{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,2]],"date-time":"2026-11-02T16:30:43Z","timestamp":1793637043240,"version":"4.5.1"},"reference-count":47,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2017,7,19]],"date-time":"2017-07-19T00:00:00Z","timestamp":1500422400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J cachexia sarcopenia muscle"],"published-print":{"date-parts":[[2017,10]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Ultrasound is a non\u2010invasive and readily available tool that can be prospectively applied at the bedside to assess muscle mass in clinical settings. The four\u2010site protocol, which images two anatomical sites on each quadriceps, may be a viable bedside method, but its ability to predict musculature has not been compared against whole\u2010body reference methods. Our primary objectives were to (i) compare the four\u2010site protocol's ability to predict appendicular lean tissue mass from dual\u2010energy X\u2010ray absorptiometry; (ii) optimize the predictability of the four\u2010site protocol with additional anatomical muscle thicknesses and easily obtained covariates; and (iii) assess the ability of the optimized protocol to identify individuals with low lean tissue mass.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>This observational cross\u2010sectional study recruited 96 university and community dwelling adults. Participants underwent ultrasound scans for assessment of muscle thickness and whole\u2010body dual\u2010energy X\u2010ray absorptiometry scans for assessment of appendicular lean tissue. Ultrasound protocols included (i) the nine\u2010site protocol, which images nine anterior and posterior muscle groups in supine and prone positions, and (ii) the four\u2010site protocol, which images two anterior sites on each quadriceps muscle group in a supine position.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The four\u2010site protocol was strongly associated (<jats:italic>R<\/jats:italic><jats:sup>2<\/jats:sup>\u00a0=\u00a00.72) with appendicular lean tissue mass, but Bland\u2013Altman analysis displayed wide limits of agreement (\u22125.67, 5.67\u00a0kg). Incorporating the anterior upper arm muscle thickness, and covariates age and sex, alongside the four\u2010site protocol, improved the association (<jats:italic>R<\/jats:italic><jats:sup>2<\/jats:sup>\u00a0=\u00a00.91) with appendicular lean tissue and displayed narrower limits of agreement (\u22123.18, 3.18\u00a0kg). The optimized protocol demonstrated a strong ability to identify low lean tissue mass (area under the curve\u00a0=\u00a00.89).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>The four\u2010site protocol can be improved with the addition of the anterior upper arm muscle thickness, sex, and age when predicting appendicular lean tissue mass. This optimized protocol can accurately identify low lean tissue mass, while still being easily applied at the bedside.<\/jats:p><\/jats:sec>","DOI":"10.1002\/jcsm.12213","type":"journal-article","created":{"date-parts":[[2017,7,19]],"date-time":"2017-07-19T12:01:25Z","timestamp":1500465685000},"page":"713-726","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":93,"title":["Development of a bedside viable ultrasound protocol to quantify appendicular lean tissue mass"],"prefix":"10.1002","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3614-962X","authenticated-orcid":false,"given":"Michael T.","family":"Paris","sequence":"first","affiliation":[{"name":"Department of Kinesiology University of Waterloo  Waterloo Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Benoit","family":"Lafleur","sequence":"additional","affiliation":[{"name":"Department of Kinesiology University of Waterloo  Waterloo 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