Sensitive Ultrasonic Delineation of Steroid Treatment in Living Dystrophic Mice with Energy-Based and Entropy-Based Radio Frequency Signal Processing

Kirk D. Wallace, Jon N. Marsh, Steven L. Baldwin, Anne M. Connolly, Richard Keeling, Gregory M. Lanza, Samuel A. Wickline, and Michael S. Hughes

ABSTRACT Duchenne muscular dystrophy is a severe wasting disease, involving replacement of necrotic muscle tissue by fibrous material and fatty infiltrates. One primary animal model of this human disease is the X chromosome-linked mdx strain of mice. The goals of the present work were to validate and quantify the capability of both energy and entropy metrics of radio-frequency ultrasonic backscatter to differentiate among normal, dystrophic, and steroid-treated skeletal muscle in the mdx model. Thirteen 12-month-old mice were blocked into three groups: 4 treated mdx-dystrophic that received daily subcutaneous steroid (prednisolone) treatment for 14 days, 4 positive-control mdx-dystrophic that received saline injections for 14 days, and 5 negative-control animals. Biceps muscle of each animal was imaged in vivo using a 40-MHz center frequency transducer in conjunction with a Vevo-660 ultrasound system. Radio-frequency data were acquired (1 GHz, 8 bits) corresponding to a sequence of transverse images, advancing the transducer from ``shoulder'' to ``elbow'' in 100-micron steps. Data were processed to generate both ``integrated backscatter'' (log energy), and ``entropy'' (information theoretic receiver, Hf) representations. Analyses of the integrated-backscatter values delineated both treated- and untreated-mdx biceps from normal controls (p < 0.01). Complementary analyses of the entropy images differentiated the steroid-treated and positive-control mdx groups (p < 0.01). To our knowledge, this study represents the first reported use of quantitative ultrasonic characterization of skeletal muscle in mdx mice. Successful differentiation among dystrophic, steroid-treated, and normal tissues suggests the potential for local noninvasive monitoring of disease severity and therapeutic effects.

Digital Object Identifier 10.1109/TUFFC.2007.533

© 2007, by The Institute of Electrical and Electronics Engineers, Inc. All rights reserved.

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