Literature DB >> 12766981

Quantitative skeletal muscle ultrasonography in children with suspected neuromuscular disease.

S Pillen1, R R Scholten, M J Zwarts, A Verrips.   

Abstract

We determined prospectively the diagnostic value of quantitative ultrasonography in detecting neuromuscular disorders in children. Ultrasonographic scans of four muscles were made in 36 children with symptoms or signs suggestive of neuromuscular disease, such as muscle weakness and hypotonia. The muscle thickness, ratio of muscle thickness to subcutaneous fat thickness, and echo intensity were determined in each muscle. The echo intensity was measured using computer-assisted gray-scale analysis. Thirteen of the 36 patients had a neuromuscular disorder (6 a myopathy and 7 a neuropathy). Differentiation between neuromuscular diseases and nonneuromuscular diseases could be made on the basis of echo intensities with a sensitivity of 92%, a specificity of 90%, a positive predictive value of 86%, and a negative predictive value of 95%. We conclude that computer-assisted quantitative analysis of muscle echo intensity is a reliable method to discriminate between neuromuscular and nonneuromuscular diseases in children.

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Year:  2003        PMID: 12766981     DOI: 10.1002/mus.10385

Source DB:  PubMed          Journal:  Muscle Nerve        ISSN: 0148-639X            Impact factor:   3.217


  15 in total

1.  Ultrasound assessment of the diaphragm: Preliminary study of a canine model of X-linked myotubular myopathy.

Authors:  Aarti Sarwal; Michael S Cartwright; Francis O Walker; Erin Mitchell; Anna Buj-Bello; Alan H Beggs; Martin K Childers
Journal:  Muscle Nerve       Date:  2014-08-30       Impact factor: 3.217

2.  Validation of grayscale-based quantitative ultrasound in manual wheelchair users: relationship to established clinical measures of shoulder pathology.

Authors:  Jennifer L Collinger; Bradley Fullerton; Bradley G Impink; Alicia M Koontz; Michael L Boninger
Journal:  Am J Phys Med Rehabil       Date:  2010-05       Impact factor: 2.159

3.  Machine learning algorithms to classify spinal muscular atrophy subtypes.

Authors:  Tuhin Srivastava; Basil T Darras; Jim S Wu; Seward B Rutkove
Journal:  Neurology       Date:  2012-07-11       Impact factor: 9.910

4.  Assessing spinal muscular atrophy with quantitative ultrasound.

Authors:  Jim S Wu; Basil T Darras; Seward B Rutkove
Journal:  Neurology       Date:  2010-08-10       Impact factor: 9.910

5.  Reliability of quantitative ultrasound measures of the biceps and supraspinatus tendons.

Authors:  Jennifer L Collinger; Dany Gagnon; Jon Jacobson; Bradley G Impink; Michael L Boninger
Journal:  Acad Radiol       Date:  2009-07-10       Impact factor: 3.173

6.  A comparison of ultrasound echo intensity to magnetic resonance imaging as a metric for tongue fat evaluation.

Authors:  Jason L Yu; Andrew Wiemken; Susan M Schultz; Brendan T Keenan; Chandra M Sehgal; Richard J Schwab
Journal:  Sleep       Date:  2022-02-14       Impact factor: 5.849

7.  Shoulder muscle changes in patients with type 2 diabetes mellitus who have a painful shoulder: a quantitative muscle ultrasound study.

Authors:  Login Ahmed S Alabdali; Bjorn Winkens; Geert-Jan Dinant; Nens van Alfen; Ramon P G Ottenheijm
Journal:  BMC Musculoskelet Disord       Date:  2022-07-14       Impact factor: 2.562

8.  The bigger, the stronger? Insights from muscle architecture and nervous characteristics in obese adolescent girls.

Authors:  S Garcia-Vicencio; E Coudeyre; V Kluka; C Cardenoux; A-G Jegu; A-V Fourot; S Ratel; V Martin
Journal:  Int J Obes (Lond)       Date:  2015-08-19       Impact factor: 5.095

9.  Association Between Muscle Strength and Modeling Estimates of Muscle Tissue Heterogeneity in Young and Old Adults.

Authors:  Michael O Harris-Love; Tomas I Gonzales; Qi Wei; Catheeja Ismail; Johannah Zabal; Paula Woletz; Loretta DiPietro; Marc R Blackman
Journal:  J Ultrasound Med       Date:  2018-12-12       Impact factor: 2.153

10.  Spinal Muscular Atrophy Type 3 Showing a Specific Pattern of Selective Vulnerability on Muscle Ultrasound.

Authors:  Ryutaro Nakamura; Akihiro Kitamura; Takahito Tsukamoto; Yuhei Otowa; Naoki Okamoto; Nobuhiro Ogawa; Isamu Yamakawa; Hyoh Kim; Mitsuru Sanada; Makoto Urushitani
Journal:  Intern Med       Date:  2021-01-15       Impact factor: 1.271

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