Siddhartha Sikdar1, Guoqing Diao2, Diego Turo3, Christopher J Stanley4, Abhinav Sharma4, Amy Chambliss5, Loretta Laughrey6, April Aralar1, Diane L Damiano4. 1. Department of Bioengineering, George Mason University, Fairfax, Virginia, USA. 2. Department of Statistics, George Mason University, Fairfax, Virginia, USA. 3. Department of Mechanical Engineering, Catholic University of America, Washington, DC, USA. 4. Functional and Applied Biomechanics, National Institutes of Health, Bethesda, Maryland USA. 5. George Washington University School of Medicine, Washington, DC, USA. 6. Department of Physics, George Mason University, Fairfax, Virginia, USA.
Abstract
OBJECTIVES: To investigate whether quantitative ultrasound (US) imaging, based on the envelope statistics of the backscattered US signal, can describe muscle properties in typically developing children and those with cerebral palsy (CP). METHODS: Radiofrequency US data were acquired from the rectus femoris muscle of children with CP (n = 22) and an age-matched cohort without CP (n = 14) at rest and during maximal voluntary isometric contraction. A mixture of gamma distributions was used to model the histogram of the echo intensities within a region of interest in the muscle. RESULTS: Muscle in CP had a heterogeneous echo texture that was significantly different from that in healthy controls (P < .001), with larger deviations from Rayleigh scattering. A mixture of 2 gamma distributions showed an excellent fit to the US intensity, and the shape and rate parameters were significantly different between CP and control groups (P < .05). The rate parameters for both the single gamma distribution and mixture of gamma distributions were significantly higher for contracted muscles compared to resting muscles, but there was no significant interaction between these factors (CP and muscle contraction) for a mixed-model analysis of variance. CONCLUSIONS: Ultrasound tissue characterization indicates a more disorganized architecture and increased echogenicity in muscles in CP, consistent with previously documented increases in fibrous infiltration and connective tissue changes in this population. Our results indicate that quantitative US can be used to objectively differentiate muscle architecture and tissue properties. This article has been contributed to by US Government employees and their work is in the public domain in the USA. Published 2018 by the American Institute of Ultrasound in Medicine.
OBJECTIVES: To investigate whether quantitative ultrasound (US) imaging, based on the envelope statistics of the backscattered US signal, can describe muscle properties in typically developing children and those with cerebral palsy (CP). METHODS: Radiofrequency US data were acquired from the rectus femoris muscle of children with CP (n = 22) and an age-matched cohort without CP (n = 14) at rest and during maximal voluntary isometric contraction. A mixture of gamma distributions was used to model the histogram of the echo intensities within a region of interest in the muscle. RESULTS: Muscle in CP had a heterogeneous echo texture that was significantly different from that in healthy controls (P < .001), with larger deviations from Rayleigh scattering. A mixture of 2 gamma distributions showed an excellent fit to the US intensity, and the shape and rate parameters were significantly different between CP and control groups (P < .05). The rate parameters for both the single gamma distribution and mixture of gamma distributions were significantly higher for contracted muscles compared to resting muscles, but there was no significant interaction between these factors (CP and muscle contraction) for a mixed-model analysis of variance. CONCLUSIONS: Ultrasound tissue characterization indicates a more disorganized architecture and increased echogenicity in muscles in CP, consistent with previously documented increases in fibrous infiltration and connective tissue changes in this population. Our results indicate that quantitative US can be used to objectively differentiate muscle architecture and tissue properties. This article has been contributed to by US Government employees and their work is in the public domain in the USA. Published 2018 by the American Institute of Ultrasound in Medicine.
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