W
authors.lastname: Wan
authors.affiliation: Biofrontiers Institute, University of Colorado at Boulder, Boulder, Colorado.
authors.forename: Leslie
authors.initials: L
authors.lastname: Leinwand
mesh_terms: D000818:Animals; D001331:Automation / Q000379:methods; D003952:Diagnostic Imaging / Q000379:methods*; D004195:Disease Models, Animal; D006331:Heart Diseases / Q000473:pathology*; D051379:Mice; D032342:Muscle Cells / Q000473:pathology*
keywords: Matlab; image analysis; myocyte disarray