Ultrasound in Medicine and Biology
Volume 32, Issue 9 , Pages 1315-1321 , September 2006

Skeletal muscle ultrasonography: Visual versus quantitative evaluation

  • Sigrid Pillen

      Affiliations

    • Department of Clinical Neurophysiology, Institute of Neurology, Nijmegen
    • Department of Paediatrics, Radboud University Nijmegen Medical Centre, Nijmegen
    • Corresponding Author InformationAddress correspondence to: Sigrid Pillen, Department of Clinical Neurophysiology, Neuromuscular Centre Nijmegen, Radboud University Nijmegen Medical Centre, Reinier Postlaan 4, PO Box 9101, 6500 HB Nijmegen, The Netherlands.
    • ,
  • Mieke van Keimpema

      Affiliations

    • Department of Clinical Neurophysiology, Institute of Neurology, Nijmegen
    • ,
  • Rutger A.J. Nievelstein

      Affiliations

    • Department of Radiology, Wilhelmina Children’s Hospital, University Medical Centre Utrecht, Utrecht
    • ,
  • Aad Verrips

      Affiliations

    • Department of Child Neurology, Canisius Wilhelmina Hospital, Nijmegen, The Netherlands
    • ,
  • Wilma van Kruijsbergen-Raijmann

      Affiliations

    • Department of Clinical Neurophysiology, Institute of Neurology, Nijmegen
    • ,
  • Machiel J. Zwarts

      Affiliations

    • Department of Clinical Neurophysiology, Institute of Neurology, Nijmegen

Received 29 December 2005 ,Revised 12 May 2006 ,Accepted 22 May 2006.

References 

  1. Aydinli N , Baslo B , Caliskan M , Ertas M , Ozmen M . Muscle ultrasonography and electromyography correlation for evaluation of floppy infants . Brain Dev . 2003;25:22–24
  2. Bargfrede M , Schwennicke A , Tumani H , Reimers CD . Quantitative ultrasonography in focal neuropathies as compared to clinical and EMG findings . Eur J Ultrasound . 1999;10:21–29
  3. Chen CM , Chou YH , Han KC , et al.   Breast lesions on sonograms: computer-aided diagnosis with nearly setting-independent features and artificial neural networks . Radiology . 2003;226:504–514
  4. Doi K . Current status and future potential of computer-aided diagnosis in medical imaging . Br J Radiol . 2005;78(Spec No 1):S3–S19
  5. Feinstein AR . Clinical epidemiology; the architecture of clinical research . Philadelphia: W.B. Sauders Company; 1985;
  6. Fischer AQ , Carpenter DW , Hartlage PL , Carroll JE , Stephens S . Muscle imaging in neuromuscular disease using computerized real-time sonography . Muscle Nerve . 1988;11:270–275
  7. Fleiss J . Statistical methods for rates and proportions . New York: Wiley; 1981;
  8. Heckmatt JZ , Dubowitz V , Leeman S . Detection of pathological change in dystrophic muscle with B-scan ultrasound imaging . Lancet . 1980;1:1389–1390
  9. Heckmatt JZ , Leeman S , Dubowitz V . Ultrasound imaging in the diagnosis of muscle disease . J Pediatr . 1982;101:656–660
  10. Heckmatt JZ , Pier N , Dubowitz V . Real-time ultrasound imaging of muscles . Muscle Nerve . 1988;11:56–65
  11. Heckmatt J , Rodillo E , Doherty M , Willson K , Leeman S . Quantitative sonography of muscle . J Child Neurol . 1989;4(Suppl):S101–S106
  12. Kapeller P , Barber R , Vermeulen RJ , et al.   Visual rating of age-related white matter changes on magnetic resonance imaging: scale comparison, interrater agreement, and correlations with quantitative measurements . Stroke . 2003;34:441–445
  13. Krupinski EA . Computer-aided detection in clinical environment: benefits and challenges for radiologists . Radiology . 2004;231:7–9
  14. Lamminen A , Jaaskelainen J , Rapola J , Suramo I . High-frequency ultrasonography of skeletal muscle in children with neuromuscular disease . J Ultrasound Med . 1988;7:505–509
  15. Landis JR , Koch GG . The measurement of observer agreement for categorical data . Biometrics . 1977;33:159–174
  16. Loch T , Leuschner I , Genberg C , et al.   Artificial neural network analysis (ANNA) of prostatic transrectal ultrasound . Prostate . 1999;39:198–204
  17. Maurits NM , Bollen AE , Windhausen A , De Jager AE , Van Der Hoeven JH . Muscle ultrasound analysis: normal values and differentiation between myopathies and neuropathies . Ultrasound Med Biol . 2003;29:215–225
  18. Maurits NM , Beenakker EA , van Schaik DE , et al.   Muscle ultrasound in children: normal values and application to neuromuscular disorders . Ultrasound Med Biol . 2004;30:1017–1027
  19. Mello-Thoms C , Dunn SM , Nodine CF , Kundel HL . An analysis of perceptual errors in reading mammograms using quasi-local spatial frequency spectra . J Digit Imaging . 2001;14:117–123
  20. Nodine CF , Kundel HL , Mello-Thoms C , et al.   How experience and training influence mammography expertise . Acad Radiol . 1999;6:575–585
  21. Pillen S , Scholten RR , Zwarts MJ , Verrips A . Quantitative skeletal muscle ultrasonography in children with suspected neuromuscular disease . Muscle Nerve . 2003;27:699–705
  22. Pohle R , Fischer D , von Rohden L . Computer-supported tissue characterization in musculoskeletal ultrasonography.[in German] . Ultraschall Med . 2000;21:245–252
  23. Reimers K , Reimers CD , Wagner S , Paetzke I , Pongratz DE . Skeletal muscle sonography: a correlative study of echogenicity and morphology . J Ultrasound Med . 1993;12:73–77
  24. Reimers CD , Fleckenstein JL , Witt TN , Muller-Felber W , Pongratz DE . Muscular ultrasound in idiopathic inflammatory myopathies of adults . J Neurol Sci . 1993;116:82–92
  25. Scholten RR , Pillen S , Verrips A , Zwarts MJ . Quantitative ultrasonography of skeletal muscles in children: normal values . Muscle Nerve . 2003;27:693–698
  26. Zuberi SM , Matta N , Nawaz S , et al.   Muscle ultrasound in the assessment of suspected neuromuscular disease in childhood . Neuromuscul Disord . 1999;9:203–207

PII: S0301-5629(06)01640-1

doi: 10.1016/j.ultrasmedbio.2006.05.028

Ultrasound in Medicine and Biology
Volume 32, Issue 9 , Pages 1315-1321 , September 2006

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