• DocumentCode
    3100454
  • Title

    Assessment of median nerve mobility by ultrasound dynamic imaging in carpal tunnel syndrome diagnosis

  • Author

    Tai-Tzung Kuo ; Ming-Ru Lee ; Yin-Yin Liao ; Wei-Ning Lee ; Yen-Wei Hsu ; Jiann-Perng Chen ; Chih-Kuang Yeh

  • Author_Institution
    Dept. of Neurosurg., Hsin-chu Mackay Memorial Hosp., Hsinchu, Taiwan
  • fYear
    2013
  • fDate
    21-25 July 2013
  • Firstpage
    876
  • Lastpage
    879
  • Abstract
    Carpal tunnel syndrome (CTS) is a common entrapment neuropathy. Nerve conduction studies (NCS) have been used as a standard for CTS diagnosis. Complementing NCS, ultrasound imaging provides anatomic information on pathologic changes of the median nerve, such as the reduced median nerve mobility. Motion of median nerve is dependent on mechanical characteristics, and body movements. The purpose of this study was therefore to measure transverse sliding patterns of the median nerve during fingers flexion and extension in ultrasound B-mode images for distinguishing healthy from CTS subjects, and to investigate any correlation between NCS severity and median nerve motion. Transverse ultrasound images were acquired from 19 normal, 15 mild, and 10 severe CTS subjects confirmed by NCS. In two-second acquisition, their fingers were initially in natural position; the median nerve was then moved toward the ulnar side and radius side in fingers flexion and extension, respectively. The displacements of the median nerve were calculated by the multilevel block-matching pyramid algorithm and averaged. All the average displacements at different acquisition times were then accumulated to obtain cumulative displacements, which were curve-fitted by polynomial function. To differentiate the normal from CTS cases, the R-squared, curvature, and amplitude of the fitted curves were computed, to evaluate the goodness, variation, and maximum value of the fit, respectively. Compared to the CTS patients, the normal subjects had higher R-square, curvature, and amplitude estimates. The three parameters were then inputted to a fuzzy c-means algorithm to classify normal cases and CTS ones. The diagnostic efficiency had an accuracy of 93.2%, a specificity of 100%, and a sensitivity of 88%. Further study includes measuring mechanical strain and stress at different neural sites to provide elasticity of the median nerve.
  • Keywords
    biomechanics; biomedical ultrasonics; brain; data acquisition; diseases; elasticity; fuzzy systems; image classification; medical image processing; neurophysiology; polynomials; sensitivity; stress-strain relations; ultrasonic imaging; R-square; anatomic information; body movements; carpal tunnel syndrome diagnosis; common entrapment neuropathy; elasticity; finger extension; finger flexion; fuzzy c-means algorithm; mechanical characteristics; mechanical strain; mechanical stress; median nerve mobility assessment; mild carpal tunnel syndrome; multilevel block-matching pyramid algorithm; nerve conduction; normal carpal tunnel syndrome; pathologic changes; polynomial function; sensitivity; severe carpal tunnel syndrome; transverse sliding patterns; transverse ultrasound images; two-second acquisition; ultrasound B-mode images; ultrasound dynamic imaging; Accuracy; Imaging; Sensitivity; Thumb; Ultrasonic imaging; Wrist; Carpal tunnel syndrome; Median nerve mobility; Ultrasound dynamic imaging;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Ultrasonics Symposium (IUS), 2013 IEEE International
  • Conference_Location
    Prague
  • ISSN
    1948-5719
  • Print_ISBN
    978-1-4673-5684-8
  • Type

    conf

  • DOI
    10.1109/ULTSYM.2013.0225
  • Filename
    6725234