A Method of Radial Nerve Length Measurement Based on Cadaveric Investigation

Published:September 06, 2016DOI:



      To determine the most reliable method to measure the length of the radial nerve during a nerve conduction study (NCS).


      Cadaveric investigation.


      A practical anatomy research laboratory in a university.


      Fresh cadavers (N=10), with 1 cadaver for study design and 9 for data.


      Design of measurement methods using cadaver dissection and comparison of the measured values to the true length in 18 arms of 9 cadavers.

      Main Outcome Measures

      Four points (A, B, C, D) were determined: (A) proximal stimulation point in NCS; (B) point at the elbow crease; (C) point in the midforearm; and (D) distal stimulation point 5cm above the extensor indicis. The true length of the radial nerve between the stimulus points (points A and D) in NCS was compared with the measured values by summation of the straight line segments between those points with various combinations. The difference in root mean square error (RMSE) of the distance measured by each method compared with the true length was calculated to determine the best measurement method.


      The closest distance to the true length (28.7±2.8cm) in the cadaveric investigation was obtained using the summation of straight line segments between points A, B, and D (A-B-D, RMSE=.72cm), followed by the A-B-C-D distance (RMSE=.87cm) and the A-D distance (RMSE=1.38cm) methods, in sequence. The former 2 distance measurements were relatively closer to the true length than the latter measurement method.


      Multiple segmentation measurement methods reflected the course of the radial nerve better than a single linear measurement method. We suggest that the distance measured using a stopover point near the lateral epicondyle between 2 stimulus points (A-B-D distance) is closer to the true length of the nerve.


      List of abbreviations:

      EI (extensor indicis), NCS (nerve conduction study), NCV (nerve conduction velocity), RMSE (root mean square error)
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