Tim Brunson DCH

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Reliability of sonomyography for pectoralis major thickness measurement.



OBJECTIVE: Muscle thickness is a widely used parameter for quantifying muscle function in ultrasound imaging. However, current measurement techniques generally rely on manual digitization, which is subjective, time consuming, and prone to error. The primary purposes of this study were to develop an automated muscle boundary tracking algorithm to overcome these limitations and to report its intraexaminer reliability on pectoralis major muscle.

METHODS: Real-time B-mode ultrasound images of the pectoralis major muscles were acquired by an integrated data acquisition system. A transducer placement protocol was developed to facilitate better repositioning of an ultrasound transducer. Intraexaminer reliability of the tracking algorithm for static measurements was studied using intraclass correlation coefficient based on the thickness data from 11 healthy subjects recruited from a chiropractic college measured at 3 independent sessions. Standard error of measurement and minimal detectable change were calculated. Feasibility of using the tracking algorithm for dynamic measurements was also evaluated.

RESULTS: All calculated intraclass correlation coefficients were larger than 0.96, indicating excellent reliability of the sonomyographic measurements. Minimal detectable changes were 9.7%, 6.7%, and 6.8% of the muscle thickness at the lateral, central, and medial aspects, respectively. For a 400-frame image stack with 3 pairs of 40 x 40 pixels tracking windows, the tracking took about 80 seconds to complete.

CONCLUSIONS: The tracking algorithm offers precise and reliable measurements of muscle thickness changes in clinical settings with potential to quantify the effects of a wide variety of chiropractic techniques on muscle function.

Koo TK, Wong C, Zheng Y. J Manipulative Physiol Ther. 2010 Jun;33(5):386-94. Foot Levelers Biomechanics Research Laboratory, New York Chiropractic College, Seneca Falls, NY 13148, USA. tkoo@nycc.edu

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