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Evaluation of neck muscle size: long-term reliability and comparison of methods
D L Belavý1, T Miokovic, G Armbrecht
1Charité Universitätsmedizin Berlin, Center for Muscle and Bone Research, Hindenburgdamm 30, 12200 Berlin, Germany. Centre for Physical Activity and Nutrition Research, School of Exercise and Nutrition Sciences, Deakin University, 221 Burwood Highway, Burwood, Victoria, 3125, Australia.
Abstract:
Although it is important for prospective studies, the reliability of quantitative measures of cervical muscle size on magnetic resonance imaging is not well established. The aim of the current work was to assess the long-term reliability of measurements of cervical muscle size. In addition, we examined the utility of selecting specific sub-regions of muscles at each vertebral level, averaging between sides of the body, and pooling muscles into larger groups. Axial scans from the base of skull to the third thoracic vertebra were performed in 20 healthy male subjects at baseline and 1.5 years later. We evaluated the semi-spinalis capitis, splenius capitis, spinalis cervicis, longus capitis, longus colli, levator scapulae, sternocleidomastoid, anterior scalenes and middle with posterior scalenes. Bland-Altman analysis showed all measurements to be repeatable between testing-days. Reliability was typically best when entire muscle volume was measured (co-efficients of variation (CVs): 3.3-8.1% depending on muscle). However, when the size of the muscle was assessed at specific vertebral levels, similar measurement precision was achieved (CVs: 2.7-7.6%). A median of 4-6 images were measured at the specific vertebral levels versus 18-37 images for entire muscle volume. This would represent considerable time saving. Based on the findings we also recommend measuring both sides of the body and calculating an average value. Pooling specific muscles into the deep neck flexors (CV: 3.5%) and neck extensors (CV: 2.7%) can serve to reduce variability further. The results of the current study help to establish outcome measures for interventional studies and for sample size estimation.
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