Design and validation of a novel method to measure cross-sectional area of neck muscles included during routine MR brain volume imaging

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Abstract / Description of output

Introduction: Low muscle mass secondary to disease and ageing is an important cause of excess mortality and morbidity. Many studies include a MR brain scan but no peripheral measure of muscle mass. We developed a technique to measure posterior neck muscle cross-sectional area (CSA) on volumetric MR brain scans enabling brain and muscle size to be measured simultaneously. Methods: We performed four studies to develop and test: feasibility, inter-rater reliability, repeatability and external validity. We used T1-weighted MR brain imaging from young and older subjects, obtained on different scanners, and collected mid-thigh MR data. Results: After developing the technique and demonstrating feasibility, we tested it for inter-rater reliability in 40 subjects. Intraclass correlation coefficients (ICC) between raters were 0.99 (95% confidence intervals (CI) 0.98-1.00) for the combined group (trapezius, splenius and semispinalis), 0.92 (CI 0.85-0.96) for obliquus and 0.92 (CI 0.85-0.96) for sternocleidomastoid. The first unrotated principal component explained 72.2% of total neck muscle CSA variance and correlated positively with both right (r = 0.52, p =. 001) and left (r = 0.50, p =. 002) grip strength. The 14 subjects in the repeatability study had had two MR brain scans on three different scanners. The ICC for between scanner variation for total neck muscle CSA was high at 0.94 (CI 0.86-0.98). The ICCs for within scanner variations were also high, with values of 0.95 (CI 0.86-0.98), 0.97 (CI 0.92-0.99) and 0.96 (CI 0.86-0.99) for the three scanners. The external validity study found a correlation coefficient for total thigh CSA and total neck CSA of 0.88. Discussion: We present a feasible, valid and reliable method for measuring neck muscle CSA on T1-weighted MR brain scans. Larger studies are needed to validate and apply our technique with subjects differing in age, ethnicity and geographical location.

Original languageEnglish
Article numbere34444
JournalPLoS ONE
Issue number4
Publication statusPublished - 3 Apr 2012

Keywords / Materials (for Non-textual outputs)

  • Ageing
  • Confidence Intervals
  • Imaging Techniques
  • Magnetic Resonance
  • Muscle Analysis
  • Muscle Components
  • Nueroimaging
  • Reseach Validity


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