{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T01:16:28Z","timestamp":1769649388836,"version":"3.49.0"},"reference-count":38,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T00:00:00Z","timestamp":1767657600000},"content-version":"vor","delay-in-days":5,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Clin Physio Funct Imaging"],"published-print":{"date-parts":[[2026,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Skeletal muscle is a critical organ influencing prognosis and overall health; however, the direct measurements of muscle mass are not easily attainable. This study aimed to estimate whole\u2010body skeletal muscle volume (WBM) using pectoralis muscle area (PMA) derived from a single chest\u2010CT slice and basic anthropometric data in a Korean population.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We analyzed PET\u2010CT data from 201 adults (101 women, 100 men). WBM was segmented using deep learning\u2013based software. The PMA was delineated and was divided into pectoralis major and minor. Sex\u2010specific LASSO regression models were developed: Model 1 included total PMA, Model 2A pectoralis major, Model 2B pectoralis minor, and Model 2C both muscles as separate predictors while Model 3 was based on L3 muscle area for comparison. All models additionally included age, height, weight, and waist circumference.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>In females and in males, R\u00b2 values were 0.76 and 0.75 (Model 1), 0.77 and 0.76 (Model 2C), and 0.84 and 0.81 (Model 3), respectively. Bland\u2010Altman bias were 0.5% (95% CI: \u221213.6%, 14.7%), 1.1% (95% CI: \u221220.4%, 22.6%) (Model 1), 0.5% (95% CI: \u221213.7%, 14.7%) 1.0% (95% CI: \u221220.1%, 22.2%) (Model 2C), 0.4% (95% CI: \u221212.2%, 13.0%) and 1.0% (95% CI: \u221218.2, 20.3) (Model 3), respectively.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>WBM can be reliably estimated using PMA measured in a single chest\u2010CT slice and basic body measurements (age, height, weight, and waist circumference). This method offers a practical and efficient surrogate for muscle assessment based on routinely acquired chest CT images.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/cpf.70046","type":"journal-article","created":{"date-parts":[[2026,1,7]],"date-time":"2026-01-07T06:20:52Z","timestamp":1767766852000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Estimation of whole\u2010body skeletal muscle volume using pectoralis muscle area and anthropometric measurements from chest CT in a Korean population"],"prefix":"10.1111","volume":"46","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2822-8480","authenticated-orcid":false,"given":"Kiook","family":"Baek","sequence":"first","affiliation":[{"name":"Department of Preventive Medicine, College of Medicine Dongguk University Gyeongju Republic of 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