A fast, automatic and quantitative image processing tool for assessing skeletal muscle health

Wednesday, October 26, 2011 — Poster Session III
10:00 a.m. – Noon	Natcher Conference Center	NIAMS	IMAG-22

Authors

• W Liu
• N Raben
• K Zaal
• T Ploug
• E Ralston

Abstract

All muscle pathologies create disorder in the normally periodic myofibrils, either by removal of contractile proteins or by inclusion of non-contractile structures such as autophagic debris. Several light imaging techniques such as immunofluorescence, autofluorescence, and Second Harmonic Generation (SHG) imaging provide an immediate visual assessment of muscle damage. However, quantitating the damage is not so easy. Objective and unbiased quantification of muscle morphology is necessary to assess muscle health, compare different biopsies, and evaluate the effectiveness of treatments and the evolution of disease. A fast, sensitive, automatic imaging analysis tool was developed to detect major and subtle morphologic changes by combining Texture features and Fourier Transform (FT) techniques. SHG images of muscle fibers were collected to visualize sarcomeres, the basic repeat unit of muscle. Texture features were then calculated by using a Haralick gray-level co-occurrence matrix in MatLab. Two Scores were retrieved by using Fourier transform and curve fitting method. These ratings are very sensitive to both subtle morphological change and major interruptions in muscle structures, thus it could be a powerful and unbiased tool to evaluate chronic disease development or effectiveness of muscle treatments.

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